Aws well architected-framework

AWS Well-Architected Framework
November 2018

Amazon Web Services AWS Well-Architected Framework
Copyright © 2018 Amazon Web Services, Inc. or its affiliates
Notices
This document is provided for informational purposes only. It represents AWS’s
current product offerings and practices as of the date of issue of this document, which
are subject to change without notice. Customers are responsible for making their
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its affiliates, suppliers or licensors. 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.

Introduction ................................................................................................................................. 1
Definitions ........................................................................................................................... 1
On Architecture .................................................................................................................. 3
General Design Principles ................................................................................................ 5
The Five Pillars of the Framework ......................................................................................... 6
Operational Excellence ..................................................................................................... 6
Security .............................................................................................................................. 12
Reliability ........................................................................................................................... 19
Performance Efficiency ................................................................................................... 25
Cost Optimization ........................................................................................................... 33
The Review Process ................................................................................................................. 39
Conclusion ................................................................................................................................. 41
Contributors .............................................................................................................................. 42
Further Reading ....................................................................................................................... 43
Document Revisions ................................................................................................................ 45
Appendix: Questions, Answers, and Best Practices ........................................................... 46
Operational Excellence ................................................................................................... 46
Security .............................................................................................................................. 55
Reliability ........................................................................................................................... 63
Performance Efficiency ................................................................................................... 69
Cost Optimization ........................................................................................................... 77
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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.
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.
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The pillars of the AWS Well-Architected Framework
Pillar Name Description
Operational Excellence The ability to run and monitor systems to deliver
business value and to continually improve supporting
processes and procedures.
Security The ability to protect information, systems, and assets
while delivering business value through risk assessments
and mitigation strategies.
Reliability The ability of a system to recover from infrastructure
or service disruptions, dynamically acquire computing
resources to meet demand, and mitigate disruptions
such as misconfigurations or transient network issues.
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.
• We use the term workload to identify a set of components that together deliver
business value. The workload is usually the level of detail that business and
technology leaders communicate about.
• Milestones mark key changes in your architecture as it evolves throughout the
product lifecycle (design, testing, go live, and in production).
• 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.
• 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 upon 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
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customer propensity to buy. Security and operational excellence are generally not
traded-off against the other pillars.
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 are often composed of 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
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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
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that carry out automated checks to ensure standards are being met.
This distributed approach is supported by the Amazon leadership principles, and
establishes a culture across all roles that works back
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from the customer. 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. Well-Architected is the customer-
facing implementation of our internal review process, where we have codified our
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Ways of doing things, process, standards, and accepted norms.
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“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.
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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.
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principal engineering thinking across ﬁeld roles like Solutions Architecture and
internal engineering teams. Well-Architected 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, trainings, or lunchtime talks where your principal
engineers can share their thinking on speciﬁc areas with multiple teams.
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General Design Principles
The Well-Architected Framework identifies a set of general design principles to
facilitate good design in the cloud:
• Stop guessing your capacity needs: Eliminate guessing about your infrastructure
capacity needs. When you make a capacity decision before you deploy a system,
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 systems 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: Allow for evolutionary architectures. In a
traditional environment, architectural decisions are often implemented as static,
one-time events, with a few major versions of a system during its lifetime. As a
business and its context continue to change, 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
fact-based 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.
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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.
Operational Excellence
The Operational Excellence pillar includes the ability to run and monitor systems
to deliver business value and to continually improve supporting processes and
procedures.
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.
Design Principles
There are six 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.
• Annotate documentation: In an on-premises environment, documentation is
created by hand, used by people, and hard to keep in sync with the pace of change.
In the cloud, you can automate the creation of annotated documentation after
every build (or automatically annotate hand-crafted documentation). Annotated
documentation can be used by people and systems. Use annotations as an input to
your operations code.
• 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
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procedures appropriately. Set up regular 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 three best practice areas for operational excellence in the cloud:
1. Prepare
2. Operate
3. Evolve
Operations teams need to understand their business and customer needs so they
can effectively and efficiently support business outcomes. Operations creates and
uses procedures to respond to operational events and validates their effectiveness
to support business needs. Operations collects metrics that are used to measure the
achievement of desired business outcomes. Everything continues to change—your
business context, business priorities, customer needs, etc. It's important to design
operations to support evolution over time in response to change and to incorporate
lessons learned through their performance.
