AWS Well-Architected Framework

AWS Well-
Architected Framework
AWS Well-Architected Framework

AWS Well-Architected Framework: AWS Well-Architected Framework
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Table of Contents
Abstract ............................................................................................................................................ 1
Abstract .................................................................................................................................... 1
Introduction ...................................................................................................................................... 2
Definitions ................................................................................................................................. 2
On Architecture ......................................................................................................................... 4
General Design Principles ............................................................................................................ 4
The Five Pillars of the Framework ........................................................................................................ 6
Operational Excellence ................................................................................................................ 6
Design Principles ................................................................................................................ 6
Definition .......................................................................................................................... 7
Best Practices .................................................................................................................... 7
Resources ........................................................................................................................ 13
Security ................................................................................................................................... 13
Design Principles .............................................................................................................. 13
Definition ........................................................................................................................ 14
Best Practices .................................................................................................................. 14
Resources ........................................................................................................................ 19
Reliability ................................................................................................................................ 19
Definition ........................................................................................................................ 20
Best Practices .................................................................................................................. 20
Resources ........................................................................................................................ 24
Performance Efficiency .............................................................................................................. 24
Definition ........................................................................................................................ 25
Best Practices .................................................................................................................. 25
Resources ........................................................................................................................ 30
Cost Optimization .................................................................................................................... 30
Definition ........................................................................................................................ 31
Best Practices .................................................................................................................. 32
Resources ........................................................................................................................ 35
The Review Process .......................................................................................................................... 37
Conclusion ....................................................................................................................................... 39
Contributors .................................................................................................................................... 40
Further Reading ............................................................................................................................... 41
Document Revisions .......................................................................................................................... 42
Appendix: Questions and Best Practices .............................................................................................. 44
Operational Excellence ............................................................................................................. 44
Organization ................................................................................................................... 44
Prepare .......................................................................................................................... 46
Operate ......................................................................................................................... 49
Evolve ............................................................................................................................ 51
Security ................................................................................................................................... 51
Security ........................................................................................................................... 52
Identity and Access Management ....................................................................................... 53
Detection ........................................................................................................................ 54
Infrastructure Protection ................................................................................................... 55
Data Protection ................................................................................................................ 56
Incident Response ............................................................................................................ 57
Reliability ................................................................................................................................ 58
Foundations ..................................................................................................................... 58
Workload Architecture ...................................................................................................... 59
Change Management ........................................................................................................ 61
iii

Failure Management ......................................................................................................... 62
Performance Efficiency .............................................................................................................. 65
Selection ......................................................................................................................... 65
Review ............................................................................................................................ 68
Monitoring ....................................................................................................................... 68
Tradeoffs ......................................................................................................................... 69
Cost Optimization .................................................................................................................... 70
Practice Cloud Financial Management ................................................................................. 70
Expenditure and usage awareness ...................................................................................... 70
Cost-effective resources ..................................................................................................... 72
Manage demand and supply resources ................................................................................ 74
Optimize over time ........................................................................................................... 74
Notices ............................................................................................................................................ 76
iv

Abstract
Publication date: July 2020 (Document Revisions (p. 42))
Abstract
The AWS Well-Architected Framework helps you understand the pros and cons of decisions you make
while building systems on AWS. By using the Framework you will learn architectural best practices for
designing and operating reliable, secure, eﬃcient, and cost-eﬀective systems in the cloud.
1

Definitions
Introduction
The AWS Well-Architected Framework helps you understand the pros and cons of decisions you make
while building systems on AWS. By using the Framework you will learn architectural best practices for
designing and operating reliable, secure, efficient, and cost-effective systems in the cloud. It provides
a way for you to consistently measure your architectures against best practices and identify areas
for improvement. The process for reviewing an architecture is a constructive conversation about
architectural decisions, and is not an audit mechanism. We believe that having well-architected systems
greatly increases the likelihood of business success.
AWS Solutions Architects have years of experience architecting solutions across a wide variety
of business verticals and use cases. We have helped design and review thousands of customers’
architectures on AWS. From this experience, we have identified best practices and core strategies for
architecting systems in the cloud.
The AWS Well-Architected Framework documents a set of foundational questions that allow you to
understand if a specific architecture aligns well with cloud best practices. The framework provides a
consistent approach to evaluating systems against the qualities you expect from modern cloud-based
systems, and the remediation that would be required to achieve those qualities. As AWS continues to
evolve, and we continue to learn more from working with our customers, we will continue to refine the
definition of well-architected.
This framework is intended for those in technology roles, such as chief technology officers (CTOs),
architects, developers, and operations team members. It describes AWS best practices and strategies
to use when designing and operating a cloud workload, and provides links to further implementation
details and architectural patterns. For more information, see the AWS Well-Architected homepage.
AWS also provides a service for reviewing your workloads at no charge. The AWS Well-Architected
Tool (AWS WA Tool) is a service in the cloud that provides a consistent process for you to review and
measure your architecture using the AWS Well-Architected Framework. The AWS WA Tool provides
recommendations for making your workloads more reliable, secure, efficient, and cost-effective.
To help you apply best practices, we have created AWS Well-Architected Labs, which provides you with
a repository of code and documentation to give you hands-on experience implementing best practices.
We also have teamed up with select AWS Partner Network (APN) Partners, who are members of the AWS
Well-Architected Partner program. These APN Partners have deep AWS knowledge, and can help you
review and improve your workloads.
Definitions
Every day, experts at AWS assist customers in architecting systems to take advantage of best practices
in the cloud. We work with you on making architectural trade-offs as your designs evolve. As you deploy
these systems into live environments, we learn how well these systems perform and the consequences of
those trade-offs.
Based on what we have learned, we have created the AWS Well-Architected Framework, which provides
a consistent set of best practices for customers and partners to evaluate architectures, and provides a set
of questions you can use to evaluate how well an architecture is aligned to AWS best practices.
The AWS Well-Architected Framework is based on five pillars — operational excellence, security,
reliability, performance efficiency, and cost optimization.
2

Definitions
Table 1. The pillars of the AWS Well-Architected Framework
Name Description
Operational Excellence The ability to support development and run
workloads effectively, gain insight into their
operations, and to continuously improve
supporting processes and procedures to deliver
business value.
Security The security pillar describes how to take
advantage of cloud technologies to protect data,
systems, and assets in a way that can improve
your security posture.
Reliability The reliability pillar encompasses the ability of
a workload to perform its intended function
correctly and consistently when it’s expected to.
This includes the ability to operate and test the
workload through its total lifecycle. This paper
provides in-depth, best practice guidance for
implementing reliable workloads on AWS.
Performance Efficiency The ability to use computing resources efficiently
to meet system requirements, and to maintain
that efficiency as demand changes and
technologies evolve.
Cost Optimization The ability to run systems to deliver business
value at the lowest price point.
In the AWS Well-Architected Framework, we use these terms:
• A component is the code, configuration, and AWS Resources that together deliver against a
requirement. A component is often the unit of technical ownership, and is decoupled from other
components.
• The term workload is used to identify a set of components that together deliver business value. A
workload is usually the level of detail that business and technology leaders communicate about.
• We think about architecture as being how components work together in a workload. How components
communicate and interact is often the focus of architecture diagrams.
• Milestones mark key changes in your architecture as it evolves throughout the product lifecycle
(design, implementation, testing, go live, and in production).
• Within an organization the technology portfolio is the collection of workloads that are required for
the business to operate.
When architecting workloads, you make trade-offs between pillars based on your business context.
These business decisions can drive your engineering priorities. You might optimize to reduce cost at the
expense of reliability in development environments, or, for mission-critical solutions, you might optimize
reliability with increased costs. In ecommerce solutions, performance can affect revenue and customer
propensity to buy. Security and operational excellence are generally not traded-off against the other
pillars.
3

On Architecture
On Architecture
In on-premises environments, customers often have a central team for technology architecture that acts
as an overlay to other product or feature teams to ensure they are following best practice. Technology
architecture teams typically include a set of roles such as: Technical Architect (infrastructure), Solutions
Architect (software), Data Architect, Networking Architect, and Security Architect. Often these teams use
TOGAF or the Zachman Framework as part of an enterprise architecture capability.
At AWS, we prefer to distribute capabilities into teams rather than having a centralized team with
that capability. There are risks when you choose to distribute decision making authority, for example,
ensuring that teams are meeting internal standards. We mitigate these risks in two ways. First, we have
practices (ways of doing things, process, standards, and accepted norms) that focus on enabling each
team to have that capability, and we put in place experts who ensure that teams raise the bar on the
standards they need to meet. Second, we implement mechanisms that carry out automated checks to
ensure standards are being met.
“Good intentions never work, you need good mechanisms to make anything happen” — Jeff
Bezos.
This means replacing humans best efforts with mechanisms (often automated) that check for compliance
with rules or process. This distributed approach is supported by the Amazon leadership principles,
and establishes a culture across all roles that works back from the customer. Working backward is a
fundamental part of our innovation process. We start with the customer and what they want, and let
that define and guide our efforts. Customer-obsessed teams build products in response to a customer
need.
For architecture, this means that we expect every team to have the capability to create architectures and
to follow best practices. To help new teams gain these capabilities or existing teams to raise their bar,
we enable access to a virtual community of principal engineers who can review their designs and help
them understand what AWS best practices are. The principal engineering community works to make
best practices visible and accessible. One way they do this, for example, is through lunchtime talks that
focus on applying best practices to real examples. These talks are recorded and can be used as part of
onboarding materials for new team members.
AWS best practices emerge from our experience running thousands of systems at internet scale. We
prefer to use data to define best practice, but we also use subject matter experts, like principal engineers,
to set them. As principal engineers see new best practices emerge, they work as a community to
ensure that teams follow them. In time, these best practices are formalized into our internal review
processes, as well as into mechanisms that enforce compliance. The Well-Architected Framework is the
customer-facing implementation of our internal review process, where we have codified our principal
engineering thinking across field roles, like Solutions Architecture and internal engineering teams. The
Well-Architected Framework is a scalable mechanism that lets you take advantage of these learnings.
By following the approach of a principal engineering community with distributed ownership of
architecture, we believe that a Well-Architected enterprise architecture can emerge that is driven by
customer need. Technology leaders (such as a CTOs or development managers), carrying out Well-
Architected reviews across all your workloads will allow you to better understand the risks in your
technology portfolio. Using this approach, you can identify themes across teams that your organization
could address by mechanisms, training, or lunchtime talks where your principal engineers can share their
thinking on specific areas with multiple teams.
General Design Principles
The Well-Architected Framework identifies a set of general design principles to facilitate good design in
the cloud:
4

General Design Principles
• Stop guessing your capacity needs: If you make a poor capacity decision when deploying a workload,
you might end up sitting on expensive idle resources or dealing with the performance implications of
limited capacity. With cloud computing, these problems can go away. You can use as much or as little
capacity as you need, and scale up and down automatically.
• Test systems at production scale: In the cloud, you can create a production-scale test environment on
demand, complete your testing, and then decommission the resources. Because you only pay for the
test environment when it's running, you can simulate your live environment for a fraction of the cost
of testing on premises.
• Automate to make architectural experimentation easier: Automation allows you to create and
replicate your workloads at low cost and avoid the expense of manual eﬀort. You can track changes to
your automation, audit the impact, and revert to previous parameters when necessary.
• Allow for evolutionary architectures: In a traditional environment, architectural decisions are often
implemented as static, onetime events, with a few major versions of a system during its lifetime.
As a business and its context continue to evolve, these initial decisions might hinder the system's
ability to deliver changing business requirements. In the cloud, the capability to automate and test on
demand lowers the risk of impact from design changes. This allows systems to evolve over time so that
businesses can take advantage of innovations as a standard practice.
• Drive architectures using data: In the cloud, you can collect data on how your architectural choices
aﬀect the behavior of your workload. This lets you make factbased decisions on how to improve your
workload. Your cloud infrastructure is code, so you can use that data to inform your architecture
choices and improvements over time.
• Improve through game days: Test how your architecture and processes perform by regularly
scheduling game days to simulate events in production. This will help you understand where
improvements can be made and can help develop organizational experience in dealing with events.
5

Operational Excellence
The Five Pillars of the Framework
Creating a software system is a lot like constructing a building. If the foundation is not solid, structural
problems can undermine the integrity and function of the building. When architecting technology
solutions, if you neglect the five pillars of operational excellence, security, reliability, performance
efficiency, and cost optimization, it can become challenging to build a system that delivers on your
expectations and requirements. Incorporating these pillars into your architecture will help you produce
stable and efficient systems. This will allow you to focus on the other aspects of design, such as
functional requirements.
Topics
• Operational Excellence (p. 6)
• Security (p. 13)
• Reliability (p. 19)
• Performance Efficiency (p. 24)
• Cost Optimization (p. 30)
The Operational Excellence pillar includes the ability to support development and run workloads
effectively, gain insight into their operations, and to continuously improve supporting processes and
procedures to deliver business value.
The operational excellence pillar provides an overview of design principles, best practices, and questions.
You can find prescriptive guidance on implementation in the Operational Excellence Pillar whitepaper.
Topics
• Design Principles (p. 6)
• Definition (p. 7)
• Best Practices (p. 7)
• Resources (p. 13)
Design Principles
There are five design principles for operational excellence in the cloud:
• Perform operations as code: In the cloud, you can apply the same engineering discipline that you use
for application code to your entire environment. You can define your entire workload (applications,
infrastructure) as code and update it with code. You can implement your operations procedures as
code and automate their execution by triggering them in response to events. By performing operations
as code, you limit human error and enable consistent responses to events.
• Make frequent, small, reversible changes: Design workloads to allow components to be updated
regularly. Make changes in small increments that can be reversed if they fail (without affecting
customers when possible).
• Refine operations procedures frequently: As you use operations procedures, look for opportunities
to improve them. As you evolve your workload, evolve your procedures appropriately. Set up regular
6

Definition
game days to review and validate that all procedures are effective and that teams are familiar with
them.
• Anticipate failure: Perform “pre-mortem” exercises to identify potential sources of failure so that
they can be removed or mitigated. Test your failure scenarios and validate your understanding of their
impact. Test your response procedures to ensure that they are effective, and that teams are familiar
with their execution. Set up regular game days to test workloads and team responses to simulated
events.
• Learn from all operational failures: Drive improvement through lessons learned from all operational
events and failures. Share what is learned across teams and through the entire organization.
Definition
There are four best practice areas for operational excellence in the cloud:
• Organization
• Prepare
• Operate
• Evolve
Your organization’s leadership defines business objectives. Your organization must understand
requirements and priorities and use these to organize and conduct work to support the achievement of
business outcomes. Your workload must emit the information necessary to support it. Implementing
services to enable integration, deployment, and delivery of your workload will enable an increased flow
of beneficial changes into production by automating repetitive processes.
There may be risks inherent in the operation of your workload. You must understand those risks and
make an informed decision to enter production. Your teams must be able to support your workload.
Business and operational metrics derived from desired business outcomes will enable you to understand
the health of your workload, your operations activities, and respond to incidents. Your priorities will
change as your business needs and business environment changes. Use these as a feedback loop to
continually drive improvement for your organization and the operation of your workload.
Best Practices
Topics
• Organization (p. 7)
• Prepare (p. 10)
• Operate (p. 11)
• Evolve (p. 12)
Organization
Your teams need to have a shared understanding of your entire workload, their role in it, and shared
business goals to set the priorities that will enable business success. Well-defined priorities will maximize
the benefits of your efforts. Evaluate internal and external customer needs involving key stakeholders,
including business, development, and operations teams, to determine where to focus efforts. Evaluating
customer needs will ensure that you have a thorough understanding of the support that is required
to achieve business outcomes. Ensure that you are aware of guidelines or obligations defined by your
organizational governance and external factors, such as regulatory compliance requirements and
industry standards, that may mandate or emphasize specific focus. Validate that you have mechanisms
to identify changes to internal governance and external compliance requirements. If no requirements
7

Best Practices
are identified, ensure that you have applied due diligence to this determination. Review your priorities
regularly so that they can be updated as needs change.
Evaluate threats to the business (for example, business risk and liabilities, and information security
threats) and maintain this information in a risk registry. Evaluate the impact of risks, and tradeoffs
between competing interests or alternative approaches. For example, accelerating speed to market for
new features may be emphasized over cost optimization, or you may choose a relational database for
non-relational data to simplify the effort to migrate a system without refactoring. Manage benefits and
risks to make informed decisions when determining where to focus efforts. Some risks or choices may be
acceptable for a time, it may be possible to mitigate associated risks, or it may become unacceptable to
allow a risk to remain, in which case you will take action to address the risk.
Your teams must understand their part in achieving business outcomes. Teams need to understand
their roles in the success of other teams, the role of other teams in their success, and have shared
goals. Understanding responsibility, ownership, how decisions are made, and who has authority to
make decisions will help focus efforts and maximize the benefits from your teams. The needs of a team
will be shaped by the customer they support, their organization, the makeup of the team, and the
characteristics of their workload. It's unreasonable to expect a single operating model to be able to
support all teams and their workloads in your organization.
Ensure that there are identified owners for each application, workload, platform, and infrastructure
component, and that each process and procedure has an identified owner responsible for its definition,
and owners responsible for their performance.
Having understanding of the business value of each component, process, and procedure, of why those
resources are in place or activities are performed, and why that ownership exists will inform the actions
of your team members. Clearly define the responsibilities of team members so that they may act
appropriately and have mechanisms to identify responsibility and ownership. Have mechanisms to
request additions, changes, and exceptions so that you do not constrain innovation. Define agreements
between teams describing how they work together to support each other and your business outcomes.
Provide support for your team members so that they can be more effective in taking action and
supporting your business outcomes. Engaged senior leadership should set expectations and measure
success. They should be the sponsor, advocate, and driver for the adoption of best practices and
evolution of the organization. Empower team members to take action when outcomes are at risk to
minimize impact and encourage them to escalate to decision makers and stakeholders when they
believe there is a risk so that it can be addressed and incidents avoided. Provide timely, clear, and
actionable communications of known risks and planned events so that team members can take timely
and appropriate action.
Encourage experimentation to accelerate learning and keep team members interested and engaged.
Teams must grow their skill sets to adopt new technologies, and to support changes in demand and
responsibilities. Support and encourage this by providing dedicated structured time for learning. Ensure
your team members have the resources, both tools and team members, to be successful and scale
to support your business outcomes. Leverage cross-organizational diversity to seek multiple unique
perspectives. Use this perspective to increase innovation, challenge your assumptions, and reduce the
risk of confirmation bias. Grow inclusion, diversity, and accessibility within your teams to gain beneficial
perspectives.
If there are external regulatory or compliance requirements that apply to your organization, you
should use the resources provided by AWS Cloud Compliance to help educate your teams so that they
can determine the impact on your priorities. The Well-Architected Framework emphasizes learning,
measuring, and improving. It provides a consistent approach for you to evaluate architectures, and
implement designs that will scale over time. AWS provides the AWS Well-Architected Tool to help you
review your approach prior to development, the state of your workloads prior to production, and the
state of your workloads in production. You can compare workloads to the latest AWS architectural best
practices, monitor their overall status, and gain insight into potential risks. AWS Trusted Advisor is a tool
that provides access to a core set of checks that recommend optimizations that may help shape your
8