Best Practices
Prepare
Effective preparation is required to drive operational excellence. Business success
is enabled by shared goals and understanding across the business, development,
and operations. Common standards simplify workload design and management,
enabling operational success. Design workloads with mechanisms to monitor and gain
insight into application, platform, and infrastructure components, as well as customer
experience and behavior.
Create mechanisms to validate that workloads, or changes, are ready to be moved
into production and supported by operations. Operational readiness is validated
through checklists to ensure a workload meets defined standards and that required
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procedures are adequately captured in runbooks and playbooks. Validate that
there are sufficient trained personnel to effectively support the workload. Prior to
transition, test responses to operational events and failures. Practice responses in
supported environments through failure injection and game day events.
AWS enables operations as code in the cloud and the ability to safely experiment,
develop 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. AWS enables
visibility into your workloads at all layers through various log collection and
monitoring features. Data on use of resources, application programming interfaces
(APIs), and network flow logs can be collected using Amazon CloudWatch, AWS
CloudTrail, and VPC Flow Logs. You can use the collectd plugin, or the CloudWatch
Logs agent, to aggregate information about the operating system into CloudWatch.
The following questions focus on these considerations for operational excellence.
(For a list of operational excellence questions, answers, and best practices, see the
Appendix.)
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 design your workload so that you can understand its state?
Design your workload so that it provides the information necessary for you to understand its
internal state (for example, metrics, logs, and traces) across all components. This enables you
to provide effective responses when appropriate.
OPS 3: 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 deployed, and enable rapid identification and remediation of issues introduced
through deployment activities.
OPS 4: 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 5: 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.
Implement the minimum number of architecture standards for your workloads.
Balance the cost to implement a standard against the benefit to the workload and
the burden upon operations. Reduce the number of supported standards to reduce
the chance that lower-than-acceptable standards will be applied by error. Operations
personnel are often constrained resources.
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Invest in implementing operations activities as code to maximize the productivity of
operations personnel, minimize error rates, and enable automated responses. Adopt
deployment practices that take advantage of the elasticity of the cloud to facilitate
pre-deployment of systems for faster implementations.
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 the workload and operations metrics that will be used
in those calculations to determine if operations are successful. Consider that
operational health includes both the health of the workload and the health and
success of the operations acting upon the workload (for example, deployment and
incident response). Establish baselines from which improvement or degradation of
operations will be identified, 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 the resolution of other events. 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 impact
(that is, duration, scale, and scope). Identify and engage individuals with the authority
to decide 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.
Determine the root cause of unplanned events and unexpected impacts from
planned events. This information will be used to update your procedures to mitigate
future occurrence of events. Communicate root cause with affected communities as
appropriate.
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
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AWS X-Ray, CloudWatch, CloudTrail, and VPC Flow Logs enabling the identification of
workload issues in support of root cause analysis and remediation.
OPS 6: 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 7: 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 8: How do you manage workload and operations events?
Prepare and validate procedures for responding to events to minimize their disruption to your
workload.
Routine operations, as well as responses to unplanned events, should be automated.
Manual processes for deployments, release management, changes, and rollbacks
should be avoided. Releases should not be large batches that are done infrequently.
Rollbacks are more difficult in large changes. Failing to have a rollback plan, or
the ability to mitigate failure impacts, will prevent continuity of operations. Align
metrics to business needs so that responses are effective at maintaining business
continuity. One-time decentralized metrics with manual responses will result in
greater disruption to operations during unplanned events.
Evolve
Evolution of operations is required to sustain operational excellence. Dedicate
work cycles to making continuous incremental improvements. 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.
With AWS Developer Tools you can implement continuous delivery build, test, and
deployment activities that work with a variety of source code, build, testing, and
deployment tools from AWS and third parties. The results of deployment activities
can be used to identify opportunities for improvement for both deployment and
development. You can perform analytics on your metrics data integrating data
from your operations and deployment activities, to enable analysis of the impact of
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those activities against business and customer outcomes. This data can be leveraged
in cross-team retrospective analysis to identify opportunities and methods for
improvement.