Best Practices
priorities. Business and Enterprise Support customers receive access to additional checks focusing on
security, reliability, performance, and cost-optimization that can further help shape their priorities.
AWS can help you educate your teams about AWS and its services to increase their understanding of
how their choices can have an impact on your workload. You should use the resources provided by
AWS Support (AWS Knowledge Center, AWS Discussion Forums, and AWS Support Center) and AWS
Documentation to educate your teams. Reach out to AWS Support through AWS Support Center for help
with your AWS questions. AWS also shares best practices and patterns that we have learned through the
operation of AWS in The Amazon Builders' Library. A wide variety of other useful information is available
through the AWS Blog and The Official AWS Podcast. AWS Training and Certification provides some free
training through self-paced digital courses on AWS fundamentals. You can also register for instructor-led
training to further support the development of your teams’ AWS skills.
You should use tools or services that enable you to centrally govern your environments across accounts,
such as AWS Organizations, to help manage your operating models. Services like AWS Control Tower
expand this management capability by enabling you to define blueprints (supporting your operating
models) for the setup of accounts, apply ongoing governance using AWS Organizations, and automate
provisioning of new accounts. Managed Services providers such as AWS Managed Services, AWS Managed
Services Partners, or Managed Services Providers in the AWS Partner Network, provide expertise
implementing cloud environments, and support your security and compliance requirements and business
goals. Adding Managed Services to your operating model can save you time and resources, and lets you
keep your internal teams lean and focused on strategic outcomes that will differentiate your business,
rather than developing new skills and capabilities.
The following questions focus on these considerations for operational excellence. (For a list of
operational excellence questions and best practices, see the Appendix (p. 44).).
OPS 1: How do you determine what your priorities are?
Everyone needs to understand their part in enabling business success. Have shared goals in order to set
priorities for resources. This will maximize the benefits of your efforts.
OPS 2: How do you structure your organization to support your business outcomes?
make decisions will help focus efforts and maximize the benefits from your teams.
OPS 3: How does your organizational culture support your business outcomes?
supporting your business outcome.
You might find that you want to emphasize a small subset of your priorities at some point in time.
Use a balanced approach over the long term to ensure the development of needed capabilities
and management of risk. Review your priorities regularly and update them as needs change. When
responsibility and ownership are undefined or unknown, you are at risk of both not performing necessary
action in a timely fashion and of redundant and potentially conflicting efforts emerging to address
those needs. Organizational culture has a direct impact on team member job satisfaction and retention.
Enable the engagement and capabilities of your team members to enable the success of your business.
Experimentation is required for innovation to happen and turn ideas into outcomes. Recognize that an
undesired result is a successful experiment that has identified a path that will not lead to success.
9

Best Practices
Prepare
To prepare for operational excellence, you have to understand your workloads and their expected
behaviors. You will then be able to design them to provide insight to their status and build the
procedures to support them.
Design your workload so that it provides the information necessary for you to understand its internal
state (for example, metrics, logs, events, and traces) across all components in support of observability
and investigating issues. Iterate to develop the telemetry necessary to monitor the health of your
workload, identify when outcomes are at risk, and enable effective responses. When instrumenting your
workload, capture a broad set of information to enable situational awareness (for example, changes in
state, user activity, privilege access, utilization counters), knowing that you can use filters to select the
most useful information over time.
Adopt approaches that improve the flow of changes into production and that enable refactoring, fast
feedback on quality, and bug fixing. These accelerate beneficial changes entering production, limit issues
deployed, and enable rapid identification and remediation of issues introduced through deployment
activities or discovered in your environments.
Adopt approaches that provide fast feedback on quality and enable rapid recovery from changes that do
not have desired outcomes. Using these practices mitigates the impact of issues introduced through the
deployment of changes. Plan for unsuccessful changes so that you are able to respond faster if necessary
and test and validate the changes you make. Be aware of planned activities in your environments so that
you can manage the risk of changes impacting planned activities. Emphasize frequent, small, reversible
changes to limit the scope of change. This results in easier troubleshooting and faster remediation with
the option to roll back a change. It also means you are able to get the benefit of valuable changes more
frequently.
Evaluate the operational readiness of your workload, processes, procedures, and personnel to
understand the operational risks related to your workload. You should use a consistent process (including
manual or automated checklists) to know when you are ready to go live with your workload or a change.
This will also enable you to find any areas that you need to make plans to address. Have runbooks
that document your routine activities and playbooks that guide your processes for issue resolution.
Understand the benefits and risks to make informed decisions to allow changes to enter production.
AWS enables you to view your entire workload (applications, infrastructure, policy, governance, and
operations) as code. This means you can apply the same engineering discipline that you use for
application code to every element of your stack and share these across teams or organizations to
magnify the benefits of development efforts. Use operations as code in the cloud and the ability to
safely experiment to develop your workload, your operations procedures, and practice failure. Using AWS
CloudFormation enables you to have consistent, templated, sandbox development, test, and production
environments with increasing levels of operations control.
The following questions focus on these considerations for operational excellence.
OPS 4: How do you design your workload so that you can understand its state?
Design your workload so that it provides the information necessary across all components (for
example, metrics, logs, and traces) for you to understand its internal state. This enables you to provide
effective responses when appropriate.
OPS 5: How do you reduce defects, ease remediation, and improve flow into production?
Adopt approaches that improve flow of changes into production, that enable refactoring, fast feedback
on quality, and bug fixing. These accelerate beneficial changes entering production, limit issues
10

Best Practices
OPS 5: How do you reduce defects, ease remediation, and improve flow into production?
activities.
OPS 6: How do you mitigate deployment risks?
Adopt approaches that provide fast feedback on quality and enable rapid recovery from changes that
do not have desired outcomes. Using these practices mitigates the impact of issues introduced through
the deployment of changes.
OPS 7: How do you know that you are ready to support a workload?
Evaluate the operational readiness of your workload, processes and procedures, and personnel to
understand the operational risks related to your workload.
Invest in implementing operations activities as code to maximize the productivity of operations
personnel, minimize error rates, and enable automated responses. Use “pre-mortems” to anticipate
failure and create procedures where appropriate. Apply metadata using Resource Tags and AWS Resource
Groups following a consistent tagging strategy to enable identification of your resources. Tag your
resources for organization, cost accounting, access controls, and targeting the execution of automated
operations activities. Adopt deployment practices that take advantage of the elasticity of the cloud to
facilitate development activities, and pre-deployment of systems for faster implementations. When
you make changes to the checklists you use to evaluate your workloads, plan what you will do with live
systems that no longer comply.
Operate
Successful operation of a workload is measured by the achievement of business and customer outcomes.
Define expected outcomes, determine how success will be measured, and identify metrics that will be
used in those calculations to determine if your workload and operations are successful. Operational
health includes both the health of the workload and the health and success of the operations activities
performed in support of the workload (for example, deployment and incident response). Establish
metrics baselines for improvement, investigation, and intervention, collect and analyze your metrics,
and then validate your understanding of operations success and how it changes over time. Use
collected metrics to determine if you are satisfying customer and business needs, and identify areas for
improvement.
Efficient and effective management of operational events is required to achieve operational excellence.
This applies to both planned and unplanned operational events. Use established runbooks for well-
understood events, and use playbooks to aid in investigation and resolution of issues. Prioritize
responses to events based on their business and customer impact. Ensure that if an alert is raised in
response to an event, there is an associated process to be executed, with a specifically identified owner.
Define in advance the personnel required to resolve an event and include escalation triggers to engage
additional personnel, as it becomes necessary, based on urgency and impact. Identify and engage
individuals with the authority to make a decision on courses of action where there will be a business
impact from an event response not previously addressed.
Communicate the operational status of workloads through dashboards and notifications that are tailored
to the target audience (for example, customer, business, developers, operations) so that they may take
appropriate action, so that their expectations are managed, and so that they are informed when normal
operations resume.
11

Best Practices
In AWS, you can generate dashboard views of your metrics collected from workloads and natively from
AWS. You can leverage CloudWatch or third-party applications to aggregate and present business,
workload, and operations level views of operations activities. AWS provides workload insights through
logging capabilities including AWS X-Ray, CloudWatch, CloudTrail, and VPC Flow Logs enabling the
identification of workload issues in support of root cause analysis and remediation.
The following questions focus on these considerations for operational excellence.
OPS 8: How do you understand the health of your workload?
Define, capture, and analyze workload metrics to gain visibility to workload events so that you can take
appropriate action.
OPS 9: How do you understand the health of your operations?
Define, capture, and analyze operations metrics to gain visibility to operations events so that you can
take appropriate action.
OPS 10: How do you manage workload and operations events?
Prepare and validate procedures for responding to events to minimize their disruption to your
workload.
All of the metrics you collect should be aligned to a business need and the outcomes they support.
Develop scripted responses to well-understood events and automate their performance in response to
recognizing the event.
Evolve
You must learn, share, and continuously improve to sustain operational excellence. Dedicate work
cycles to making continuous incremental improvements. Perform post-incident analysis of all customer
impacting events. Identify the contributing factors and preventative action to limit or prevent recurrence.
Communicate contributing factors with affected communities as appropriate. Regularly evaluate
and prioritize opportunities for improvement (for example, feature requests, issue remediation, and
compliance requirements), including both the workload and operations procedures.
Include feedback loops within your procedures to rapidly identify areas for improvement and capture
learnings from the execution of operations.
Share lessons learned across teams to share the benefits of those lessons. Analyze trends within lessons
learned and perform cross-team retrospective analysis of operations metrics to identify opportunities
and methods for improvement. Implement changes intended to bring about improvement and evaluate
the results to determine success.
On AWS, you can export your log data to Amazon S3 or send logs directly to Amazon S3 for long-term
storage. Using AWS Glue, you can discover and prepare your log data in Amazon S3 for analytics, and
store associated metadata in the AWS Glue Data Catalog. Amazon Athena, through its native integration
with AWS Glue, can then be used to analyze your log data, querying it using standard SQL. Using a
business intelligence tool like Amazon QuickSight, you can visualize, explore, and analyze your data.
Discovering trends and events of interest that may drive improvement.
The following question focuses on these considerations for operational excellence.
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OPS 11: How do you evolve operations?
Dedicate time and resources for continuous incremental improvement to evolve the effectiveness and
efficiency of your operations.
Successful evolution of operations is founded in: frequent small improvements; providing safe
environments and time to experiment, develop, and test improvements; and environments in which
learning from failures is encouraged. Operations support for sandbox, development, test, and production
environments, with increasing level of operational controls, facilitates development and increases the
predictability of successful results from changes deployed into production.
Resources
Refer to the following resources to learn more about our best practices for Operational Excellence.
Documentation
• DevOps and AWS
Whitepaper
• Operational Excellence Pillar
Video
• DevOps at Amazon
Security
The Security pillar encompasses the ability to protect data, systems, and assets to take advantage of
cloud technologies to improve your security.
The security pillar provides an overview of design principles, best practices, and questions. You can find
prescriptive guidance on implementation in the Security Pillar whitepaper.
Topics
Design Principles
There are seven design principles for security in the cloud:
• Implement a strong identity foundation: Implement the principle of least privilege and enforce
separation of duties with appropriate authorization for each interaction with your AWS resources.
Centralize identity management, and aim to eliminate reliance on long-term static credentials.
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Definition
• Enable traceability: Monitor, alert, and audit actions and changes to your environment in real time.
Integrate log and metric collection with systems to automatically investigate and take action.
• Apply security at all layers: Apply a defense in depth approach with multiple security controls. Apply
to all layers (for example, edge of network, VPC, load balancing, every instance and compute service,
operating system, application, and code).
• Automate security best practices: Automated software-based security mechanisms improve your
ability to securely scale more rapidly and cost-effectively. Create secure architectures, including the
implementation of controls that are defined and managed as code in version-controlled templates.
• Protect data in transit and at rest: Classify your data into sensitivity levels and use mechanisms, such
as encryption, tokenization, and access control where appropriate.
• Keep people away from data: Use mechanisms and tools to reduce or eliminate the need for direct
access or manual processing of data. This reduces the risk of mishandling or modification and human
error when handling sensitive data.
• Prepare for security events: Prepare for an incident by having incident management and investigation
policy and processes that align to your organizational requirements. Run incident response simulations
and use tools with automation to increase your speed for detection, investigation, and recovery.
Definition
There are six best practice areas for security in the cloud:
• Security
• Identity and Access Management
• Detection
• Infrastructure Protection
• Data Protection
• Incident Response
Before you architect any workload, you need to put in place practices that influence security. You
will want to control who can do what. In addition, you want to be able to identify security incidents,
protect your systems and services, and maintain the confidentiality and integrity of data through data
protection. You should have a well-defined and practiced process for responding to security incidents.
These tools and techniques are important because they support objectives such as preventing financial
loss or complying with regulatory obligations.
The AWS Shared Responsibility Model enables organizations that adopt the cloud to achieve their
security and compliance goals. Because AWS physically secures the infrastructure that supports our
cloud services, as an AWS customer you can focus on using services to accomplish your goals. The AWS
Cloud also provides greater access to security data and an automated approach to responding to security
events.
Best Practices
Topics
• Identity and Access Management (p. 15)
• Detection (p. 16)
• Infrastructure Protection (p. 17)
• Data Protection (p. 17)
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• Incident Response (p. 18)
Security
To operate your workload securely, you must apply overarching best practices to every area of security.
Take requirements and processes that you have defined in operational excellence at an organizational
and workload level, and apply them to all areas.
Staying up to date with AWS and industry recommendations and threat intelligence helps you evolve
your threat model and control objectives. Automating security processes, testing, and validation allow
you to scale your security operations.
The following question focuses on these considerations for security. (For a list of security questions and
best practices, see the Appendix (p. 51).).
SEC 1: How do you securely operate your workload?
To operate your workload securely, you must apply overarching best practices to every area of security.
Take requirements and processes that you have defined in operational excellence at an organizational
and workload level, and apply them to all areas. Staying up to date with recommendations from AWS,
industry sources, and threat intelligence helps you evolve your threat model and control objectives.
Automating security processes, testing, and validation allow you to scale your security operations.
In AWS, segregating different workloads by account, based on their function and compliance or data
sensitivity requirements, is a recommended approach.
Identity and Access Management
Identity and access management are key parts of an information security program, ensuring that only
authorized and authenticated users and components are able to access your resources, and only in a
manner that you intend. For example, you should define principals (that is, accounts, users, roles, and
services that can perform actions in your account), build out policies aligned with these principals, and
implement strong credential management. These privilege-management elements form the core of
authentication and authorization.
In AWS, privilege management is primarily supported by the AWS Identity and Access Management (IAM)
service, which allows you to control user and programmatic access to AWS services and resources. You
should apply granular policies, which assign permissions to a user, group, role, or resource. You also
have the ability to require strong password practices, such as complexity level, avoiding re-use, and
enforcing multi-factor authentication (MFA). You can use federation with your existing directory service.
For workloads that require systems to have access to AWS, IAM enables secure access through roles,
instance profiles, identity federation, and temporary credentials.
The following questions focus on these considerations for security.
SEC 2: How do you manage identities for people and machines?
There are two types of identities you need to manage when approaching operating secure AWS
workloads. Understanding the type of identity you need to manage and grant access helps you ensure
the right identities have access to the right resources under the right conditions.
Human Identities: Your administrators, developers, operators, and end users require an identity to
access your AWS environments and applications. These are members of your organization, or external
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SEC 2: How do you manage identities for people and machines?
users with whom you collaborate, and who interact with your AWS resources via a web browser, client
application, or interactive command-line tools.
Machine Identities: Your service applications, operational tools, and workloads require an identity to
make requests to AWS services, for example, to read data. These identities include machines running
in your AWS environment such as Amazon EC2 instances or AWS Lambda functions. You may also
manage machine identities for external parties who need access. Additionally, you may also have
machines outside of AWS that need access to your AWS environment.
SEC 3: How do you manage permissions for people and machines?
Manage permissions to control access to people and machine identities that require access to AWS and
your workload. Permissions control who can access what, and under what conditions.
Credentials must not be shared between any user or system. User access should be granted using
a least-privilege approach with best practices including password requirements and MFA enforced.
Programmatic access including API calls to AWS services should be performed using temporary and
limited-privilege credentials such as those issued by the AWS Security Token Service.
AWS provides resources that can help you with Identity and access management. To help learn best
practices, explore our hands-on labs on managing credentials & authentication, controlling human
access, and controlling programmatic access.
Detection
You can use detective controls to identify a potential security threat or incident. They are an essential
part of governance frameworks and can be used to support a quality process, a legal or compliance
obligation, and for threat identification and response efforts. There are different types of detective
controls. For example, conducting an inventory of assets and their detailed attributes promotes more
effective decision making (and lifecycle controls) to help establish operational baselines. You can also
use internal auditing, an examination of controls related to information systems, to ensure that practices
meet policies and requirements and that you have set the correct automated alerting notifications based
on defined conditions. These controls are important reactive factors that can help your organization
identify and understand the scope of anomalous activity.
In AWS, you can implement detective controls by processing logs, events, and monitoring that allows
for auditing, automated analysis, and alarming. CloudTrail logs, AWS API calls, and CloudWatch provide
monitoring of metrics with alarming, and AWS Config provides configuration history. Amazon GuardDuty
is a managed threat detection service that continuously monitors for malicious or unauthorized behavior
to help you protect your AWS accounts and workloads. Service-level logs are also available, for example,
you can use Amazon Simple Storage Service (Amazon S3) to log access requests.
The following question focuses on these considerations for security.
SEC 4: How do you detect and investigate security events?
Capture and analyze events from logs and metrics to gain visibility. Take action on security events and
potential threats to help secure your workload.
Log management is important to a Well-Architected workload for reasons ranging from security
or forensics to regulatory or legal requirements. It is critical that you analyze logs and respond to
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them so that you can identify potential security incidents. AWS provides functionality that makes log
management easier to implement by giving you the ability to define a data-retention lifecycle or define
where data will be preserved, archived, or eventually deleted. This makes predictable and reliable data
handling simpler and more cost effective.
Infrastructure Protection
Infrastructure protection encompasses control methodologies, such as defense in depth, necessary to
meet best practices and organizational or regulatory obligations. Use of these methodologies is critical
for successful, ongoing operations in either the cloud or on-premises.
In AWS, you can implement stateful and stateless packet inspection, either by using AWS-native
technologies or by using partner products and services available through the AWS Marketplace. You
should use Amazon Virtual Private Cloud (Amazon VPC) to create a private, secured, and scalable
environment in which you can define your topology—including gateways, routing tables, and public and
private subnets.
SEC 5: How do you protect your network resources?
Any workload that has some form of network connectivity, whether it’s the internet or a private
network, requires multiple layers of defense to help protect from external and internal network-based
threats.
SEC 6: How do you protect your compute resources?
Compute resources in your workload require multiple layers of defense to help protect from external
and internal threats. Compute resources include EC2 instances, containers, AWS Lambda functions,
database services, IoT devices, and more.
Multiple layers of defense are advisable in any type of environment. In the case of infrastructure
protection, many of the concepts and methods are valid across cloud and on-premises models. Enforcing
boundary protection, monitoring points of ingress and egress, and comprehensive logging, monitoring,
and alerting are all essential to an effective information security plan.
AWS customers are able to tailor, or harden, the configuration of an Amazon Elastic Compute Cloud
(Amazon EC2), Amazon Elastic Container Service (Amazon ECS) container, or AWS Elastic Beanstalk
instance, and persist this configuration to an immutable Amazon Machine Image (AMI). Then, whether
triggered by Auto Scaling or launched manually, all new virtual servers (instances) launched with this
AMI receive the hardened configuration.
Data Protection
Before architecting any system, foundational practices that influence security should be in place.
For example, data classification provides a way to categorize organizational data based on levels of
sensitivity, and encryption protects data by way of rendering it unintelligible to unauthorized access.
These tools and techniques are important because they support objectives such as preventing financial
loss or complying with regulatory obligations.
In AWS, the following practices facilitate protection of data:
• As an AWS customer you maintain full control over your data.
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• AWS makes it easier for you to encrypt your data and manage keys, including regular key rotation,
which can be easily automated by AWS or maintained by you.
• Detailed logging that contains important content, such as file access and changes, is available.
• AWS has designed storage systems for exceptional resiliency. For example, Amazon S3 Standard,
S3 Standard–IA, S3 One Zone-IA, and Amazon Glacier are all designed to provide 99.999999999%
durability of objects over a given year. This durability level corresponds to an average annual expected
loss of 0.000000001% of objects.
• Versioning, which can be part of a larger data lifecycle management process, can protect against
accidental overwrites, deletes, and similar harm.
• AWS never initiates the movement of data between Regions. Content placed in a Region will remain in
that Region unless you explicitly enable a feature or leverage a service that provides that functionality.
SEC 7: How do you classify your data?
Classification provides a way to categorize data, based on criticality and sensitivity in order to help you
determine appropriate protection and retention controls.
SEC 8: How do you protect your data at rest?
Protect your data at rest by implementing multiple controls, to reduce the risk of unauthorized access
or mishandling.
SEC 9: How do you protect your data in transit?
Protect your data in transit by implementing multiple controls to reduce the risk of unauthorized
access or loss.
AWS provides multiple means for encrypting data at rest and in transit. We build features into our
services that make it easier to encrypt your data. For example, we have implemented server-side
encryption (SSE) for Amazon S3 to make it easier for you to store your data in an encrypted form. You
can also arrange for the entire HTTPS encryption and decryption process (generally known as SSL
termination) to be handled by Elastic Load Balancing (ELB).
Incident Response
Even with extremely mature preventive and detective controls, your organization should still put
processes in place to respond to and mitigate the potential impact of security incidents. The architecture
of your workload strongly affects the ability of your teams to operate effectively during an incident, to
isolate or contain systems, and to restore operations to a known good state. Putting in place the tools
and access ahead of a security incident, then routinely practicing incident response through game days,
will help you ensure that your architecture can accommodate timely investigation and recovery.
In AWS, the following practices facilitate effective incident response:
• Detailed logging is available that contains important content, such as file access and changes.
• Events can be automatically processed and trigger tools that automate responses through the use of
AWS APIs.
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• You can pre-provision tooling and a “clean room” using AWS CloudFormation. This allows you to carry
out forensics in a safe, isolated environment.
The following question focuses on these considerations for security.
SEC 10: How do you anticipate, respond to, and recover from incidents?
Preparation is critical to timely and eﬀective investigation, response to, and recovery from security
incidents to help minimize disruption to your organization.
Ensure that you have a way to quickly grant access for your security team, and automate the isolation of
instances as well as the capturing of data and state for forensics.
Resources
Refer to the following resources to learn more about our best practices for Security.
Documentation
• AWS Cloud Security
• AWS Compliance
• AWS Security Blog
Whitepaper
• Security Pillar
• AWS Security Overview
• AWS Security Best Practices
• AWS Risk and Compliance
Video
• AWS Security State of the Union
• Shared Responsibility Overview
Reliability
The Reliability pillar encompasses the ability of a workload to perform its intended function correctly
and consistently when it’s expected to. This includes the ability to operate and test the workload
through its total lifecycle. This paper provides in-depth, best practice guidance for implementing reliable
workloads on AWS.
The reliability pillar provides an overview of design principles, best practices, and questions. You can ﬁnd
prescriptive guidance on implementation in the Reliability Pillar whitepaper.
Topics
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Design Principles
Design Principles
There are five design principles for reliability in the cloud:
• Automatically recover from failure: By monitoring a workload for key performance indicators
(KPIs), you can trigger automation when a threshold is breached. These KPIs should be a measure of
business value, not of the technical aspects of the operation of the service. This allows for automatic
notification and tracking of failures, and for automated recovery processes that work around or repair
the failure. With more sophisticated automation, it’s possible to anticipate and remediate failures
before they occur.
• Test recovery procedures: In an on-premises environment, testing is often conducted to prove
that the workload works in a particular scenario. Testing is not typically used to validate recovery
strategies. In the cloud, you can test how your workload fails, and you can validate your recovery
procedures. You can use automation to simulate different failures or to recreate scenarios that led to
failures before. This approach exposes failure pathways that you can test and fix before a real failure
scenario occurs, thus reducing risk.
• Scale horizontally to increase aggregate workload availability: Replace one large resource with
multiple small resources to reduce the impact of a single failure on the overall workload. Distribute
requests across multiple, smaller resources to ensure that they don’t share a common point of failure.
• Stop guessing capacity: A common cause of failure in on-premises workloads is resource saturation,
when the demands placed on a workload exceed the capacity of that workload (this is often the
objective of denial of service attacks). In the cloud, you can monitor demand and workload utilization,
and automate the addition or removal of resources to maintain the optimal level to satisfy demand
without over- or under-provisioning. There are still limits, but some quotas can be controlled and
others can be managed (see Manage Service Quotas and Constraints).
• Manage change in automation: Changes to your infrastructure should be made using automation. The
changes that need to be managed include changes to the automation, which then can be tracked and
reviewed.
Definition
There are four best practice areas for reliability in the cloud:
• Foundations
• Workload Architecture
• Change Management
• Failure Management
To achieve reliability you must start with the foundations — an environment where service quotas and
network topology accommodate the workload. The workload architecture of the distributed system
must be designed to prevent and mitigate failures. The workload must handle changes in demand or
requirements, and it must be designed to detect failure and automatically heal itself.
Best Practices
Topics
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Best Practices
• Foundations (p. 21)
• Workload Architecture (p. 21)
• Change Management (p. 22)
• Failure Management (p. 23)
Foundations
Foundational requirements are those whose scope extends beyond a single workload or project. Before
architecting any system, foundational requirements that influence reliability should be in place. For
example, you must have sufficient network bandwidth to your data center.
With AWS, most of these foundational requirements are already incorporated or can be addressed
as needed. The cloud is designed to be nearly limitless, so it’s the responsibility of AWS to satisfy the
requirement for sufficient networking and compute capacity, leaving you free to change resource size
and allocations on demand.
The following questions focus on these considerations for reliability. (For a list of reliability questions and
best practices, see the Appendix (p. 58).).
REL 1: How do you manage service quotas and constraints?
For cloud-based workload architectures, there are service quotas (which are also referred to as service
limits). These quotas exist to prevent accidentally provisioning more resources than you need and
to limit request rates on API operations so as to protect services from abuse. There are also resource
constraints, for example, the rate that you can push bits down a fiber-optic cable, or the amount of
storage on a physical disk.
REL 2: How do you plan your network topology?
Workloads often exist in multiple environments. These include multiple cloud environments (both
publicly accessible and private) and possibly your existing data center infrastructure. Plans must
include network considerations such as intra- and inter-system connectivity, public IP address
management, private IP address management, and domain name resolution.
limits). These quotas exist to prevent accidentally provisioning more resources than you need and to
limit request rates on API operations to protect services from abuse. Workloads often exist in multiple
environments. You must monitor and manage these quotas for all workload environments. These include
multiple cloud environments (both publicly accessible and private) and may include your existing data
center infrastructure. Plans must include network considerations, such as intrasystem and intersystem
connectivity, public IP address management, private IP address management, and domain name
resolution.
Workload Architecture
A reliable workload starts with upfront design decisions for both software and infrastructure. Your
architecture choices will impact your workload behavior across all five Well-Architected pillars. For
reliability, there are specific patterns you must follow.
With AWS, workload developers have their choice of languages and technologies to use. AWS SDKs take
the complexity out of coding by providing language-specific APIs for AWS services. These SDKs, plus the
choice of languages, allow developers to implement the reliability best practices listed here. Developers
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can also read about and learn from how Amazon builds and operates software in The Amazon Builders'
Library.
The following questions focus on these considerations for reliability.
REL 3: How do you design your workload service architecture?
Build highly scalable and reliable workloads using a service-oriented architecture (SOA) or a
microservices architecture. Service-oriented architecture (SOA) is the practice of making software
components reusable via service interfaces. Microservices architecture goes further to make
components smaller and simpler.
REL 4: How do you design interactions in a distributed system to prevent failures?
Distributed systems rely on communications networks to interconnect components, such as servers
or services. Your workload must operate reliably despite data loss or latency in these networks.
Components of the distributed system must operate in a way that does not negatively impact other
components or the workload. These best practices prevent failures and improve mean time between
failures (MTBF).
REL 5: How do you design interactions in a distributed system to mitigate or withstand failures?
Distributed systems rely on communications networks to interconnect components (such as servers
or services). Your workload must operate reliably despite data loss or latency over these networks.
components or the workload. These best practices enable workloads to withstand stresses or failures,
more quickly recover from them, and mitigate the impact of such impairments. The result is improved
mean time to recovery (MTTR).
components or the workload.
Change Management
Changes to your workload or its environment must be anticipated and accommodated to achieve reliable
operation of the workload. Changes include those imposed on your workload, such as spikes in demand,
as well as those from within, such as feature deployments and security patches.
Using AWS, you can monitor the behavior of a workload and automate the response to KPIs. For
example, your workload can add additional servers as a workload gains more users. You can control who
has permission to make workload changes and audit the history of these changes.
REL 6: How do you monitor workload resources?
Logs and metrics are powerful tools to gain insight into the health of your workload. You can configure
your workload to monitor logs and metrics and send notifications when thresholds are crossed or
significant events occur. Monitoring enables your workload to recognize when low-performance
thresholds are crossed or failures occur, so it can recover automatically in response.
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REL 7: How do you design your workload to adapt to changes in demand?
A scalable workload provides elasticity to add or remove resources automatically so that they closely
match the current demand at any given point in time.
REL 8: How do you implement change?
Controlled changes are necessary to deploy new functionality, and to ensure that the workloads
and the operating environment are running known software and can be patched or replaced in a
predictable manner. If these changes are uncontrolled, then it makes it difficult to predict the effect of
these changes, or to address issues that arise because of them.
When you architect a workload to automatically add and remove resources in response to changes
in demand, this not only increases reliability but also ensures that business success doesn't become
a burden. With monitoring in place, your team will be automatically alerted when KPIs deviate from
expected norms. Automatic logging of changes to your environment allows you to audit and quickly
identify actions that might have impacted reliability. Controls on change management ensure that you
can enforce the rules that deliver the reliability you need.
Failure Management
In any system of reasonable complexity, it is expected that failures will occur. Reliability requires
that your workload be aware of failures as they occur and take action to avoid impact on availability.
Workloads must be able to both withstand failures and automatically repair issues.
With AWS, you can take advantage of automation to react to monitoring data. For example, when a
particular metric crosses a threshold, you can trigger an automated action to remedy the problem. Also,
rather than trying to diagnose and fix a failed resource that is part of your production environment, you
can replace it with a new one and carry out the analysis on the failed resource out of band. Since the
cloud enables you to stand up temporary versions of a whole system at low cost, you can use automated
testing to verify full recovery processes.
REL 9: How do you back up data?
Back up data, applications, and configuration to meet your requirements for recovery time objectives
(RTO) and recovery point objectives (RPO).
REL 10: How do you use fault isolation to protect your workload?
Fault isolated boundaries limit the effect of a failure within a workload to a limited number of
components. Components outside of the boundary are unaffected by the failure. Using multiple fault
isolated boundaries, you can limit the impact on your workload.
REL 11: How do you design your workload to withstand component failures?
Workloads with a requirement for high availability and low mean time to recovery (MTTR) must be
architected for resiliency.
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REL 12: How do you test reliability?
After you have designed your workload to be resilient to the stresses of production, testing is the only
way to ensure that it will operate as designed, and deliver the resiliency you expect.
REL 13: How do you plan for disaster recovery (DR)?
Having backups and redundant workload components in place is the start of your DR strategy. RTO
and RPO are your objectives for restoration of your workload. Set these based on business needs.
Implement a strategy to meet these objectives, considering locations and function of workload
resources and data. The probability of disruption and cost of recovery are also key factors that help to
inform the business value of providing disaster recovery for a workload.
Regularly back up your data and test your backup files to ensure that you can recover from both logical
and physical errors. A key to managing failure is the frequent and automated testing of workloads to
cause failure, and then observe how they recover. Do this on a regular schedule and ensure that such
testing is also triggered after significant workload changes. Actively track KPIs, as well as the recovery
time objective (RTO) and recovery point objective (RPO), to assess a workload's resiliency (especially
under failure-testing scenarios). Tracking KPIs will help you identify and mitigate single points of failure.
The objective is to thoroughly test your workload-recovery processes so that you are confident that you
can recover all your data and continue to serve your customers, even in the face of sustained problems.
Your recovery processes should be as well exercised as your normal production processes.
Resources
Refer to the following resources to learn more about our best practices for Reliability.
Documentation
• AWS Documentation
• AWS Global Infrastructure
• AWS Auto Scaling: How Scaling Plans Work
• What Is AWS Backup?
Whitepaper
• Reliability Pillar: AWS Well-Architected
• Implementing Microservices on AWS
Performance Efficiency
The Performance Efficiency pillar includes the ability to use computing resources efficiently to meet
system requirements, and to maintain that efficiency as demand changes and technologies evolve.
The performance efficiency pillar provides an overview of design principles, best practices, and
questions. You can find prescriptive guidance on implementation in the Performance Efficiency Pillar
whitepaper.
Topics
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Design Principles
Design Principles
There are five design principles for performance efficiency in the cloud:
• Democratize advanced technologies: Make advanced technology implementation easier for your
team by delegating complex tasks to your cloud vendor. Rather than asking your IT team to learn
about hosting and running a new technology, consider consuming the technology as a service. For
example, NoSQL databases, media transcoding, and machine learning are all technologies that
require specialized expertise. In the cloud, these technologies become services that your team can
consume, allowing your team to focus on product development rather than resource provisioning and
management.
• Go global in minutes: Deploying your workload in multiple AWS Regions around the world allows you
to provide lower latency and a better experience for your customers at minimal cost.
• Use serverless architectures: Serverless architectures remove the need for you to run and maintain
physical servers for traditional compute activities. For example, serverless storage services can act as
static websites (removing the need for web servers) and event services can host code. This removes the
operational burden of managing physical servers, and can lower transactional costs because managed
services operate at cloud scale.
• Experiment more often: With virtual and automatable resources, you can quickly carry out
comparative testing using different types of instances, storage, or configurations.
• Consider mechanical sympathy: Understand how cloud services are consumed and always use the
technology approach that aligns best with your workload goals. For example, consider data access
patterns when you select database or storage approaches.
Definition
There are four best practice areas for performance efficiency in the cloud:
• Selection
• Review
• Monitoring
• Tradeoffs
Take a data-driven approach to building a high-performance architecture. Gather data on all aspects of
the architecture, from the high-level design to the selection and configuration of resource types.
Reviewing your choices on a regular basis ensures that you are taking advantage of the continually
evolving AWS Cloud. Monitoring ensures that you are aware of any deviance from expected performance.
Make trade-offs in your architecture to improve performance, such as using compression or caching, or
relaxing consistency requirements.
Best Practices
Topics
• Selection (p. 26)
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Best Practices
• Review (p. 29)
• Monitoring (p. 29)
• Tradeoffs (p. 30)
Selection
The optimal solution for a particular workload varies, and solutions often combine multiple approaches.
Well-architected workloads use multiple solutions and enable different features to improve performance.
AWS resources are available in many types and configurations, which makes it easier to find an approach
that closely matches your workload needs. You can also find options that are not easily achievable with
on-premises infrastructure. For example, a managed service such as Amazon DynamoDB provides a fully
managed NoSQL database with single-digit millisecond latency at any scale.
The following question focuses on these considerations for performance efficiency. (For a list of
performance efficiency questions and best practices, see the Appendix (p. 65).).
PERF 1: How do you select the best performing architecture?
Often, multiple approaches are required for optimal performance across a workload. Well-architected
systems use multiple solutions and features to improve performance.
Use a data-driven approach to select the patterns and implementation for your architecture and achieve
a cost effective solution. AWS Solutions Architects, AWS Reference Architectures, and AWS Partner
Network (APN) partners can help you select an architecture based on industry knowledge, but data
obtained through benchmarking or load testing will be required to optimize your architecture.
Your architecture will likely combine a number of different architectural approaches (for example, event-
driven, ETL, or pipeline). The implementation of your architecture will use the AWS services that are
specific to the optimization of your architecture's performance. In the following sections we discuss the
four main resource types to consider (compute, storage, database, and network).
Compute
Selecting compute resources that meet your requirements, performance needs, and provide great
efficiency of cost and effort will enable you to accomplish more with the same number of resources.
When evaluating compute options, be aware of your requirements for workload performance and cost
requirements and use this to make informed decisions.
In AWS, compute is available in three forms: instances, containers, and functions:
• Instances are virtualized servers, allowing you to change their capabilities with a button or an API call.
Because resource decisions in the cloud aren’t fixed, you can experiment with different server types. At
AWS, these virtual server instances come in different families and sizes, and they offer a wide variety
of capabilities, including solid-state drives (SSDs) and graphics processing units (GPUs).
• Containers are a method of operating system virtualization that allow you to run an application and
its dependencies in resource-isolated processes. AWS Fargate is serverless compute for containers or
Amazon EC2 can be used if you need control over the installation, configuration, and management
of your compute environment. You can also choose from multiple container orchestration platforms:
Amazon Elastic Container Service (ECS) or Amazon Elastic Kubernetes Service (EKS).
• Functions abstract the execution environment from the code you want to execute. For example, AWS
Lambda allows you to execute code without running an instance.
The following question focuses on these considerations for performance efficiency.
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Best Practices
PERF 2: How do you select your compute solution?
The optimal compute solution for a workload varies based on application design, usage patterns, and
configuration settings. Architectures can use different compute solutions for various components
and enable different features to improve performance. Selecting the wrong compute solution for an
architecture can lead to lower performance efficiency.
When architecting your use of compute you should take advantage of the elasticity mechanisms
available to ensure you have sufficient capacity to sustain performance as demand changes.
Storage
Cloud storage is a critical component of cloud computing, holding the information used by your
workload. Cloud storage is typically more reliable, scalable, and secure than traditional on-premises
storage systems. Select from object, block, and file storage services as well as cloud data migration
options for your workload.
In AWS, storage is available in three forms: object, block, and file:
• Object Storage provides a scalable, durable platform to make data accessible from any internet
location for user-generated content, active archive, serverless computing, Big Data storage or backup
and recovery. Amazon Simple Storage Service (Amazon S3) is an object storage service that offers
industry-leading scalability, data availability, security, and performance. Amazon S3 is designed for
99.999999999% (11 9's) of durability, and stores data for millions of applications for companies all
around the world.
• Block Storage provides highly available, consistent, low-latency block storage for each virtual host
and is analogous to direct-attached storage (DAS) or a Storage Area Network (SAN). Amazon Elastic
Block Store (Amazon EBS) is designed for workloads that require persistent storage accessible by EC2
instances that helps you tune applications with the right storage capacity, performance and cost.
• File Storage provides access to a shared file system across multiple systems. File storage solutions
like Amazon Elastic File System (EFS) are ideal for use cases, such as large content repositories,
development environments, media stores, or user home directories. Amazon FSx makes it easy and
cost effective to launch and run popular file systems so you can leverage the rich feature sets and fast
performance of widely used open source and commercially-licensed file systems.
PERF 3: How do you select your storage solution?
The optimal storage solution for a system varies based on the kind of access method (block, file, or
object), patterns of access (random or sequential), required throughput, frequency of access (online,
offline, archival), frequency of update (WORM, dynamic), and availability and durability constraints.
Well-architected systems use multiple storage solutions and enable different features to improve
performance and use resources efficiently.
When you select a storage solution, ensuring that it aligns with your access patterns will be critical to
achieving the performance you want.
Database
The cloud offers purpose-built database services that address different problems presented by your
workload. You can choose from many purpose-built database engines including relational, key-value,
document, in-memory, graph, time series, and ledger databases. By picking the best database to
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Best Practices
solve a specific problem (or a group of problems), you can break away from restrictive one-size-fits-
all monolithic databases and focus on building applications to meet the performance needs of your
customers.
In AWS you can choose from multiple purpose-built database engines including relational, key-value,
document, in-memory, graph, time series, and ledger databases. With AWS databases, you don’t need
to worry about database management tasks such as server provisioning, patching, setup, configuration,
backups, or recovery. AWS continuously monitors your clusters to keep your workloads up and running
with self-healing storage and automated scaling, so that you can focus on higher value application
development.
PERF 4: How do you select your database solution?
The optimal database solution for a system varies based on requirements for availability, consistency,
partition tolerance, latency, durability, scalability, and query capability. Many systems use different
database solutions for various subsystems and enable different features to improve performance.
Selecting the wrong database solution and features for a system can lead to lower performance
efficiency.
Your workload's database approach has a significant impact on performance efficiency. It's often an
area that is chosen according to organizational defaults rather than through a data-driven approach. As
with storage, it is critical to consider the access patterns of your workload, and also to consider if other
non-database solutions could solve the problem more efficiently (such as using graph, time series, or in-
memory storage database).
Network
Since the network is between all workload components, it can have great impacts, both positive
and negative, on workload performance and behavior. There are also workloads that are heavily
dependent on network performance such as High Performance Computing (HPC) where deep network
understanding is important to increase cluster performance. You must determine the workload
requirements for bandwidth, latency, jitter, and throughput.
On AWS, networking is virtualized and is available in a number of different types and configurations.
This makes it easier to match your networking methods with your needs. AWS offers product features
(for example, Enhanced Networking, Amazon EBS-optimized instances, Amazon S3 transfer acceleration,
and dynamic Amazon CloudFront) to optimize network traffic. AWS also offers networking features (for
example, Amazon Route 53 latency routing, Amazon VPC endpoints, AWS Direct Connect, and AWS
Global Accelerator) to reduce network distance or jitter.
PERF 5: How do you configure your networking solution?
The optimal network solution for a workload varies based on latency, throughput requirements,
jitter, and bandwidth. Physical constraints, such as user or on-premises resources, determine location
options. These constraints can be offset with edge locations or resource placement.
You must consider location when deploying your network. You can choose to place resources close to
where they will be used to reduce distance. Use networking metrics to make changes to networking
configuration as the workload evolves. By taking advantage of Regions, placement groups, and edge
services, you can significantly improve performance. Cloud based networks can be quickly re-built
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Best Practices
or modified, so evolving your network architecture over time is necessary to maintain performance
efficiency.
Review
Cloud technologies are rapidly evolving and you must ensure that workload components are using the
latest technologies and approaches to continually improve performance. You must continually evaluate
and consider changes to your workload components to ensure you are meeting its performance and cost
objectives. New technologies, such as machine learning and artificial intelligence (AI), can allow you to
reimagine customer experiences and innovate across all of your business workloads.
Take advantage of the continual innovation at AWS driven by customer need. We release new Regions,
edge locations, services, and features regularly. Any of these releases could positively improve the
performance efficiency of your architecture.
PERF 6: How do you evolve your workload to take advantage of new releases?
When architecting workloads, there are finite options that you can choose from. However, over time,
new technologies and approaches become available that could improve the performance of your
workload.
Architectures performing poorly are usually the result of a non-existent or broken performance review
process. If your architecture is performing poorly, implementing a performance review process will allow
you to apply Deming’s plan-do-check-act (PDCA) cycle to drive iterative improvement.
Monitoring
After you implement your workload, you must monitor its performance so that you can remediate any
issues before they impact your customers. Monitoring metrics should be used to raise alarms when
thresholds are breached.
Amazon CloudWatch is a monitoring and observability service that provides you with data and
actionable insights to monitor your workload, respond to system-wide performance changes, optimize
resource utilization, and get a unified view of operational health. CloudWatch collects monitoring and
operational data in the form of logs, metrics, and events from workloads that run on AWS and on-
premises servers. AWS X-Ray helps developers analyze and debug production, distributed applications.
With AWS X-Ray, you can glean insights into how your application is performing and discover root
causes and identify performance bottlenecks. You can use these insights to react quickly and keep your
workload running smoothly.
PERF 7: How do you monitor your resources to ensure they are performing?
System performance can degrade over time. Monitor system performance to identify degradation and
remediate internal or external factors, such as the operating system or application load.
Ensuring that you do not see false positives is key to an effective monitoring solution. Automated
triggers avoid human error and can reduce the time it takes to fix problems. Plan for game days, where
simulations are conducted in the production environment, to test your alarm solution and ensure that it
correctly recognizes issues.
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Resources
Tradeoffs
When you architect solutions, think about tradeoffs to ensure an optimal approach. Depending on
your situation, you could trade consistency, durability, and space for time or latency, to deliver higher
performance.
Using AWS, you can go global in minutes and deploy resources in multiple locations across the globe to
be closer to your end users. You can also dynamically add readonly replicas to information stores (such as
database systems) to reduce the load on the primary database.
PERF 8: How do you use tradeoffs to improve performance?
When architecting solutions, determining tradeoffs enables you to select an optimal approach. Often
you can improve performance by trading consistency, durability, and space for time and latency.
As you make changes to the workload, collect and evaluate metrics to determine the impact of those
changes. Measure the impacts to the system and to the end-user to understand how your trade-offs
impact your workload. Use a systematic approach, such as load testing, to explore whether the tradeoff
improves performance.
Resources
Refer to the following resources to learn more about our best practices for Performance Efficiency.
Documentation
• Amazon S3 Performance Optimization
• Amazon EBS Volume Performance
Whitepaper
• Performance Efficiency Pillar
Video
• AWS re:Invent 2019: Amazon EC2 foundations (CMP211-R2)
• AWS re:Invent 2019: Leadership session: Storage state of the union (STG201-L)
• AWS re:Invent 2019: Leadership session: AWS purpose-built databases (DAT209-L)
• AWS re:Invent 2019: Connectivity to AWS and hybrid AWS network architectures (NET317-R1)
• AWS re:Invent 2019: Powering next-gen Amazon EC2: Deep dive into the Nitro system (CMP303-R2)
• AWS re:Invent 2019: Scaling up to your first 10 million users (ARC211-R)
Cost Optimization
The Cost Optimization pillar includes the ability to run systems to deliver business value at the lowest
price point.
The cost optimization pillar provides an overview of design principles, best practices, and questions. You
can find prescriptive guidance on implementation in the Cost Optimization Pillar whitepaper.
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Design Principles
Topics
Design Principles
There are five design principles for cost optimization in the cloud:
• Implement Cloud Financial Management: To achieve financial success and accelerate business value
realization in the cloud, you need to invest in Cloud Financial Management /Cost Optimization.
Your organization needs to dedicate time and resources to build capability in this new domain of
technology and usage management. Similar to your Security or Operational Excellence capability, you
need to build capability through knowledge building, programs, resources, and processes to become a
cost-efficient organization.
• Adopt a consumption model: Pay only for the computing resources that you require and increase or
decrease usage depending on business requirements, not by using elaborate forecasting. For example,
development and test environments are typically only used for eight hours a day during the work
week. You can stop these resources when they are not in use for a potential cost savings of 75% (40
hours versus 168 hours).
• Measure overall efficiency: Measure the business output of the workload and the costs associated
with delivering it. Use this measure to know the gains you make from increasing output and reducing
costs.
• Stop spending money on undifferentiated heavy lifting: AWS does the heavy lifting of data center
operations like racking, stacking, and powering servers. It also removes the operational burden of
managing operating systems and applications with managed services. This allows you to focus on your
customers and business projects rather than on IT infrastructure.
• Analyze and attribute expenditure: The cloud makes it easier to accurately identify the usage and
cost of systems, which then allows transparent attribution of IT costs to individual workload owners.
This helps measure return on investment (ROI) and gives workload owners an opportunity to optimize
their resources and reduce costs.
Definition
There are five best practice areas for cost optimization in the cloud:
• Practice Cloud Financial Management
• Expenditure and usage awareness
• Cost-effective resources
• Manage demand and supply resources
• Optimize over time
As with the other pillars within the Well-Architected Framework, there are tradeoffs to consider, for
example, whether to optimize for speed-to-market or for cost. In some cases, it’s best to optimize
for speed—going to market quickly, shipping new features, or simply meeting a deadline—rather
than investing in up-front cost optimization. Design decisions are sometimes directed by haste rather
than data, and the temptation always exists to overcompensate “just in case” rather than spend time
benchmarking for the most cost-optimal deployment. This might lead to over-provisioned and under-
optimized deployments. However, this is a reasonable choice when you need to “lift and shift” resources
from your on-premises environment to the cloud and then optimize afterwards. Investing the right
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Best Practices
amount of effort in a cost optimization strategy up front allows you to realize the economic benefits of
the cloud more readily by ensuring a consistent adherence to best practices and avoiding unnecessary
over provisioning. The following sections provide techniques and best practices for both the initial and
ongoing implementation of Cloud Financial Management and cost optimization of your workloads.
Best Practices
Topics
• Practice Cloud Financial Management (p. 32)
• Expenditure and usage awareness (p. 32)
• Cost-effective resources (p. 33)
• Manage demand and supply resources (p. 34)
• Optimize over time (p. 35)
Practice Cloud Financial Management
With the adoption of cloud, technology teams innovate faster due to shortened approval, procurement,
and infrastructure deployment cycles. A new approach to financial management in the cloud is required
to realize business value and financial success. This approach is Cloud Financial Management, and builds
capability across your organization by implementing organizational wide knowledge building, programs,
resources, and processes.
Many organizations are composed of many different units with different priorities. The ability to align
your organization to an agreed set of financial objectives, and provide your organization the mechanisms
to meet them, will create a more efficient organization. A capable organization will innovate and build
faster, be more agile and adjust to any internal or external factors.
In AWS you can use Cost Explorer, and optionally Amazon Athena and Amazon QuickSight with the
Cost and Usage Report (CUR), to provide cost and usage awareness throughout your organization. AWS
Budgets provides proactive notifications for cost and usage. The AWS blogs provide information on new
services and features to ensure you keep up to date with new service releases.
The following question focuses on these considerations for cost optimization. (For a list of cost
optimization questions and best practices, see the Appendix (p. 70).).
COST 1: How do you implement cloud financial management?
Implementing Cloud Financial Management enables organizations to realize business value and
financial success as they optimize their cost and usage and scale on AWS.
When building a cost optimization function, use members and supplement the team with experts in CFM
and cost optimization. Existing team members will understand how the organization currently functions
and how to rapidly implement improvements. Also consider including people with supplementary or
specialist skill sets, such as analytics and project management.
When implementing cost awareness in your organization, improve or build on existing programs and
processes. It is much faster to add to what exists than to build new processes and programs. This will
result in achieving outcomes much faster.
Expenditure and usage awareness
The increased flexibility and agility that the cloud enables encourages innovation and fast-paced
development and deployment. It eliminates the manual processes and time associated with provisioning
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Best Practices
on-premises infrastructure, including identifying hardware specifications, negotiating price quotations,
managing purchase orders, scheduling shipments, and then deploying the resources. However, the ease
of use and virtually unlimited on-demand capacity requires a new way of thinking about expenditures.
Many businesses are composed of multiple systems run by various teams. The capability to attribute
resource costs to the individual organization or product owners drives efficient usage behavior and helps
reduce waste. Accurate cost attribution allows you to know which products are truly profitable, and
allows you to make more informed decisions about where to allocate budget.
In AWS, you create an account structure with AWS Organizations or AWS Control Tower, which provides
separation and assists in allocation of your costs and usage. You can also use resource tagging to apply
business and organization information to your usage and cost. Use AWS Cost Explorer for visibility into
your cost and usage, or create customized dashboards and analytics with Amazon Athena and Amazon
QuickSight. Controlling your cost and usage is done by notifications through AWS Budgets, and controls
using AWS Identity and Access Management (IAM), and Service Quotas.
The following questions focus on these considerations for cost optimization.
COST 2: How do you govern usage?
Establish policies and mechanisms to ensure that appropriate costs are incurred while objectives are
achieved. By employing a checks-and-balances approach, you can innovate without overspending.
COST 3: How do you monitor usage and cost?
Establish policies and procedures to monitor and appropriately allocate your costs. This allows you to
measure and improve the cost efficiency of this workload.
COST 4: How do you decommission resources?
Implement change control and resource management from project inception to end-of-life. This
ensures you shut down or terminate unused resources to reduce waste.
You can use cost allocation tags to categorize and track your AWS usage and costs. When you apply tags
to your AWS resources (such as EC2 instances or S3 buckets), AWS generates a cost and usage report
with your usage and your tags. You can apply tags that represent organization categories (such as cost
centers, workload names, or owners) to organize your costs across multiple services.
Ensure you use the right level of detail and granularity in cost and usage reporting and monitoring. For
high level insights and trends, use daily granularity with AWS Cost Explorer. For deeper analysis and
inspection use hourly granularity in AWS Cost Explorer, or Amazon Athena and Amazon QuickSight with
the Cost and Usage Report (CUR) at an hourly granularity.
Combining tagged resources with entity lifecycle tracking (employees, projects) makes it possible to
identify orphaned resources or projects that are no longer generating value to the organization and
should be decommissioned. You can set up billing alerts to notify you of predicted overspending.
Cost-effective resources
Using the appropriate instances and resources for your workload is key to cost savings. For example, a
reporting process might take five hours to run on a smaller server but one hour to run on a larger server
that is twice as expensive. Both servers give you the same outcome, but the smaller server incurs more
cost over time.
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Best Practices
A well-architected workload uses the most cost-effective resources, which can have a significant and
positive economic impact. You also have the opportunity to use managed services to reduce costs. For
example, rather than maintaining servers to deliver email, you can use a service that charges on a per-
message basis.
AWS offers a variety of flexible and cost-effective pricing options to acquire instances from Amazon
EC2 and other services in a way that best fits your needs. On-Demand Instances allow you to pay for
compute capacity by the hour, with no minimum commitments required. Savings Plans and Reserved
Instances offer savings of up to 75% off On-Demand pricing. With Spot Instances, you can leverage
unused Amazon EC2 capacity and offer savings of up to 90% off On-Demand pricing. Spot Instances are
appropriate where the system can tolerate using a fleet of servers where individual servers can come and
go dynamically, such as stateless web servers, batch processing, or when using HPC and big data.
Appropriate service selection can also reduce usage and costs; such as CloudFront to minimize data
transfer, or completely eliminate costs, such as utilizing Amazon Aurora on RDS to remove expensive
database licensing costs.
The following questions focus on these considerations for cost optimization.
COST 5: How do you evaluate cost when you select services?
Amazon EC2, Amazon EBS, and Amazon S3 are building-block AWS services. Managed services, such
as Amazon RDS and Amazon DynamoDB, are higher level, or application level, AWS services. By
selecting the appropriate building blocks and managed services, you can optimize this workload for
cost. For example, using managed services, you can reduce or remove much of your administrative and
operational overhead, freeing you to work on applications and business-related activities.
COST 6: How do you meet cost targets when you select resource type, size and number?
Ensure that you choose the appropriate resource size and number of resources for the task at hand.
You minimize waste by selecting the most cost effective type, size, and number.
COST 7: How do you use pricing models to reduce cost?
Use the pricing model that is most appropriate for your resources to minimize expense.
COST 8: How do you plan for data transfer charges?
Ensure that you plan and monitor data transfer charges so that you can make architectural decisions to
minimize costs. A small yet effective architectural change can drastically reduce your operational costs
over time.
By factoring in cost during service selection, and using tools such as Cost Explorer and AWS Trusted
Advisor to regularly review your AWS usage, you can actively monitor your utilization and adjust your
deployments accordingly.
Manage demand and supply resources
When you move to the cloud, you pay only for what you need. You can supply resources to match the
workload demand at the time they’re needed, this eliminates the need for costly and wasteful over
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Resources
provisioning. You can also modify the demand, using a throttle, buffer, or queue to smooth the demand
and serve it with less resources resulting in a lower cost, or process it at a later time with a batch service.
In AWS, you can automatically provision resources to match the workload demand. Auto Scaling
using demand or time-based approaches allow you to add and remove resources as needed. If you
can anticipate changes in demand, you can save more money and ensure your resources match your
workload needs. You can use Amazon API Gateway to implement throttling, or Amazon SQS to
implementing a queue in your workload. These will both allow you to modify the demand on your
workload components.
The following question focuses on these considerations for cost optimization.
COST 9: How do you manage demand, and supply resources?
For a workload that has balanced spend and performance, ensure that everything you pay for is used
and avoid significantly underutilizing instances. A skewed utilization metric in either direction has an
adverse impact on your organization, in either operational costs (degraded performance due to over-
utilization), or wasted AWS expenditures (due to over-provisioning).
When designing to modify demand and supply resources, actively think about the patterns of usage, the
time it takes to provision new resources, and the predictability of the demand pattern. When managing
demand, ensure you have a correctly sized queue or buffer, and that you are responding to workload
demand in the required amount of time.
Optimize over time
As AWS releases new services and features, it's a best practice to review your existing architectural
decisions to ensure they continue to be the most cost effective. As your requirements change, be
aggressive in decommissioning resources, entire services, and systems that you no longer require.
Implementing new features or resource types can optimize your workload incrementally, while
minimizing the effort required to implement the change. This provides continual improvements in
efficiency over time and ensures you remain on the most updated technology to reduce operating
costs. You can also replace or add new components to the workload with new services. This can provide
significant increases in efficiency, so it's essential to regularly review your workload, and implement new
services and features.
The following question focuses on these considerations for cost optimization.
COST 10: How do you evaluate new services?
decisions to ensure they continue to be the most cost effective.
When regularly reviewing your deployments, assess how newer services can help save you money. For
example, Amazon Aurora on RDS can reduce costs for relational databases. Using serverless such as
Lambda can remove the need to operate and manage instances to run code.
Resources
Refer to the following resources to learn more about our best practices for Cost Optimization.
Documentation
• AWS Documentation
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Resources
Whitepaper
• Cost Optimization Pillar
36