OPS 9: 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.
Key AWS Services
The AWS service that is essential to Operational Excellence is AWS CloudFormation,
which you can use to create templates based on best practices. This enables you
to provision resources in an orderly and consistent fashion from your development
through production environments. The following services and features support the
three areas in operational excellence:
• Prepare: AWS Config and AWS Config rules can be used to create standards for
workloads and to determine if environments are compliant with those standards
before being put into production.
• Operate: Amazon CloudWatch allows you to monitor the operational health of a
workload.
• Evolve: Amazon Elasticsearch Service (Amazon ES) allows you to analyze your log
data to gain actionable insights quickly and securely.
Resources
Refer to the following resources to learn more about our best practices for
Operational Excellence.
Documentation
• DevOps and AWS
Whitepaper
• Operational Excellence Pillar
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Video
• DevOps at Amazon
Security
The Security pillar includes the ability to protect information, systems, and assets
while delivering business value through risk assessments and mitigation strategies.
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.
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 privilege management and reduce or even
eliminate reliance on long-term credentials.
• Enable traceability: Monitor, alert, and audit actions and changes to your
environment in real time. Integrate logs and metrics with systems to automatically
respond and take action.
• Apply security at all layers: Rather than just focusing on protection of a single
outer layer, apply a defense-in-depth approach with other security controls.
Apply to all layers (e.g., edge network, VPC, subnet, load balancer, every instance,
operating system, and application).
• 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: Create mechanisms and tools to reduce or eliminate
the need for direct access or manual processing of data. This reduces the risk of loss
or modification and human error when handling sensitive data.
• Prepare for security events: Prepare for an incident by having an incident
management process that aligns to your organizational requirements. Run incident
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response simulations and use tools with automation to increase your speed for
detection, investigation, and recovery.
Definition
There are five best practice areas for security in the cloud:
1. Identity and Access Management
2. Detective Controls
3. Infrastructure Protection
4. Data Protection
5. Incident Response
Before you architect any system, 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
Identity and Access Management
Identity and access management are key parts of an information security program,
ensuring that only authorized and authenticated users are able to access your
resources, and only in a manner that you intend. For example, you should define
principals (that is, users, groups, services, and roles that take action 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
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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. (For a list of
security questions, answers, and best practices, see the Appendix.)
SEC 1: How do you manage credentials and authentication?
Credentials and authentication mechanisms include passwords, tokens, and keys that grant
access directly or indirectly in your workload. Protect credentials with appropriate mechanisms
to help reduce the risk of accidental or malicious use.
SEC 2: How do you control human access?
Control human access by implementing controls inline with defined business requirements to
reduce risk and lower the impact of unauthorized access. This applies to privileged users and
administrators of your AWS account, and also applies to end users of your application
SEC 3: How do you control programmatic access?
Control programmatic or automated access with appropriately defined, limited, and segregated
access to help reduce the risk of unauthorized access. Programmatic access includes access that
is internal to your workload, and access to AWS related resources.
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.
Detective Controls
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
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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 questions focus 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.
SEC 5: How do you defend against emerging security threats?
Staying up to date with AWS and industry best practices and threat intelligence helps you
be aware of new risks. This enables you to create a threat model to identify, prioritize, and
implement appropriate controls to help protect your workload.
Log management is important to a well-architected design for reasons ranging from
security or forensics to regulatory or legal requirements. It is critical that you analyze
logs and respond to 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.
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SEC 6: How do you protect your networks?
Public and private networks require multiple layers of defense to help protect from external
and internal network-based threats.
SEC 7: 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 EC2 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.
• 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.
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• 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 8: How do you classify your data?
Classification provides a way to categorize data, based on levels of sensitivity, to help you
determine appropriate protective and retention controls.
SEC 9: How do you protect your data at rest?
Protect your data at rest by defining your requirements and implementing controls, including
encryption, to reduce the risk of unauthorized access or loss.
SEC 10: How do you protect your data in transit?
Protecting your data in transit by defining your requirements and implementing controls,
including encryption, reduces the risk of unauthorized access or exposure.
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.
SEC 11: How do you respond to an incident?
Preparation is critical to timely investigation and response to security incidents to help
minimize potential disruption to your organization.