The Review Process
The review of architectures needs to be done in a consistent manner, with a blamefree approach that
encourages diving deep. It should be a light weight process (hours not days) that is a conversation and
not an audit. The purpose of reviewing an architecture is to identify any critical issues that might need
addressing or areas that could be improved. The outcome of the review is a set of actions that should
improve the experience of a customer using the workload.
As discussed in the “On Architecture” section, you will want each team member to take responsibility for
the quality of its architecture. We recommend that the team members who build an architecture use the
Well-Architected Framework to continually review their architecture, rather than holding a formal review
meeting. A continuous approach allows your team members to update answers as the architecture
evolves, and improve the architecture as you deliver features.
The AWS Well-Architected Framework is aligned to the way that AWS reviews systems and services
internally. It is premised on a set of design principles that influences architectural approach, and
questions that ensure that people don’t neglect areas that often featured in Root Cause Analysis (RCA).
Whenever there is a significant issue with an internal system, AWS service, or customer, we look at the
RCA to see if we could improve the review processes we use.
Reviews should be applied at key milestones in the product lifecycle, early on in the design phase to
avoid one-way doors that are difficult to change, and then before the go-live date. After you go into
production, your workload will continue to evolve as you add new features and change technology
implementations. The architecture of a workload changes over time. You will need to follow good
hygiene practices to stop its architectural characteristics from degrading as you evolve it. As you
make significant architecture changes you should follow a set of hygiene processes including a Well-
Architected review.
If you want to use the review as a one-time snapshot or independent measurement, you will want to
ensure that you have all the right people in the conversation. Often, we find that reviews are the first
time that a team truly understands what they have implemented. An approach that works well when
reviewing another team's workload is to have a series of informal conversations about their architecture
where you can glean the answers to most questions. You can then follow up with one or two meetings
where you can gain clarity or dive deep on areas of ambiguity or perceived risk.
Here are some suggested items to facilitate your meetings:
• A meeting room with whiteboards
• Print outs of any diagrams or design notes
• Action list of questions that require out-of-band research to answer (for example, “did we enable
encryption or not?”)
After you have done a review, you should have a list of issues that you can prioritize based on your
business context. You will also want to take into account the impact of those issues on the day-to-day
work of your team. If you address these issues early, you could free up time to work on creating business
value rather than solving recurring problems. As you address issues, you can update your review to see
how the architecture is improving.
While the value of a review is clear after you have done one, you may find that a new team might be
resistant at first. Here are some objections that can be handled through educating the team on the
benefits of a review:
• “We are too busy!” (Often said when the team is getting ready for a big launch.)
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• If you are getting ready for a big launch you will want it to go smoothly. The review will allow you to
understand any problems you might have missed.
• We recommend that you carry out reviews early in the product lifecycle to uncover risks and develop
a mitigation plan aligned with the feature delivery roadmap.
• “We don’t have time to do anything with the results!” (Often said when there is an immovable event,
such as the Super Bowl, that they are targeting.)
• These events can’t be moved. Do you really want to go into it without knowing the risks in your
architecture? Even if you don’t address all of these issues you can still have playbooks for handling
them if they materialize.
• “We don’t want others to know the secrets of our solution implementation!”
• If you point the team at the questions in the Well-Architected Framework, they will see that none of
the questions reveal any commercial or technical proprietary information.
As you carry out multiple reviews with teams in your organization, you might identify thematic issues.
For example, you might see that a group of teams has clusters of issues in a particular pillar or topic.
You will want to look at all your reviews in a holistic manner, and identify any mechanisms, training, or
principal engineering talks that could help address those thematic issues.
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Conclusion
The AWS Well-Architected Framework provides architectural best practices across the five pillars
for designing and operating reliable, secure, efficient, and cost-effective systems in the cloud. The
Framework provides a set of questions that allows you to review an existing or proposed architecture. It
also provides a set of AWS best practices for each pillar. Using the Framework in your architecture will
help you produce stable and efficient systems, which allow you to focus on your functional requirements.
39

Contributors
The following individuals and organizations contributed to this document:
• Rodney Lester: Senior Manager Well-Architected, Amazon Web Services
• Brian Carlson: Operations Lead Well-Architected, Amazon Web Services
• Ben Potter: Security Lead Well-Architected, Amazon Web Services
• Eric Pullen: Performance Lead Well-Architected, Amazon Web Services
• Seth Eliot: Reliability Lead Well-Architected, Amazon Web Services
• Nathan Besh: Cost Lead Well-Architected, Amazon Web Services
• Jon Steele: Sr. Technical Account Manager, Amazon Web Services
• Ryan King: Technical Program Manager, Amazon Web Services
• Erin Rifkin: Senior Product Manager, Amazon Web Services
• Max Ramsay: Principal Security Solutions Architect, Amazon Web Services
• Scott Paddock: Security Solutions Architect, Amazon Web Services
• Callum Hughes: Solutions Architect, Amazon Web Services
• Philip Fitzsimons, Sr Manager Well-Architected, Amazon Web Services
40

Further Reading
AWS Architecture Center
AWS Cloud Compliance
AWS Well-Architected Partner program
AWS Well-Architected Tool
AWS Well-Architected homepage
Cost Optimization Pillar whitepaper
Operational Excellence Pillar whitepaper
Performance Eﬃciency Pillar whitepaper
Reliability Pillar whitepaper
Security Pillar whitepaper
The Amazon Builders' Library
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Document Revisions
To be notified about updates to this whitepaper, subscribe to the RSS feed.
update-history-change update-history-description update-history-date
Minor update (p. 42) Fixed numerous links. March 10, 2021
Minor update (p. 42) Minor editorial changes
throughout.
July 15, 2020
Updates for new
Framework (p. 42)
Review and rewrite of most
questions and answers.
July 8, 2020
Whitepaper updated (p. 42) Addition of AWS Well-
Architected Tool, links to AWS
Well-Architected Labs, and
AWS Well-Architected Partners,
minor fixes to enable multiple
language version of framework.
July 1, 2019
Whitepaper updated (p. 42) Review and rewrite of most
questions and answers, to ensure
questions focus on one topic
at a time. This caused some
previous questions to be split
into multiple questions. Added
common terms to definitions
(workload, component etc).
Changed presentation of
question in main body to include
descriptive text.
November 1, 2018
Whitepaper updated (p. 42) Updates to simplify question
text, standardize answers, and
improve readability.
June 1, 2018
Whitepaper updated (p. 42) Operational Excellence moved to
front of pillars and rewritten so
it frames other pillars. Refreshed
other pillars to reflect evolution
of AWS.
November 1, 2017
Whitepaper updated (p. 42) Updated the Framework to
include operational excellence
pillar, and revised and updated
the other pillars to reduce
duplication and incorporate
learnings from carrying out
reviews with thousands of
customers.
November 1, 2016
Minor updates (p. 42) Updated the Appendix with
current Amazon CloudWatch
Logs information.
November 1, 2015
42

Initial publication (p. 42) AWS Well-Architected
Framework published.
October 1, 2015
43

Appendix: Questions and Best
Practices
Topics
• Operational Excellence (p. 44)
• Reliability (p. 58)
• Performance Efficiency (p. 65)
• Cost Optimization (p. 70)
Topics
• Organization (p. 44)
• Prepare (p. 46)
• Operate (p. 49)
• Evolve (p. 51)
Organization
OPS 1 How do you determine what your priorities are?
Everyone needs to understand their part in enabling business success. Have shared goals in order to set
priorities for resources. This will maximize the benefits of your efforts.
Best Practices:
• Evaluate external customer needs: Involve key stakeholders, including business, development, and
operations teams, to determine where to focus efforts on external customer needs. This will ensure
that you have a thorough understanding of the operations support that is required to achieve your
desired business outcomes.
• Evaluate internal customer needs: Involve key stakeholders, including business, development, and
operations teams, when determining where to focus efforts on internal customer needs. This will
ensure that you have a thorough understanding of the operations support that is required to achieve
business outcomes.
• Evaluate governance requirements: Ensure that you are aware of guidelines or obligations defined
by your organization that may mandate or emphasize specific focus. Evaluate internal factors, such
as organization policy, standards, and requirements. Validate that you have mechanisms to identify
changes to governance. If no governance requirements are identified, ensure that you have applied
due diligence to this determination.
• Evaluate compliance requirements: Evaluate external factors, such as regulatory compliance
requirements and industry standards, to ensure that you are aware of guidelines or obligations that
44

Organization
may mandate or emphasize specific focus. If no compliance requirements are identified, ensure that
you apply due diligence to this determination.
• Evaluate threat landscape: Evaluate threats to the business (for example, competition, business risk
and liabilities, operational risks, and information security threats) and maintain current information in
a risk registry. Include the impact of risks when determining where to focus efforts.
• Evaluate tradeoffs: Evaluate the impact of tradeoffs between competing interests or alternative
approaches, to help make informed decisions when determining where to focus efforts or choosing
a course of action. For example, accelerating speed to market for new features may be emphasized
over cost optimization, or you may choose a relational database for non-relational data to simplify
the effort to migrate a system, rather than migrating to a database optimized for your data type and
updating your application.
• Manage benefits and risks: Manage benefits and risks to make informed decisions when determining
where to focus efforts. For example, it may be beneficial to deploy a workload with unresolved issues
so that significant new features can be made available to customers. It may be possible to mitigate
associated risks, or it may become unacceptable to allow a risk to remain, in which case you will take
action to address the risk.
OPS 2 How do you structure your organization to support your business outcomes?
make decisions will help focus efforts and maximize the benefits from your teams.
Best Practices:
• Resources have identified owners: Understand who has ownership of each application, workload,
platform, and infrastructure component, what business value is provided by that component, and why
that ownership exists. Understanding the business value of these individual components and how they
support business outcomes informs the processes and procedures applied against them.
• Processes and procedures have identified owners: Understand who has ownership of the definition of
individual processes and procedures, why those specific process and procedures are used, and why that
ownership exists. Understanding the reasons that specific processes and procedures are used enables
identification of improvement opportunities.
• Operations activities have identified owners responsible for their performance: Understand who
has responsibility to perform specific activities on defined workloads and why that responsibility exists.
Understanding who has responsibility to perform activities informs who will conduct the activity,
validate the result, and provide feedback to the owner of the activity.
• Team members know what they are responsible for: Understanding the responsibilities of your role
and how you contribute to business outcomes informs the prioritization of your tasks and why your
role is important. This enables team members to recognize needs and respond appropriately.
• Mechanisms exist to identify responsibility and ownership: Where no individual or team is identified,
there are defined escalation paths to someone with the authority to assign ownership or plan for that
need to be addressed.
• Mechanisms exist to request additions, changes, and exceptions: You are able to make requests to
owners of processes, procedures, and resources. Make informed decisions to approve requests where
viable and determined to be appropriate after an evaluation of benefits and risks.
• Responsibilities between teams are predefined or negotiated: There are defined or negotiated
agreements between teams describing how they work with and support each other (for example,
response times, service level objectives, or service level agreements). Understanding the impact of the
teams’ work on business outcomes, and the outcomes of other teams and organizations, informs the
prioritization of their tasks and enables them to respond appropriately.
45

Prepare
OPS 3 How does your organizational culture support your business outcomes?
supporting your business outcome.
Best Practices:
• Executive Sponsorship: Senior leadership clearly sets expectations for the organization and evaluates
success. Senior leadership is the sponsor, advocate, and driver for the adoption of best practices and
evolution of the organization
• Team members are empowered to take action when outcomes are at risk: The workload owner
has defined guidance and scope empowering team members to respond when outcomes are at risk.
Escalation mechanisms are used to get direction when events are outside of the defined scope.
• Escalation is encouraged: Team members have mechanisms and are encouraged to escalate concerns
to decision makers and stakeholders if they believe outcomes are at risk. Escalation should be
performed early and often so that risks can be identified, and prevented from causing incidents.
• Communications are timely, clear, and actionable: Mechanisms exist and are used to provide timely
notice to team members of known risks and planned events. Necessary context, details, and time
(when possible) are provided to support determining if action is necessary, what action is required,
and to take action in a timely manner. For example, providing notice of software vulnerabilities so that
patching can be expedited, or providing notice of planned sales promotions so that a change freeze
can be implemented to avoid the risk of service disruption.
• Experimentation is encouraged: Experimentation accelerates learning and keeps team members
interested and engaged. An undesired result is a successful experiment that has identified a path that
will not lead to success. Team members are not punished for successful experiments with undesired
results. Experimentation is required for innovation to happen and turn ideas into outcomes.
• Team members are enabled and encouraged to maintain and grow their skill sets: Teams must
grow their skill sets to adopt new technologies, and to support changes in demand and responsibilities
in support of your workloads. Growth of skills in new technologies is frequently a source of team
member satisfaction and supports innovation. Support your team members’ pursuit and maintenance
of industry certifications that validate and acknowledge their growing skills. Cross train to promote
knowledge transfer and reduce the risk of significant impact when you lose skilled and experienced
team members with institutional knowledge. Provide dedicated structured time for learning.
• Resource teams appropriately: Maintain team member capacity, and provide tools and resources,
to support your workload needs. Overtasking team members increases the risk of incidents resulting
from human error. Investments in tools and resources (for example, providing automation for
frequently executed activities) can scale the effectiveness of your team, enabling them to support
additional activities.
• Diverse opinions are encouraged and sought within and across teams: Leverage cross-organizational
diversity to seek multiple unique perspectives. Use this perspective to increase innovation, challenge
your assumptions, and reduce the risk of confirmation bias. Grow inclusion, diversity, and accessibility
within your teams to gain beneficial perspectives.
Prepare
OPS 4 How do you design your workload so that you can understand its state?
Design your workload so that it provides the information necessary across all components (for
example, metrics, logs, and traces) for you to understand its internal state. This enables you to provide
effective responses when appropriate.
46

Prepare
Best Practices:
• Implement application telemetry: Instrument your application code to emit information about
its internal state, status, and achievement of business outcomes. For example, queue depth, error
messages, and response times. Use this information to determine when a response is required.
• Implement and configure workload telemetry: Design and configure your workload to emit
information about its internal state and current status. For example, API call volume, HTTP status
codes, and scaling events. Use this information to help determine when a response is required.
• Implement user activity telemetry: Instrument your application code to emit information about
user activity, for example, click streams, or started, abandoned, and completed transactions. Use this
information to help understand how the application is used, patterns of usage, and to determine when
a response is required.
• Implement dependency telemetry: Design and configure your workload to emit information about
the status (for example, reachability or response time) of resources it depends on. Examples of external
dependencies can include, external databases, DNS, and network connectivity. Use this information to
determine when a response is required.
• Implement transaction traceability: Implement your application code and configure your workload
components to emit information about the flow of transactions across the workload. Use this
information to determine when a response is required and to assist you in identifying the factors
contributing to an issue.
OPS 5 How do you reduce defects, ease remediation, and improve flow into production?
Adopt approaches that improve flow of changes into production, that enable refactoring, fast feedback
on quality, and bug fixing. These accelerate beneficial changes entering production, limit issues
activities.
Best Practices:
• Use version control: Use version control to enable tracking of changes and releases.
• Test and validate changes: Test and validate changes to help limit and detect errors. Automate testing
to reduce errors caused by manual processes, and reduce the level of effort to test.
• Use configuration management systems: Use configuration management systems to make and track
configuration changes. These systems reduce errors caused by manual processes and reduce the level
of effort to deploy changes.
• Use build and deployment management systems: Use build and deployment management systems.
These systems reduce errors caused by manual processes and reduce the level of effort to deploy
changes.
• Perform patch management: Perform patch management to gain features, address issues, and
remain compliant with governance. Automate patch management to reduce errors caused by manual
processes, and reduce the level of effort to patch.
• Share design standards: Share best practices across teams to increase awareness and maximize the
benefits of development efforts.
• Implement practices to improve code quality: Implement practices to improve code quality and
minimize defects. For example, test-driven development, code reviews, and standards adoption.
• Use multiple environments: Use multiple environments to experiment, develop, and test your
workload. Use increasing levels of controls as environments approach production to gain confidence
your workload will operate as intended when deployed.
• Make frequent, small, reversible changes: Frequent, small, and reversible changes reduce the scope
and impact of a change. This eases troubleshooting, enables faster remediation, and provides the
option to roll back a change.
47

Prepare
• Fully automate integration and deployment: Automate build, deployment, and testing of the
workload. This reduces errors caused by manual processes and reduces the effort to deploy changes.
OPS 6 How do you mitigate deployment risks?
Adopt approaches that provide fast feedback on quality and enable rapid recovery from changes that
do not have desired outcomes. Using these practices mitigates the impact of issues introduced through
the deployment of changes.
Best Practices:
• Plan for unsuccessful changes: Plan to revert to a known good state, or remediate in the production
environment if a change does not have the desired outcome. This preparation reduces recovery time
through faster responses.
• Test and validate changes: Test changes and validate the results at all lifecycle stages to confirm new
features and minimize the risk and impact of failed deployments.
• Use deployment management systems: Use deployment management systems to track and
implement change. This reduces errors cause by manual processes and reduces the effort to deploy
changes.
• Test using limited deployments: Test with limited deployments alongside existing systems to confirm
desired outcomes prior to full scale deployment. For example, use deployment canary testing or one-
box deployments.
• Deploy using parallel environments: Implement changes onto parallel environments, and then
transition over to the new environment. Maintain the prior environment until there is confirmation
of successful deployment. Doing so minimizes recovery time by enabling rollback to the previous
environment.
• Deploy frequent, small, reversible changes: Use frequent, small, and reversible changes to reduce the
scope of a change. This results in easier troubleshooting and faster remediation with the option to roll
back a change.
• Fully automate integration and deployment: Automate build, deployment, and testing of the
workload. This reduces errors cause by manual processes and reduces the effort to deploy changes.
• Automate testing and rollback: Automate testing of deployed environments to confirm desired
outcomes. Automate rollback to previous known good state when outcomes are not achieved to
minimize recovery time and reduce errors caused by manual processes.
OPS 7 How do you know that you are ready to support a workload?
Evaluate the operational readiness of your workload, processes and procedures, and personnel to
understand the operational risks related to your workload.
Best Practices:
• Ensure personnel capability: Have a mechanism to validate that you have the appropriate number
of trained personnel to provide support for operational needs. Train personnel and adjust personnel
capacity as necessary to maintain effective support.
• Ensure consistent review of operational readiness: Ensure you have a consistent review of your
readiness to operate a workload. Reviews must include, at a minimum, the operational readiness of the
teams and the workload, and security requirements. Implement review activities in code and trigger
automated review in response to events where appropriate, to ensure consistency, speed of execution,
and reduce errors caused by manual processes.
48

Operate
• Use runbooks to perform procedures: Runbooks are documented procedures to achieve specific
outcomes. Enable consistent and prompt responses to well-understood events by documenting
procedures in runbooks. Implement runbooks as code and trigger the execution of runbooks in
response to events where appropriate, to ensure consistency, speed responses, and reduce errors
caused by manual processes.
• Use playbooks to investigate issues: Enable consistent and prompt responses to issues that are not
well understood, by documenting the investigation process in playbooks. Playbooks are the predefined
steps performed to identify the factors contributing to a failure scenario. The results from any process
step are used to determine the next steps to take until the issue is identified or escalated.
• Make informed decisions to deploy systems and changes: Evaluate the capabilities of the team to
support the workload and the workload's compliance with governance. Evaluate these against the
benefits of deployment when determining whether to transition a system or change into production.
Understand the benefits and risks to make informed decisions.
Operate
OPS 8 How do you understand the health of your workload?
Define, capture, and analyze workload metrics to gain visibility to workload events so that you can take
appropriate action.
Best Practices:
• Identify key performance indicators: Identify key performance indicators (KPIs) based on desired
business outcomes (for example, order rate, customer retention rate, and profit versus operating
expense) and customer outcomes (for example, customer satisfaction). Evaluate KPIs to determine
workload success.
• Define workload metrics: Define workload metrics to measure the achievement of KPIs (for example,
abandoned shopping carts, orders placed, cost, price, and allocated workload expense). Define
workload metrics to measure the health of the workload (for example, interface response time,
error rate, requests made, requests completed, and utilization). Evaluate metrics to determine if the
workload is achieving desired outcomes, and to understand the health of the workload.
• Collect and analyze workload metrics: Perform regular proactive reviews of metrics to identify trends
and determine where appropriate responses are needed.
• Establish workload metrics baselines: Establish baselines for metrics to provide expected values
as the basis for comparison and identification of under and over performing components. Identify
thresholds for improvement, investigation, and intervention.
• Learn expected patterns of activity for workload: Establish patterns of workload activity to identify
anomalous behavior so that you can respond appropriately if required.
• Alert when workload outcomes are at risk: Raise an alert when workload outcomes are at risk so that
you can respond appropriately if necessary.
• Alert when workload anomalies are detected: Raise an alert when workload anomalies are detected
so that you can respond appropriately if necessary.
• Validate the achievement of outcomes and the effectiveness of KPIs and metrics : Create a business-
level view of your workload operations to help you determine if you are satisfying needs and to
identify areas that need improvement to reach business goals. Validate the effectiveness of KPIs and
metrics and revise them if necessary.
49