Ensure that you have a way to quickly grant access for your InfoSec team, and
automate the isolation of instances as well as the capturing of data and state for
forensics.
Key AWS Services
The AWS service that is essential to Security is AWS Identity and Access
Management (IAM), which allows you to securely control access to AWS services and
resources for your users. The following services and features support the five areas in
security:
• Identity and Access Management: IAM enables you to securely control access to
AWS services and resources. MFA adds an additional layer of protection on user
access. AWS Organizations lets you centrally manage and enforce policies for
multiple AWS accounts.
• Detective Controls: AWS CloudTrail records AWS API calls, AWS Config provides a
detailed inventory of your AWS resources and configuration. Amazon GuardDuty
is a managed threat detection service that continuously monitors for malicious
or unauthorized behavior. Amazon CloudWatch is a monitoring service for AWS
resources which can trigger CloudWatch Events to automate security responses.
• Infrastructure Protection: Amazon Virtual Private Cloud (Amazon VPC) enables
you to launch AWS resources into a virtual network that you've defined. Amazon
CloudFront is a global content delivery network that securely delivers data,
videos, applications, and APIs to your viewers which integrates with AWS Shield
for DDoS mitigation. AWS WAF is a web application firewall that is deployed on
either Amazon CloudFront or Application Load Balancer to help protect your web
applications from common web exploits.
• Data Protection: Services such as ELB, Amazon Elastic Block Store (Amazon EBS),
Amazon S3, and Amazon Relational Database Service (Amazon RDS) include
encryption capabilities to protect your data in transit and at rest. Amazon Macie
automatically discovers, classifies and protects sensitive data, while AWS Key
Management Service (AWS KMS) makes it easy for you to create and control keys
used for encryption.
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• Incident Response: IAM should be used to grant appropriate authorization to
incident response teams and response tools. AWS CloudFormation can be used to
create a trusted environment or clean room for conducting investigations. Amazon
CloudWatch Events allows you to create rules that trigger automated responses
including AWS Lambda.
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 includes the ability of a system to recover from infrastructure or
service disruptions, dynamically acquire computing resources to meet demand, and
mitigate disruptions such as misconfigurations or transient network issues.
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.
Design Principles
There are five design principles for reliability in the cloud:
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• Test recovery procedures: In an on-premises environment, testing is often
conducted to prove the system works in a particular scenario. Testing is not
typically used to validate recovery strategies. In the cloud, you can test how
your system 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 exposes failure pathways that you can test and rectify before a real
failure scenario, reducing the risk of components failing that have not been tested
before.
• Automatically recover from failure: By monitoring a system for key performance
indicators (KPIs), you can trigger automation when a threshold is breached. 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.
• Scale horizontally to increase aggregate system availability: Replace one large
resource with multiple small resources to reduce the impact of a single failure on
the overall system. 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 systems is
resource saturation, when the demands placed on a system exceed the capacity of
that system (this is often the objective of denial of service attacks). In the cloud,
you can monitor demand and system utilization, and automate the addition or
removal of resources to maintain the optimal level to satisfy demand without over-
or under- provisioning.
• Manage change in automation: Changes to your infrastructure should be done
using automation. The changes that need to be managed are changes to the
automation.
Definition
There are three best practice areas for reliability in the cloud:
1. Foundations
2. Change Management
3. Failure Management
To achieve reliability, a system must have a well-planned foundation and monitoring
in place, with mechanisms for handling changes in demand or requirements. The
system should be designed to detect failure and automatically heal itself.
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Best Practices
Foundations
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. These requirements are sometimes neglected (because they are beyond
a single project’s scope). This neglect can have a significant impact on the ability
to deliver a reliable system. In an on-premises environment, these requirements
can cause long lead times due to dependencies and therefore must be incorporated
during initial planning.
With AWS, most of these foundational requirements are already incorporated or
may be addressed as needed. The cloud is designed to be essentially limitless, so it
is the responsibility of AWS to satisfy the requirement for sufficient networking and
compute capacity, while you are free to change resource size and allocation, such as
the size of storage devices, on demand.
The following questions focus on these considerations for reliability. (For a list of
reliability questions, answers, and best practices, see the Appendix.)