Operate
OPS 9 How do you understand the health of your operations?
Define, capture, and analyze operations metrics to gain visibility to operations events so that you can
take appropriate action.
Best Practices:
• Identify key performance indicators: Identify key performance indicators (KPIs) based on desired
business (for example, new features delivered) and customer outcomes (for example, customer
support cases). Evaluate KPIs to determine operations success.
• Define operations metrics: Define operations metrics to measure the achievement of KPIs (for
example, successful deployments, and failed deployments). Define operations metrics to measure the
health of operations activities (for example, mean time to detect an incident (MTTD), and mean time
to recovery (MTTR) from an incident). Evaluate metrics to determine if operations are achieving desired
outcomes, and to understand the health of your operations activities.
• Collect and analyze operations metrics: Perform regular, proactive reviews of metrics to identify
trends and determine where appropriate responses are needed.
• Establish operations metrics baselines: Establish baselines for metrics to provide expected values as
the basis for comparison and identification of under and over performing operations activities.
• Learn the expected patterns of activity for operations: Establish patterns of operations activities to
identify anomalous activity so that you can respond appropriately if necessary.
• Alert when operations outcomes are at risk: Raise an alert when operations outcomes are at risk so
that you can respond appropriately if necessary.
• Alert when operations anomalies are detected: Raise an alert when operations anomalies are
detected so that you can respond appropriately if necessary.
• Validate the achievement of outcomes and the effectiveness of KPIs and metrics : Create a business-
level view of your operations activities to help you determine if you are satisfying needs and to
identify areas that need improvement to reach business goals. Validate the effectiveness of KPIs and
metrics and revise them if necessary.
OPS 10 How do you manage workload and operations events?
Prepare and validate procedures for responding to events to minimize their disruption to your
workload.
Best Practices:
• Use processes for event, incident, and problem management: Have processes to address observed
events, events that require intervention (incidents), and events that require intervention and either
recur or cannot currently be resolved (problems). Use these processes to mitigate the impact of these
events on the business and your customers by ensuring timely and appropriate responses.
• Have a process per alert: Have a well-defined response (runbook or playbook), with a specifically
identified owner, for any event for which you raise an alert. This ensures effective and prompt
responses to operations events and prevents actionable events from being obscured by less valuable
notifications.
• Prioritize operational events based on business impact: Ensure that when multiple events require
intervention, those that are most significant to the business are addressed first. For example, impacts
can include loss of life or injury, financial loss, or damage to reputation or trust.
• Define escalation paths: Define escalation paths in your runbooks and playbooks, including what
triggers escalation, and procedures for escalation. Specifically identify owners for each action to
ensure effective and prompt responses to operations events.
50

Evolve
• Enable push notifications: Communicate directly with your users (for example, with email or SMS)
when the services they use are impacted, and again when the services return to normal operating
conditions, to enable users to take appropriate action.
• Communicate status through dashboards: Provide dashboards tailored to their target audiences (for
example, internal technical teams, leadership, and customers) to communicate the current operating
status of the business and provide metrics of interest.
• Automate responses to events: Automate responses to events to reduce errors caused by manual
processes, and to ensure prompt and consistent responses.
Evolve
OPS 11 How do you evolve operations?
Dedicate time and resources for continuous incremental improvement to evolve the effectiveness and
efficiency of your operations.
Best Practices:
• Have a process for continuous improvement: Regularly evaluate and prioritize opportunities for
improvement to focus efforts where they can provide the greatest benefits.
• Perform post-incident analysis: Review customer-impacting events, and identify the contributing
factors and preventative actions. Use this information to develop mitigations to limit or prevent
recurrence. Develop procedures for prompt and effective responses. Communicate contributing factors
and corrective actions as appropriate, tailored to target audiences.
• Implement feedback loops: Include feedback loops in your procedures and workloads to help you
identify issues and areas that need improvement.
• Perform Knowledge Management: Mechanisms exist for your team members to discover the
information that they are looking for in a timely manner, access it, and identify that it’s current and
complete. Mechanisms are present to identify needed content, content in need of refresh, and content
that should be archived so that it’s no longer referenced.
• Define drivers for improvement: Identify drivers for improvement to help you evaluate and prioritize
opportunities.
• Validate insights: Review your analysis results and responses with cross-functional teams and business
owners. Use these reviews to establish common understanding, identify additional impacts, and
determine courses of action. Adjust responses as appropriate.
• Perform operations metrics reviews: Regularly perform retrospective analysis of operations metrics
with cross-team participants from different areas of the business. Use these reviews to identify
opportunities for improvement, potential courses of action, and to share lessons learned.
• Document and share lessons learned: Document and share lessons learned from the execution of
operations activities so that you can use them internally and across teams.
• Allocate time to make improvements: Dedicate time and resources within your processes to make
continuous incremental improvements possible.
Security
Topics
• Security Foundations (p. 52)
• Identity and Access Management (p. 53)
• Detection (p. 54)
51

Security
• Infrastructure Protection (p. 55)
• Data Protection (p. 56)
• Incident Response (p. 57)
Security Foundations
SEC 1 How do you securely operate your workload?
To operate your workload securely, you must apply overarching best practices to every area of
security. Take requirements and processes that you have defined in operational excellence at an
organizational and workload level, and apply them to all areas. Staying up to date with AWS and
industry recommendations and threat intelligence helps you evolve your threat model and control
objectives. Automating security processes, testing, and validation allow you to scale your security
operations.
Best Practices:
• Separate workloads using accounts: Organize workloads in separate accounts and group accounts
based on function or a common set of controls rather -than mirroring your company’s reporting
structure. Start with security and infrastructure in mind to enable your organization to set common
guardrails as your workloads grow.
• Secure AWS account: Secure access to your accounts, for example by enabling MFA and restrict use of
the root user, and configure account contacts.
• Identify and validate control objectives: Based on your compliance requirements and risks identified
from your threat model, derive and validate the control objectives and controls that you need to
apply to your workload. Ongoing validation of control objectives and controls help you measure the
effectiveness of risk mitigation.
• Keep up to date with security threats: Recognize attack vectors by staying up to date with the latest
security threats to help you define and implement appropriate controls.
• Keep up to date with security recommendations: Stay up to date with both AWS and industry
security recommendations to evolve the security posture of your workload.
• Automate testing and validation of security controls in pipelines: Establish secure baselines and
templates for security mechanisms that are tested and validated as part of your build, pipelines,
and processes. Use tools and automation to test and validate all security controls continuously.
For example, scan items such as machine images and infrastructure as code templates for security
vulnerabilities, irregularities, and drift from an established baseline at each stage.
• Identify and prioritize risks using a threat model: Use a threat model to identify and maintain an up-
to-date register of potential threats. Prioritize your threats and adapt your security controls to prevent,
detect, and respond. Revisit and maintain this in the context of the evolving security landscape.
• Evaluate and implement new security services and features regularly: AWS and APN Partners
constantly release new features and services that allow you to evolve the security posture of your
workload.
52

SEC 2 How do you manage authentication for people and machines?
There are two types of identities you need to manage when approaching operating secure AWS
workloads. Understanding the type of identity you need to manage and grant access helps you ensure
the right identities have access to the right resources under the right conditions.
Human Identities: Your administrators, developers, operators, and end users require an identity to
access your AWS environments and applications. These are members of your organization, or external
users with whom you collaborate, and who interact with your AWS resources via a web browser, client
application, or interactive command-line tools.
Machine Identities: Your service applications, operational tools, and workloads require an identity to
make requests to AWS services for example, to read data. These identities include machines running
in your AWS environment such as Amazon EC2 instances or AWS Lambda functions. You may also
manage machine identities for external parties who need access. Additionally, you may also have
machines outside of AWS that need access to your AWS environment.
Best Practices:
• Use strong sign-in mechanisms: Enforce minimum password length, and educate users to avoid
common or re-used passwords. Enforce multi-factor authentication (MFA) with software or hardware
mechanisms to provide an additional layer.
• Use temporary credentials: Require identities to dynamically acquire temporary credentials. For
workforce identities, use AWS Single Sign-On, or federation with IAM roles to access AWS accounts. For
machine identities, require the use of IAM roles instead of long term access keys.
• Store and use secrets securely: For workforce and machine identities that require secrets such as
passwords to third party applications, store them with automatic rotation using the latest industry
standards in a specialized service.
• Rely on a centralized identity provider: For workforce identities, rely on an identity provider that
enables you to manage identities in a centralized place. This enables you to create, manage, and
revoke access from a single location making it easier to manage access. This reduces the requirement
for multiple credentials and provides an opportunity to integrate with HR processes.
• Audit and rotate credentials periodically: When you cannot rely on temporary credentials and require
long term credentials, audit credentials to ensure that the deﬁned controls (for example, MFA) are
enforced, rotated regularly, and have appropriate access level.
• Leverage user groups and attributes: Place users with common security requirements in groups
deﬁned by your identity provider, and put mechanisms in place to ensure that user attributes that may
be used for access control (e.g., department or location) are correct and updated. Use these groups and
attributes, rather than individual users, to control access. This allows you to manage access centrally by
changing a user’s group membership or attributes once, rather than updating many individual policies
when a user’s access needs change.
SEC 3 How do you manage permissions for people and machines?
Manage permissions to control access to people and machine identities that require access to AWS and
your workload. Permissions control who can access what, and under what conditions.
Best Practices:
53

Detection
• Define access requirements: Each component or resource of your workload needs to be accessed by
administrators, end users, or other components. Have a clear definition of who or what should have
access to each component, choose the appropriate identity type and method of authentication and
authorization.
• Grant least privilege access: Grant only the access that identities require by allowing access to specific
actions on specific AWS resources under specific conditions. Rely on groups and identity attributes
to dynamically set permissions at scale, rather than defining permissions for individual users. For
example, you can allow a group of developers access to manage only resources for their project. This
way, when a developer is removed from the group, access for the developer is revoked everywhere that
group was used for access control, without requiring any changes to the access policies.
• Establish emergency access process: A process that allows emergency access to your workload in
the unlikely event of an automated process or pipeline issue. This will help you rely on least privilege
access, but ensure users can obtain the right level of access when they require it. For example,
establish a process for administrators to verify and approve their request.
• Reduce permissions continuously: As teams and workloads determine what access they need, remove
permissions they no longer use and establish review processes to achieve least privilege permissions.
Continuously monitor and reduce unused identities and permissions.
• Define permission guardrails for your organization: Establish common controls that restrict access
to all identities in your organization. For example, you can restrict access to specific AWS Regions, or
prevent your operators from deleting common resources, such as an IAM role used for your central
security team.
• Manage access based on life cycle: Integrate access controls with operator and application life cycle
and your centralized federation provider. For example, remove a user’s access when they leave the
organization or change roles.
• Analyze public and cross account access: Continuously monitor findings that highlight public and
cross account access. Reduce public access and cross account access to only resources that require this
type of access.
• Share resources securely: Govern the consumption of shared resources across accounts or within your
AWS Organization. Monitor shared resources and review shared resource access.
Detection
SEC 4 How do you detect and investigate security events?
Capture and analyze events from logs and metrics to gain visibility. Take action on security events and
potential threats to help secure your workload.
Best Practices:
• Configure service and application logging: Configure logging throughout the workload, including
application logs, resource logs, and AWS service logs. For example, ensure that AWS CloudTrail,
Amazon CloudWatch Logs, Amazon GuardDuty and AWS Security Hub are enabled for all accounts
within your organization.
• Analyze logs, findings, and metrics centrally: All logs, metrics, and telemetry should be collected
centrally, and automatically analyzed to detect anomalies and indicators of unauthorized activity.
A dashboard can provide you easy to access insight into real-time health. For example, ensure that
Amazon GuardDuty and Security Hub logs are sent to a central location for alerting and analysis.
• Automate response to events: Using automation to investigate and remediate events reduces human
effort and error, and enables you to scale investigation capabilities. Regular reviews will help you tune
automation tools, and continuously iterate. For example, automate responses to Amazon GuardDuty
events by automating the first investigation step, then iterate to gradually remove human effort.
54

• Implement actionable security events: Create alerts that are sent to and can be actioned by your
team. Ensure that alerts include relevant information for the team to take action. For example, ensure
that Amazon GuardDuty and AWS Security Hub alerts are sent to the team to action, or sent to
response automation tooling with the team remaining informed by messaging from the automation
framework.
SEC 5 How do you protect your network resources?
Any workload that has some form of network connectivity, whether it’s the internet or a private
network, requires multiple layers of defense to help protect from external and internal network-based
threats.
Best Practices:
• Create network layers: Group components that share reachability requirements into layers. For
example, a database cluster in a VPC with no need for internet access should be placed in subnets with
no route to or from the internet. In a serverless workload operating without a VPC, similar layering and
segmentation with microservices can achieve the same goal.
• Control traffic at all layers: Apply controls with a defense in depth approach for both inbound and
outbound traffic. For example, for Amazon Virtual Private Cloud (VPC) this includes security groups,
Network ACLs, and subnets. For AWS Lambda, consider running in your private VPC with VPC-based
controls.
• Automate network protection: Automate protection mechanisms to provide a self-defending network
based on threat intelligence and anomaly detection. For example, intrusion detection and prevention
tools that can pro-actively adapt to current threats and reduce their impact.
• Implement inspection and protection: Inspect and filter your traffic at each layer. For example,
use a web application firewall to help protect against inadvertent access at the application network
layer. For Lambda functions, third-party tools can add application-layer firewalling to your runtime
environment.
SEC 6 How do you protect your compute resources?
Compute resources in your workload require multiple layers of defense to help protect from external
and internal threats. Compute resources include EC2 instances, containers, AWS Lambda functions,
database services, IoT devices, and more.
Best Practices:
• Perform vulnerability management: Frequently scan and patch for vulnerabilities in your code,
dependencies, and in your infrastructure to help protect against new threats.
• Reduce attack surface: Reduce your attack surface by hardening operating systems, minimizing
components, libraries, and externally consumable services in use.
• Implement managed services: Implement services that manage resources, such as Amazon RDS,
AWS Lambda, and Amazon ECS, to reduce your security maintenance tasks as part of the shared
responsibility model.
• Automate compute protection: Automate your protective compute mechanisms including
vulnerability management, reduction in attack surface, and management of resources.
55

Data Protection
• Enable people to perform actions at a distance: Removing the ability for interactive access reduces
the risk of human error, and the potential for manual configuration or management. For example, use
a change management workflow to deploy EC2 instances using infrastructure as code, then manage
EC2 instances using tools instead of allowing direct access or a bastion host.
• Validate software integrity: Implement mechanisms (for example, code signing) to validate that
the software, code, and libraries used in the workload are from trusted sources and have not been
tampered with.
Data Protection
SEC 7 How do you classify your data?
Classification provides a way to categorize data, based on criticality and sensitivity in order to help you
determine appropriate protection and retention controls.
Best Practices:
• Identify the data within your workload: This includes the type and classification of data, the
associated business processes. data owner, applicable legal and compliance requirements, where it’s
stored, and the resulting controls that are needed to be enforced. This may include classifications to
indicate if the data is intended to be publicly available, if the data is internal use only such as customer
personally identifiable information (PII), or if the data is for more restricted access such as intellectual
property, legally privileged or marked sensitive, and more.
• Define data protection controls: Protect data according to its classification level. For example, secure
data classified as public by using relevant recommendations while protecting sensitive data with
additional controls.
• Automate identification and classification: Automate identification and classification of data to
reduce the risk of human error from manual interactions.
• Define data lifecycle management: Your defined lifecycle strategy should be based on sensitivity
level, as well as legal and organization requirements. Aspects including the duration you retain data
for, data destruction, data access management, data transformation, and data sharing should be
considered.
SEC 8 How do you protect your data at rest?
Protect your data at rest by implementing multiple controls, to reduce the risk of unauthorized access
or mishandling.
Best Practices:
• Implement secure key management: Encryption keys must be stored securely, with strict access
control, for example, by using a key management service such as AWS KMS. Consider using different
keys, and access control to the keys, combined with the AWS IAM and resource policies, to align with
data classification levels and segregation requirements.
• Enforce encryption at rest: Enforce your encryption requirements based on the latest standards and
recommendations to help protect your data at rest.
• Automate data at rest protection: Use automated tools to validate and enforce data at rest protection
continuously, for example, verify that there are only encrypted storage resources.
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Incident Response
• Enforce access control: Enforce access control with least privileges and mechanisms, including
backups, isolation, and versioning, to help protect your data at rest. Consider what data you have that
is publicly accessible.
• Use mechanisms to keep people away from data: Keep all users away from directly accessing
sensitive data and systems under normal operational circumstances. For example, provide a dashboard
instead of direct access to a data store to run queries. Where CI/CD pipelines are not used, determine
which controls and processes are required to adequately provide a normally disabled break-glass
access mechanism.
SEC 9 How do you protect your data in transit?
Protect your data in transit by implementing multiple controls to reduce the risk of unauthorized
access or loss.
Best Practices:
• Implement secure key and certificate management: Store encryption keys and certificates securely
and rotate them at appropriate time intervals while applying strict access control; for example, by
using a certificate management service, such as AWS Certificate Manager (ACM).
• Enforce encryption in transit: Enforce your defined encryption requirements based on appropriate
standards and recommendations to help you meet your organizational, legal, and compliance
requirements.
• Automate detection of unintended data access: Use tools such as GuardDuty to automatically detect
attempts to move data outside of defined boundaries based on data classification level, for example,
to detect a trojan that is copying data to an unknown or untrusted network using the DNS protocol.
• Authenticate network communications: Verify the identity of communications by using protocols
that support authentication, such as Transport Layer Security (TLS) or IPsec.
Incident Response
SEC 10 How do you anticipate, respond to, and recover from incidents?
Preparation is critical to timely and effective investigation, response to, and recovery from security
incidents to help minimize disruption to your organization.
Best Practices:
• Identify key personnel and external resources: Identify internal and external personnel, resources,
and legal obligations that would help your organization respond to an incident.
• Develop incident management plans: Create plans to help you respond to, communicate during, and
recover from an incident. For example, you can start an incident response plan with the most likely
scenarios for your workload and organization. Include how you would communicate and escalate both
internally and externally.
• Prepare forensic capabilities: Identify and prepare forensic investigation capabilities that are suitable,
including external specialists, tools, and automation.
• Automate containment capability: Automate containment and recovery of an incident to reduce
response times and organizational impact.
• Pre-provision access: Ensure that incident responders have the correct access pre-provisioned into
AWS to reduce the time for investigation through to recovery.
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Reliability
• Pre-deploy tools: Ensure that security personnel have the right tools pre-deployed into AWS to reduce
the time for investigation through to recovery.
• Run game days: Practice incident response game days (simulations) regularly, incorporate lessons
learned into your incident management plans, and continuously improve.
Reliability
Topics
• Foundations (p. 58)
• Workload Architecture (p. 59)
• Change Management (p. 61)
• Failure Management (p. 62)
Foundations
REL 1 How do you manage service quotas and constraints?
limits). These quotas exist to prevent accidentally provisioning more resources than you need and
to limit request rates on API operations so as to protect services from abuse. There are also resource
constraints, for example, the rate that you can push bits down a fiber-optic cable, or the amount of
storage on a physical disk.
Best Practices:
• Aware of service quotas and constraints: You are aware of your default quotas and quota increase
requests for your workload architecture. You additionally know which resource constraints, such as disk
or network, are potentially impactful.
• Manage service quotas across accounts and regions: If you are using multiple AWS accounts or AWS
Regions, ensure that you request the appropriate quotas in all environments in which your production
workloads run.
• Accommodate fixed service quotas and constraints through architecture: Be aware of unchangeable
service quotas and physical resources, and architect to prevent these from impacting reliability.
• Monitor and manage quotas: Evaluate your potential usage and increase your quotas appropriately
allowing for planned growth in usage.
• Automate quota management: Implement tools to alert you when thresholds are being approached.
By using AWS Service Quotas APIs, you can automate quota increase requests.
• Ensure that a sufficient gap exists between the current quotas and the maximum usage to
accommodate failover: When a resource fails, it may still be counted against quotas until its
successfully terminated. Ensure that your quotas cover the overlap of all failed resources with
replacements before the failed resources are terminated. You should consider an Availability Zone
failure when calculating this gap.
REL 2 How do you plan your network topology?
Workloads often exist in multiple environments. These include multiple cloud environments (both
publicly accessible and private) and possibly your existing data center infrastructure. Plans must
include network considerations such as intra- and inter-system connectivity, public IP address
management, private IP address management, and domain name resolution.
58

Best Practices:
• Use highly available network connectivity for your workload public endpoints: These endpoints
and the routing to them must be highly available. To achieve this, use highly available DNS, content
delivery networks (CDNs), API Gateway, load balancing, or reverse proxies.
• Provision redundant connectivity between private networks in the cloud and on-premises
environments: Use multiple AWS Direct Connect (DX) connections or VPN tunnels between separately
deployed private networks. Use multiple DX locations for high availability. If using multiple AWS
Regions, ensure redundancy in at least two of them. You might want to evaluate AWS Marketplace
appliances that terminate VPNs. If you use AWS Marketplace appliances, deploy redundant instances
for high availability in different Availability Zones.
• Ensure IP subnet allocation accounts for expansion and availability: Amazon VPC IP address
ranges must be large enough to accommodate workload requirements, including factoring in future
expansion and allocation of IP addresses to subnets across Availability Zones. This includes load
balancers, EC2 instances, and container-based applications.
• Prefer hub-and-spoke topologies over many-to-many mesh: If more than two network address
spaces (for example, VPCs and on-premises networks) are connected via VPC peering, AWS Direct
Connect, or VPN, then use a hub-and-spoke model, like that provided by AWS Transit Gateway.
• Enforce non-overlapping private IP address ranges in all private address spaces where they are
connected: The IP address ranges of each of your VPCs must not overlap when peered or connected
via VPN. You must similarly avoid IP address conflicts between a VPC and on-premises environments or
with other cloud providers that you use. You must also have a way to allocate private IP address ranges
when needed.
REL 3 How do you design your workload service architecture?
Build highly scalable and reliable workloads using a service-oriented architecture (SOA) or a
microservices architecture. Service-oriented architecture (SOA) is the practice of making software
components reusable via service interfaces. Microservices architecture goes further to make
components smaller and simpler.
Best Practices:
• Choose how to segment your workload: Monolithic architecture should be avoided. Instead, you
should choose between SOA and microservices. When making each choice, balance the benefits
against the complexities—what is right for a new product racing to first launch is different than what
a workload built to scale from the start needs. The benefits of using smaller segments include greater
agility, organizational flexibility, and scalability. Complexities include possible increased latency, more
complex debugging, and increased operational burden
• Build services focused on specific business domains and functionality: SOA builds services with
well-delineated functions defined by business needs. Microservices use domain models and bounded
context to limit this further so that each service does just one thing. Focusing on specific functionality
enables you to differentiate the reliability requirements of different services, and target investments
more specifically. A concise business problem and having a small team associated with each service
also enables easier organizational scaling.
• Provide service contracts per API: Service contracts are documented agreements between teams
on service integration and include a machine-readable API definition, rate limits, and performance
expectations. A versioning strategy allows clients to continue using the existing API and migrate their
applications to the newer API when they are ready. Deployment can happen anytime, as long as the
contract is not violated. The service provider team can use the technology stack of their choice to
satisfy the API contract. Similarly, the service consumer can use their own technology.
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REL 4 How do you design interactions in a distributed system to prevent failures?
components or the workload. These best practices prevent failures and improve mean time between
failures (MTBF).
Best Practices:
• Identify which kind of distributed system is required: Hard real-time distributed systems require
responses to be given synchronously and rapidly, while soft real-time systems have a more generous
time window of minutes or more for response. Offline systems handle responses through batch or
asynchronous processing. Hard real-time distributed systems have the most stringent reliability
requirements.
• Implement loosely coupled dependencies: Dependencies such as queuing systems, streaming
systems, workflows, and load balancers are loosely coupled. Loose coupling helps isolate behavior of a
component from other components that depend on it, increasing resiliency and agility
• Make all responses idempotent: An idempotent service promises that each request is completed
exactly once, such that making multiple identical requests has the same effect as making a single
request. An idempotent service makes it easier for a client to implement retries without fear that a
request will be erroneously processed multiple times. To do this, clients can issue API requests with an
idempotency token—the same token is used whenever the request is repeated. An idempotent service
API uses the token to return a response identical to the response that was returned the first time that
the request was completed.
• Do constant work: Systems can fail when there are large, rapid changes in load. For example, if your
workload is doing a health check that monitors the health of thousands of servers, it should send the
same size payload (a full snapshot of the current state) each time. Whether no servers are failing, or all
of them, the health check system is doing constant work with no large, rapid changes.
REL 5 How do you design interactions in a distributed system to mitigate or withstand failures?
Distributed systems rely on communications networks to interconnect components (such as servers
or services). Your workload must operate reliably despite data loss or latency over these networks.
components or the workload. These best practices enable workloads to withstand stresses or failures,
more quickly recover from them, and mitigate the impact of such impairments. The result is improved
mean time to recovery (MTTR).
Best Practices:
• Implement graceful degradation to transform applicable hard dependencies into soft
dependencies: When a component's dependencies are unhealthy, the component itself can still
function, although in a degraded manner. For example, when a dependency call fails, failover to a
predetermined static response.
• Throttle requests: This is a mitigation pattern to respond to an unexpected increase in demand. Some
requests are honored but those over a defined limit are rejected and return a message indicating they
have been throttled. The expectation on clients is that they will back off and abandon the request or
try again at a slower rate.
• Control and limit retry calls: Use exponential backoff to retry after progressively longer intervals.
Introduce jitter to randomize those retry intervals, and limit the maximum number of retries.
60

Change Management
• Fail fast and limit queues: If the workload is unable to respond successfully to a request, then fail fast.
This allows the releasing of resources associated with a request, and permits the service to recover if
it’s running out of resources. If the workload is able to respond successfully but the rate of requests
is too high, then use a queue to buffer requests instead. However, do not allow long queues that can
result in serving stale requests that the client has already given up on.
• Set client timeouts: Set timeouts appropriately, verify them systematically, and do not rely on default
values as they are generally set too high
• Make services stateless where possible: Services should either not require state, or should offload
state such that between different client requests, there is no dependence on locally stored data on
disk or in memory. This enables servers to be replaced at will without causing an availability impact.
Amazon ElastiCache or Amazon DynamoDB are good destinations for offloaded state.
• Implement emergency levers: These are rapid processes that may mitigate availability impact on your
workload. They can be operated in the absence of a root cause. An ideal emergency lever reduces the
cognitive burden on the resolvers to zero by providing fully deterministic activation and deactivation
criteria. Example levers include blocking all robot traffic or serving a static response. Levers are often
manual, but they can also be automated.
Change Management
REL 6 How do you monitor workload resources?
Logs and metrics are powerful tools to gain insight into the health of your workload. You can configure
your workload to monitor logs and metrics and send notifications when thresholds are crossed or
significant events occur. Monitoring enables your workload to recognize when low-performance
thresholds are crossed or failures occur, so it can recover automatically in response.
Best Practices:
• Monitor all components for the workload (Generation): Monitor the components of the workload
with Amazon CloudWatch or third-party tools. Monitor AWS services with AWS Personal Health
Dashboard
• Define and calculate metrics (Aggregation): Store log data and apply filters where necessary
to calculate metrics, such as counts of a specific log event, or latency calculated from log event
timestamps
• Send notifications (Real-time processing and alarming): Organizations that need to know, receive
notifications when significant events occur
• Automate responses (Real-time processing and alarming): Use automation to take action when an
event is detected, for example, to replace failed components
• Storage and Analytics: Collect log files and metrics histories and analyze these for broader trends and
workload insights
• Conduct reviews regularly: Frequently review how workload monitoring is implemented and update it
based on significant events and changes
• Monitor end-to-end tracing of requests through your system: Use AWS X-Ray or third-party tools
so that developers can more easily analyze and debug distributed systems to understand how their
applications and its underlying services are performing
REL 7 How do you design your workload to adapt to changes in demand?
A scalable workload provides elasticity to add or remove resources automatically so that they closely
match the current demand at any given point in time.
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Failure Management
Best Practices:
• Use automation when obtaining or scaling resources: When replacing impaired resources or scaling
your workload, automate the process by using managed AWS services, such as Amazon S3 and AWS
Auto Scaling. You can also use third-party tools and AWS SDKs to automate scaling.
• Obtain resources upon detection of impairment to a workload: Scale resources reactively when
necessary if availability is impacted, to restore workload availability.
• Obtain resources upon detection that more resources are needed for a workload: Scale resources
proactively to meet demand and avoid availability impact.
• Load test your workload: Adopt a load testing methodology to measure if scaling activity meets
workload requirements.
REL 8 How do you implement change?
Controlled changes are necessary to deploy new functionality, and to ensure that the workloads
and the operating environment are running known software and can be patched or replaced in a
predictable manner. If these changes are uncontrolled, then it makes it difficult to predict the effect of
these changes, or to address issues that arise because of them.
Best Practices:
• Use runbooks for standard activities such as deployment: Runbooks are the predefined steps used
to achieve specific outcomes. Use runbooks to perform standard activities, whether done manually or
automatically. Examples include deploying a workload, patching it, or making DNS modifications.
• Integrate functional testing as part of your deployment: Functional tests are run as part of
automated deployment. If success criteria are not met, the pipeline is halted or rolled back.
• Integrate resiliency testing as part of your deployment: Resiliency tests (as part of chaos
engineering) are run as part of the automated deployment pipeline in a pre-prod environment.
• Deploy using immutable infrastructure: This is a model that mandates that no updates, security
patches, or configuration changes happen in-place on production workloads. When a change is
needed, the architecture is built onto new infrastructure and deployed into production.
• Deploy changes with automation: Deployments and patching are automated to eliminate negative
impact.
Failure Management
REL 9 How do you back up data?
Back up data, applications, and configuration to meet your requirements for recovery time objectives
(RTO) and recovery point objectives (RPO).
Best Practices:
• Identify and back up all data that needs to be backed up, or reproduce the data from sources:
Amazon S3 can be used as a backup destination for multiple data sources. AWS services such as
Amazon EBS, Amazon RDS, and Amazon DynamoDB have built in capabilities to create backups.
Third-party backup software can also be used. Alternatively, if the data can be reproduced from other
sources to meet RPO, you might not require a backup
• Secure and encrypt backups: Detect access using authentication and authorization, such as AWS IAM,
and detect data integrity compromise by using encryption.
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Failure Management
• Perform data backup automatically: Configure backups to be taken automatically based on a periodic
schedule, or by changes in the dataset. RDS instances, EBS volumes, DynamoDB tables, and S3 objects
can all be configured for automatic backup. AWS Marketplace solutions or third-party solutions can
also be used.
• Perform periodic recovery of the data to verify backup integrity and processes: Validate that
your backup process implementation meets your recovery time objectives (RTO) and recovery point
objectives (RPO) by performing a recovery test.
REL 10 How do you use fault isolation to protect your workload?
Fault isolated boundaries limit the effect of a failure within a workload to a limited number of
components. Components outside of the boundary are unaffected by the failure. Using multiple fault
isolated boundaries, you can limit the impact on your workload.
Best Practices:
• Deploy the workload to multiple locations: Distribute workload data and resources across multiple
Availability Zones or, where necessary, across AWS Regions. These locations can be as diverse as
required.
• Automate recovery for components constrained to a single location: If components of the workload
can only run in a single Availability Zone or on-premises data center, you must implement the
capability to do a complete rebuild of the workload within your defined recovery objectives.
• Use bulkhead architectures to limit scope of impact: Like the bulkheads on a ship, this pattern
ensures that a failure is contained to a small subset of requests/users so that the number of impaired
requests is limited, and most can continue without error. Bulkheads for data are often called partitions,
while bulkheads for services are known as cells.
REL 11 How do you design your workload to withstand component failures?
Workloads with a requirement for high availability and low mean time to recovery (MTTR) must be
architected for resiliency.
Best Practices:
• Monitor all components of the workload to detect failures: Continuously monitor the health of your
workload so that you and your automated systems are aware of degradation or complete failure as
soon as they occur. Monitor for key performance indicators (KPIs) based on business value.
• Fail over to healthy resources: Ensure that if a resource failure occurs, that healthy resources can
continue to serve requests. For location failures (such as Availability Zone or AWS Region) ensure you
have systems in place to failover to healthy resources in unimpaired locations.
• Automate healing on all layers: Upon detection of a failure, use automated capabilities to perform
actions to remediate.
• Use static stability to prevent bimodal behavior: Bimodal behavior is when your workload exhibits
different behavior under normal and failure modes, for example, relying on launching new instances
if an Availability Zone fails. You should instead build workloads that are statically stable and operate
in only one mode. In this case, provision enough instances in each Availability Zone to handle the
workload load if one AZ were removed and then use Elastic Load Balancing or Amazon Route 53
health checks to shift load away from the impaired instances.
• Send notifications when events impact availability: Notifications are sent upon the detection of
significant events, even if the issue caused by the event was automatically resolved.
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Failure Management
REL 12 How do you test reliability?
After you have designed your workload to be resilient to the stresses of production, testing is the only
way to ensure that it will operate as designed, and deliver the resiliency you expect.
Best Practices:
• Use playbooks to investigate failures: Enable consistent and prompt responses to failure scenarios
that are not well understood, by documenting the investigation process in playbooks. Playbooks are
the predefined steps performed to identify the factors contributing to a failure scenario. The results
from any process step are used to determine the next steps to take until the issue is identified or
escalated.
• Perform post-incident analysis: Review customer-impacting events, and identify the contributing
factors and preventative action items. Use this information to develop mitigations to limit or prevent
recurrence. Develop procedures for prompt and effective responses. Communicate contributing factors
and corrective actions as appropriate, tailored to target audiences. Have a method to communicate
these causes to others as needed.
• Test functional requirements: These include unit tests and integration tests that validate required
functionality.
• Test scaling and performance requirements: This includes load testing to validate that the workload
meets scaling and performance requirements.
• Test resiliency using chaos engineering: Run tests that inject failures regularly into pre-production
and production environments. Hypothesize how your workload will react to the failure, then compare
your hypothesis to the testing results and iterate if they do not match. Ensure that production testing
does not impact users.
• Conduct game days regularly: Use game days to regularly exercise your procedures for responding
to events and failures as close to production as possible (including in production environments) with
the people who will be involved in actual failure scenarios. Game days enforce measures to ensure that
production testing does not impact users.
REL 13 How do you plan for disaster recovery (DR)?
Having backups and redundant workload components in place is the start of your DR strategy. RTO
and RPO are your objectives for restoration of your workload. Set these based on business needs.
Implement a strategy to meet these objectives, considering locations and function of workload
resources and data. The probability of disruption and cost of recovery are also key factors that help to
inform the business value of providing disaster recovery for a workload.
Best Practices:
• Define recovery objectives for downtime and data loss: The workload has a recovery time objective
(RTO) and recovery point objective (RPO).
• Use defined recovery strategies to meet the recovery objectives: A disaster recovery (DR) strategy
has been defined to meet objectives. Choose a strategy such as: backup and restore, active/passive
(pilot light or warm standby), or active/active.
• Test disaster recovery implementation to validate the implementation: Regularly test failover to DR
to ensure that RTO and RPO are met.
• Manage configuration drift at the DR site or region: Ensure that the infrastructure, data, and
configuration are as needed at the DR site or region. For example, check that AMIs and service quotas
are up to date.
64

• Automate recovery: Use AWS or third-party tools to automate system recovery and route traffic to the
DR site or region.
Topics
• Selection (p. 65)
• Review (p. 68)
• Monitoring (p. 68)
• Tradeoffs (p. 69)
Selection
PERF 1 How do you select the best performing architecture?
Often, multiple approaches are required for optimal performance across a workload. Well-architected
systems use multiple solutions and features to improve performance.
Best Practices:
• Understand the available services and resources: Learn about and understand the wide range of
services and resources available in the cloud. Identify the relevant services and configuration options
for your workload, and understand how to achieve optimal performance.
• Define a process for architectural choices: Use internal experience and knowledge of the cloud,
or external resources such as published use cases, relevant documentation, or whitepapers to
define a process to choose resources and services. You should define a process that encourages
experimentation and benchmarking with the services that could be used in your workload.
• Factor cost requirements into decisions : Workloads often have cost requirements for operation. Use
internal cost controls to select resource types and sizes based on predicted resource need.
• Use policies or reference architectures: Maximize performance and efficiency by evaluating
internal policies and existing reference architectures and using your analysis to select services and
configurations for your workload.
• Use guidance from your cloud provider or an appropriate partner: Use cloud company resources,
such as solutions architects, professional services, or an appropriate partner to guide your decisions.
These resources can help review and improve your architecture for optimal performance.
• Benchmark existing workloads: Benchmark the performance of an existing workload to understand
how it performs on the cloud. Use the data collected from benchmarks to drive architectural decisions.
• Load test your workload: Deploy your latest workload architecture on the cloud using different
resource types and sizes. Monitor the deployment to capture performance metrics that identify
bottlenecks or excess capacity. Use this performance information to design or improve your
architecture and resource selection.
PERF 2 How do you select your compute solution?
The optimal compute solution for a workload varies based on application design, usage patterns, and
configuration settings. Architectures can use different compute solutions for various components
and enable different features to improve performance. Selecting the wrong compute solution for an
architecture can lead to lower performance efficiency.
65

Selection
Best Practices:
• Evaluate the available compute options: Understand the performance characteristics of the compute-
related options available to you. Know how instances, containers, and functions work, and what
advantages, or disadvantages, they bring to your workload.
• Understand the available compute configuration options: Understand how various options
complement your workload, and which configuration options are best for your system. Examples of
these options include instance family, sizes, features (GPU, I/O), function sizes, container instances, and
single versus multi-tenancy.
• Collect compute-related metrics: One of the best ways to understand how your compute systems
are performing is to record and track the true utilization of various resources. This data can be used to
make more accurate determinations about resource requirements.
• Determine the required configuration by right-sizing: Analyze the various performance
characteristics of your workload and how these characteristics relate to memory, network, and CPU
usage. Use this data to choose resources that best match your workload's profile. For example, a
memory-intensive workload, such as a database, could be served best by the r-family of instances.
However, a bursting workload can benefit more from an elastic container system.
• Use the available elasticity of resources: The cloud provides the flexibility to expand or reduce your
resources dynamically through a variety of mechanisms to meet changes in demand. Combined with
compute-related metrics, a workload can automatically respond to changes and utilize the optimal set
of resources to achieve its goal.
• Re-evaluate compute needs based on metrics: Use system-level metrics to identify the behavior and
requirements of your workload over time. Evaluate your workload's needs by comparing the available
resources with these requirements and make changes to your compute environment to best match
your workload's profile. For example, over time a system might be observed to be more memory-
intensive than initially thought, so moving to a different instance family or size could improve both
performance and efficiency.
PERF 3 How do you select your storage solution?
The optimal storage solution for a system varies based on the kind of access method (block, file, or
object), patterns of access (random or sequential), required throughput, frequency of access (online,
offline, archival), frequency of update (WORM, dynamic), and availability and durability constraints.
Well-architected systems use multiple storage solutions and enable different features to improve
performance and use resources efficiently.
Best Practices:
• Understand storage characteristics and requirements: Understand the different characteristics
(for example, shareable, file size, cache size, access patterns, latency, throughput, and persistence of
data) that are required to select the services that best fit your workload, such as object storage, block
storage, file storage, or instance storage.
• Evaluate available configuration options: Evaluate the various characteristics and configuration
options and how they relate to storage. Understand where and how to use provisioned IOPS, SSDs,
magnetic storage, object storage, archival storage, or ephemeral storage to optimize storage space
and performance for your workload.
• Make decisions based on access patterns and metrics: Choose storage systems based on your
workload's access patterns and configure them by determining how the workload accesses data.
Increase storage efficiency by choosing object storage over block storage. Configure the storage
options you choose to match your data access patterns.
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Selection
PERF 4 How do you select your database solution?
The optimal database solution for a system varies based on requirements for availability, consistency,
partition tolerance, latency, durability, scalability, and query capability. Many systems use different
database solutions for various subsystems and enable different features to improve performance.
Selecting the wrong database solution and features for a system can lead to lower performance
efficiency.
Best Practices:
• Understand data characteristics: Understand the different characteristics of data in your workload.
Determine if the workload requires transactions, how it interacts with data, and what its performance
demands are. Use this data to select the best performing database approach for your workload (for
example, relational databases, NoSQL Key-value, document, wide column, graph, time series, or in-
memory storage).
• Evaluate the available options: Evaluate the services and storage options that are available as part
of the selection process for your workload's storage mechanisms. Understand how, and when, to use a
given service or system for data storage. Learn about available configuration options that can optimize
database performance or efficiency, such as provisioned IOPs, memory and compute resources, and
caching.
• Collect and record database performance metrics: Use tools, libraries, and systems that record
performance measurements related to database performance. For example, measure transactions
per second, slow queries, or system latency introduced when accessing the database. Use this data to
understand the performance of your database systems.
• Choose data storage based on access patterns: Use the access patterns of the workload to decide
which services and technologies to use. For example, utilize a relational database for workloads that
require transactions, or a key-value store that provides higher throughput but is eventually consistent
where applicable.
• Optimize data storage based on access patterns and metrics: Use performance characteristics and
access patterns that optimize how data is stored or queried to achieve the best possible performance.
Measure how optimizations such as indexing, key distribution, data warehouse design, or caching
strategies impact system performance or overall efficiency.
PERF 5 How do you configure your networking solution?
The optimal network solution for a workload varies based on latency, throughput requirements,
jitter, and bandwidth. Physical constraints, such as user or on-premises resources, determine location
options. These constraints can be offset with edge locations or resource placement.
Best Practices:
• Understand how networking impacts performance: Analyze and understand how network-related
decisions impact workload performance. For example, network latency often impacts the user
experience, and using the wrong protocols can starve network capacity through excessive overhead.
• Evaluate available networking features: Evaluate networking features in the cloud that may increase
performance. Measure the impact of these features through testing, metrics, and analysis. For
example, take advantage of network-level features that are available to reduce latency, network
distance, or jitter.
• Choose appropriately sized dedicated connectivity or VPN for hybrid workloads: When there is a
requirement for on-premise communication, ensure that you have adequate bandwidth for workload
performance. Based on bandwidth requirements, a single dedicated connection or a single VPN might
not be enough, and you must enable traffic load balancing across multiple connections.
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Review
• Leverage load-balancing and encryption offloading: Distribute traffic across multiple resources or
services to allow your workload to take advantage of the elasticity that the cloud provides. You can
also use load balancing for offloading encryption termination to improve performance and to manage
and route traffic effectively.
• Choose network protocols to improve performance: Make decisions about protocols for
communication between systems and networks based on the impact to the workload’s performance.
• Choose your workload’s location based on network requirements: Use the cloud location options
available to reduce network latency or improve throughput. Utilize AWS Regions, Availability Zones,
placement groups, and edge locations such as Outposts, Local Zones, and Wavelength, to reduce
network latency or improve throughput.
• Optimize network configuration based on metrics: Use collected and analyzed data to make
informed decisions about optimizing your network configuration. Measure the impact of those
changes and use the impact measurements to make future decisions.
Review
PERF 6 How do you evolve your workload to take advantage of new releases?
When architecting workloads, there are finite options that you can choose from. However, over time,
new technologies and approaches become available that could improve the performance of your
workload.
Best Practices:
• Stay up-to-date on new resources and services: Evaluate ways to improve performance as new
services, design patterns, and product offerings become available. Determine which of these could
improve performance or increase the efficiency of the workload through ad-hoc evaluation, internal
discussion, or external analysis.
• Define a process to improve workload performance: Define a process to evaluate new services,
design patterns, resource types, and configurations as they become available. For example, run existing
performance tests on new instance offerings to determine their potential to improve your workload.
• Evolve workload performance over time: As an organization, use the information gathered through
the evaluation process to actively drive adoption of new services or resources when they become
available.
Monitoring
PERF 7 How do you monitor your resources to ensure they are performing?
System performance can degrade over time. Monitor system performance to identify degradation and
remediate internal or external factors, such as the operating system or application load.
Best Practices:
• Record performance-related metrics: Use a monitoring and observability service to record
performance-related metrics. For example, record database transactions, slow queries, I/O latency,
HTTP request throughput, service latency, or other key data.
• Analyze metrics when events or incidents occur: In response to (or during) an event or incident, use
monitoring dashboards or reports to understand and diagnose the impact. These views provide insight
into which portions of the workload are not performing as expected.
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Tradeoffs
• Establish Key Performance Indicators (KPIs) to measure workload performance: Identify the KPIs
that indicate whether the workload is performing as intended. For example, an API-based workload
might use overall response latency as an indication of overall performance, and an e-commerce site
might choose to use the number of purchases as its KPI.
• Use monitoring to generate alarm-based notifications: Using the performance-related key
performance indicators (KPIs) that you defined, use a monitoring system that generates alarms
automatically when these measurements are outside expected boundaries.
• Review metrics at regular intervals: As routine maintenance, or in response to events or incidents,
review which metrics are collected. Use these reviews to identify which metrics were key in addressing
issues and which additional metrics, if they were being tracked, would help to identify, address, or
prevent issues.
• Monitor and alarm proactively: Use key performance indicators (KPIs), combined with monitoring
and alerting systems, to proactively address performance-related issues. Use alarms to trigger
automated actions to remediate issues where possible. Escalate the alarm to those able to respond if
automated response is not possible. For example, you may have a system that can predict expected
key performance indicators (KPI) values and alarm when they breach certain thresholds, or a tool that
can automatically halt or roll back deployments if KPIs are outside of expected values.
Tradeoffs
PERF 8 How do you use tradeoffs to improve performance?
When architecting solutions, determining tradeoffs enables you to select an optimal approach. Often
you can improve performance by trading consistency, durability, and space for time and latency.
Best Practices:
• Understand the areas where performance is most critical: Understand and identify areas where
increasing the performance of your workload will have a positive impact on efficiency or customer
experience. For example, a website that has a large amount of customer interaction can benefit from
using edge services to move content delivery closer to customers.
• Learn about design patterns and services: Research and understand the various design patterns and
services that help improve workload performance. As part of the analysis, identify what you could
trade to achieve higher performance. For example, using a cache service can help to reduce the load
placed on database systems; however, it requires some engineering to implement safe caching or
possible introduction of eventual consistency in some areas.
• Identify how tradeoffs impact customers and efficiency: When evaluating performance-related
improvements, determine which choices will impact your customers and workload efficiency. For
example, if using a key-value data store increases system performance, it is important to evaluate how
the eventually consistent nature of it will impact customers.
• Measure the impact of performance improvements: As changes are made to improve performance,
evaluate the collected metrics and data. Use this information to determine impact that the
performance improvement had on the workload, the workload’s components, and your customers.
This measurement helps you understand the improvements that result from the tradeoff, and helps
you determine if any negative side-effects were introduced.
• Use various performance-related strategies: Where applicable, utilize multiple strategies to improve
performance. For example, using strategies like caching data to prevent excessive network or database
calls, using read-replicas for database engines to improve read rates, sharding or compressing data
where possible to reduce data volumes, and buffering and streaming of results as they are available to
avoid blocking.
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Cost Optimization
Cost Optimization
Topics
• Practice Cloud Financial Management (p. 70)
• Expenditure and usage awareness (p. 70)
• Cost-effective resources (p. 72)
• Manage demand and supply resources (p. 74)
• Optimize over time (p. 74)
Practice Cloud Financial Management
COST 1 How do you implement cloud financial management?
Implementing Cloud Financial Management enables organizations to realize business value and
financial success as they optimize their cost and usage and scale on AWS.
Best Practices:
• Establish a cost optimization function: Create a team that is responsible for establishing and
maintaining cost awareness across your organization. The team requires people from finance,
technology, and business roles across the organization.
• Establish a partnership between finance and technology: Involve finance and technology teams in
cost and usage discussions at all stages of your cloud journey. Teams regularly meet and discuss topics
such as organizational goals and targets, current state of cost and usage, and financial and accounting
practices.
• Establish cloud budgets and forecasts: Adjust existing organizational budgeting and forecasting
processes to be compatible with the highly variable nature of cloud costs and usage. Processes must
be dynamic using trend based or business driver-based algorithms, or a combination.
• Implement cost awareness in your organizational processes: Implement cost awareness into new or
existing processes that impact usage, and leverage existing processes for cost awareness. Implement
cost awareness into employee training.
• Report and notify on cost optimization: Configure AWS Budgets to provide notifications on cost and
usage against targets. Have regular meetings to analyze this workload's cost efficiency and to promote
cost aware culture.
• Monitor cost proactively: Implement tooling and dashboards to monitor cost proactively for the
workload. Do not just look at costs and categories when you receive notifications. This helps to identify
positive trends and promote them throughout your organization.
• Keep up to date with new service releases: Consult regularly with experts or APN Partners to consider
which services and features provide lower cost. Review AWS blogs and other information sources.
COST 2 How do you govern usage?
Establish policies and mechanisms to ensure that appropriate costs are incurred while objectives are
achieved. By employing a checks-and-balances approach, you can innovate without overspending.
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Best Practices:
• Develop policies based on your organization requirements: Develop policies that define how
resources are managed by your organization. Policies should cover cost aspects of resources and
workloads, including creation, modification and decommission over the resource lifetime.
• Implement goals and targets: Implement both cost and usage goals for your workload. Goals provide
direction to your organization on cost and usage, and targets provide measurable outcomes for your
workloads.
• Implement an account structure: Implement a structure of accounts that maps to your organization.
This assists in allocating and managing costs throughout your organization.
• Implement groups and roles: Implement groups and roles that align to your policies and control who
can create, modify, or decommission instances and resources in each group. For example, implement
development, test, and production groups. This applies to AWS services and third-party solutions.
• Implement cost controls: Implement controls based on organization policies and defined groups and
roles. These ensure that costs are only incurred as defined by organization requirements: for example,
control access to regions or resource types with IAM policies.
• Track project lifecycle: Track, measure, and audit the lifecycle of projects, teams, and environments to
avoid using and paying for unnecessary resources.
COST 3 How do you monitor usage and cost?
Establish policies and procedures to monitor and appropriately allocate your costs. This allows you to
measure and improve the cost efficiency of this workload.
Best Practices:
• Configure detailed information sources: Configure the AWS Cost and Usage Report, and Cost Explorer
hourly granularity, to provide detailed cost and usage information. Configure your workload to have
log entries for every delivered business outcome.
• Identify cost attribution categories: Identify organization categories that could be used to allocate
cost within your organization.
• Establish organization metrics: Establish the organization metrics that are required for this workload.
Example metrics of a workload are customer reports produced or web pages served to customers.
• Configure billing and cost management tools: Configure AWS Cost Explorer and AWS Budgets inline
with your organization policies.
• Add organization information to cost and usage: Define a tagging schema based on organization,
and workload attributes, and cost allocation categories. Implement tagging across all resources. Use
Cost Categories to group costs and usage according to organization attributes.
• Allocate costs based on workload metrics: Allocate the workload's costs by metrics or business
outcomes to measure workload cost efficiency. Implement a process to analyze the AWS Cost and
Usage Report with Amazon Athena, which can provide insight and charge back capability.
COST 4 How do you decommission resources?
Implement change control and resource management from project inception to end-of-life. This
ensures you shut down or terminate unused resources to reduce waste.
Best Practices:
71

• Track resources over their life time: Define and implement a method to track resources and their
associations with systems over their life time. You can use tagging to identify the workload or function
of the resource.
• Implement a decommissioning process: Implement a process to identify and decommission orphaned
resources.
• Decommission resources: Decommission resources triggered by events such as periodic audits, or
changes in usage. Decommissioning is typically performed periodically, and is manual or automated.
• Decommission resources automatically: Design your workload to gracefully handle resource
termination as you identify and decommission non-critical resources, resources that are not required,
or resources with low utilization.
COST 5 How do you evaluate cost when you select services?
Amazon EC2, Amazon EBS, and Amazon S3 are building-block AWS services. Managed services, such
as Amazon RDS and Amazon DynamoDB, are higher level, or application level, AWS services. By
selecting the appropriate building blocks and managed services, you can optimize this workload for
cost. For example, using managed services, you can reduce or remove much of your administrative and
operational overhead, freeing you to work on applications and business-related activities.
Best Practices:
• Identify organization requirements for cost: Work with team members to define the balance
between cost optimization and other pillars, such as performance and reliability, for this workload.
• Analyze all components of this workload: Ensure every workload component is analyzed, regardless
of current size or current costs. Review effort should reflect potential benefit, such as current and
projected costs.
• Perform a thorough analysis of each component: Look at overall cost to the organization of each
component. Look at total cost of ownership by factoring in cost of operations and management,
especially when using managed services. Review effort should reflect potential benefit: for example,
time spent analyzing is proportional to component cost.
• Select software with cost effective licensing: Open source software will eliminate software licensing
costs, which can contribute significant costs to workloads. Where licensed software is required, avoid
licenses bound to arbitrary attributes such as CPUs, look for licenses that are bound to output or
outcomes. The cost of these licenses scales more closely to the benefit they provide.
• Select components of this workload to optimize cost in line with organization priorities: Factor in
cost when selecting all components. This includes using application level and managed services, such
as Amazon RDS, Amazon DynamoDB, Amazon SNS, and Amazon SES to reduce overall organization
cost. Use serverless and containers for compute, such as AWS Lambda, Amazon S3 for static websites,
and Amazon ECS. Minimize license costs by using open source software, or software that does not
have license fees: for example, Amazon Linux for compute workloads or migrate databases to Amazon
Aurora.
• Perform cost analysis for different usage over time: Workloads can change over time. Some services
or features are more cost effective at different usage levels. By performing the analysis on each
component over time and at projected usage, you ensure the workload remains cost effective over its
lifetime..
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COST 6 How do you meet cost targets when you select resource type, size and number?
Ensure that you choose the appropriate resource size and number of resources for the task at hand.
You minimize waste by selecting the most cost effective type, size, and number.
Best Practices:
• Perform cost modeling: Identify organization requirements and perform cost modeling of the
workload and each of its components. Perform benchmark activities for the workload under different
predicted loads and compare the costs. The modeling effort should reflect potential benefit: for
example, time spent is proportional to component cost.
• Select resource type and size based on data: Select resource size or type based on data about the
workload and resource characteristics: for example, compute, memory, throughput, or write intensive.
This selection is typically made using a previous version of the workload (such as an on-premises
version), using documentation, or using other sources of information about the workload.
• Select resource type and size automatically based on metrics: Use metrics from the currently
running workload to select the right size and type to optimize for cost. Appropriately provision
throughput, sizing, and storage for services such as Amazon EC2, Amazon DynamoDB, Amazon EBS
(PIOPS), Amazon RDS, Amazon EMR, and networking. This can be done with a feedback loop such as
automatic scaling or by custom code in the workload.
COST 7 How do you use pricing models to reduce cost?
Use the pricing model that is most appropriate for your resources to minimize expense.
Best Practices:
• Perform pricing model analysis: Analyze each component of the workload. Determine if the
component and resources will be running for extended periods (for commitment discounts), or
dynamic and short running (for spot or on-demand). Perform an analysis on the workload using the
Recommendations feature in AWS Cost Explorer.
• Implement regions based on cost: Resource pricing can be different in each region. Factoring in region
cost ensures you pay the lowest overall price for this workload
• Select third party agreements with cost efficient terms: Cost efficient agreements and terms ensure
the cost of these services scales with the benefits they provide. Select agreements and pricing that
scale when they provide additional benefits to your organization.
• Implement pricing models for all components of this workload: Permanently running resources
should utilize reserved capacity such as Savings Plans or reserved Instances. Short term capacity is
configured to use Spot Instances, or Spot Fleet. On demand is only used for short-term workloads that
cannot be interrupted and do not run long enough for reserved capacity, between 25% to 75% of the
period, depending on the resource type.
• Perform pricing model analysis at the master account level: Use Cost Explorer Savings Plans and
Reserved Instance recommendations to perform regular analysis at the master account level for
commitment discounts.
COST 8 How do you plan for data transfer charges?
Ensure that you plan and monitor data transfer charges so that you can make architectural decisions to
minimize costs. A small yet effective architectural change can drastically reduce your operational costs
over time.
73

Best Practices:
• Perform data transfer modeling: Gather organization requirements and perform data transfer
modeling of the workload and each of its components. This identifies the lowest cost point for its
current data transfer requirements.
• Select components to optimize data transfer cost: All components are selected, and architecture is
designed to reduce data transfer costs. This includes using components such as WAN optimization and
Multi-AZ configurations
• Implement services to reduce data transfer costs: Implement services to reduce data transfer: for
example, using a CDN such as Amazon CloudFront to deliver content to end users, caching layers using
Amazon ElastiCache, or using AWS Direct Connect instead of VPN for connectivity to AWS.
COST 9 How do you manage demand, and supply resources?
For a workload that has balanced spend and performance, ensure that everything you pay for is used
and avoid significantly underutilizing instances. A skewed utilization metric in either direction has an
adverse impact on your organization, in either operational costs (degraded performance due to over-
utilization), or wasted AWS expenditures (due to over-provisioning).
Best Practices:
• Perform an analysis on the workload demand: Analyze the demand of the workload over time.
Ensure the analysis covers seasonal trends and accurately represents operating conditions over the
full workload lifetime. Analysis effort should reflect potential benefit: for example, time spent is
proportional to the workload cost.
• Implement a buffer or throttle to manage demand: Buffering and throttling modify the demand
on your workload, smoothing out any peaks. Implement throttling when your clients perform retries.
Implement buffering to store the request and defer processing until a later time. Ensure your throttles
and buffers are designed so clients receive a response in the required time.
• Supply resources dynamically: Resources are provisioned in a planned manner. This can be
demandbased, such as through automatic scaling, or time-based, where demand is predictable and
resources are provided based on time. These methods result in the least amount of over or under
provisioning.
Optimize over time
COST 10 How do you evaluate new services?
decisions to ensure they continue to be the most cost effective.
Best Practices:
• Develop a workload review process: Develop a process that defines the criteria and process for
workload review. The review effort should reflect potential benefit: for example, core workloads or
workloads with a value of over 10% of the bill are reviewed quarterly, while workloads below 10% are
reviewed annually.
74

Optimize over time
• Review and analyze this workload regularly: Existing workloads are regularly reviewed as per deﬁned
processes.
75

Notices
Customers are responsible for making their own independent assessment of the information in this
document. This document: (a) is for informational purposes only, (b) represents current AWS product
offerings and practices, which are subject to change without notice, and (c) does not create any
commitments or assurances from AWS and its affiliates, suppliers or licensors. AWS products or services
are provided “as is” without warranties, representations, or conditions of any kind, whether express or
implied. The responsibilities and liabilities of AWS to its customers are controlled by AWS agreements,
and this document is not part of, nor does it modify, any agreement between AWS and its customers.
Copyright © 2021 Amazon Web Services, Inc. or its affiliates.
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