REL 1: How do you manage service limits?
Default service limits exist to prevent accidental provisioning of more resources than you need.
There are also limits on how often you can call API operations to protect services from abuse.
If you are using AWS Direct Connect, you have limits on the amount of data you can transfer
on each connection. If you are using AWS Marketplace applications, you need to understand
the limitations of the applications. If you are using third-party web services or software as a
service, you also need to be aware of the limits of those services.
REL 2: How do you manage your network topology?
Applications can exist in one or more environments: your existing data center infrastructure,
publicly accessible public cloud infrastructure, or private addressed public cloud infrastructure.
Network considerations such as intra- and inter-system connectivity, public IP address
management, private address management, and name resolution are fundamental to using
resources in the cloud.
AWS sets service limits (an upper limit on the number of each resource your team can
request) to protect you from accidentally over-provisioning resources. You will need
to have governance and processes in place to monitor and change these limits to
meet your business needs. As you adopt the cloud, you may need to plan integration
with existing on-premises resources (a hybrid approach). A hybrid model enables the
gradual transition to an all-in cloud approach over time. Therefore, it’s important to
have a design for how your AWS and on-premises resources will interact as a network
topology.
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Change Management
Being aware of how change affects a system allows you to plan proactively, and
monitoring allows you to quickly identify trends that could lead to capacity issues or
SLA breaches. In traditional environments, change-control processes are often manual
and must be carefully coordinated with auditing to effectively control who makes
changes and when they are made.
Using AWS, you can monitor the behavior of a system and automate the response to
KPIs, for example, by adding additional servers as a system gains more users. You can
control who has permission to make system changes and audit the history of these
changes.
The following questions focus on these considerations for reliability.
REL 3: How does your system adapt to changes in demand?
A scalable system provides elasticity to add and remove resources automatically so that they
closely match the current demand at any given point in time.
REL 4: How do you monitor your resources?
Logs and metrics are a powerful tool to gain insight into the health of your workloads. You can
configure your workload to monitor logs and metrics and send notifications when thresholds
are crossed or significant events occur. Ideally, when low-performance thresholds are crossed
or failures occur, the workload has been architected to automatically self-heal or scale in
response.
REL 5: How do you implement change?
Uncontrolled changes to your environment make it difficult to predict the effect of a change.
Controlled changes to provisioned resources and workloads are necessary to ensure that the
workloads and the operating environment are running known software and can be patched or
replaced in a predictable manner.
When you architect a system 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. It is
generally of interest to know how to become aware of these failures, respond to
them, and prevent them from happening again.
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
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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.
The following questions focus on these considerations for reliability.
REL 6: How do you back up data?
Back up data, applications, and operating environments (defined as operating systems
configured with applications) to meet requirements for mean time to recovery (MTTR) and
recovery point objectives (RPO).
REL 7: How does your system withstand component failures?
If your workloads have a requirement, implicit or explicit, for high availability and low mean
time to recovery (MTTR), architect your workloads for resilience and distribute your workloads
to withstand outages.
REL 8: How do you test resilience?
Test the resilience of your workload to help you find latent bugs that only surface in
production. Exercise these tests regularly.
REL 9: How do you plan for disaster recovery?
Disaster recovery (DR) is critical should restoration of data be required from backup methods.
Your definition of and execution on the objectives, resources, locations, and functions of this
data must align with RTO and RPO objectives.
Regularly back up your data and test your backup files to ensure you can recover
from both logical and physical errors. A key to managing failure is the frequent and
automated testing of systems 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 system changes. Actively track KPIs, such as the recovery time objective
(RTO) and recovery point objective (RPO), to assess a system’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 system-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.
Key AWS Services
The AWS service that is essential to Reliability is Amazon CloudWatch, which
monitors runtime metrics. The following services and features support the three areas
in reliability:
• Foundations: AWS IAM enables you to securely control access to AWS services
and resources. Amazon VPC lets you provision a private, isolated section of the
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AWS Cloud where you can launch AWS resources in a virtual network. AWS Trusted
Advisor provides visibility into service limits. AWS Shield is a managed Distributed
Denial of Service (DDoS) protection service that safeguards web applications
running on AWS.
• Change Management: AWS CloudTrail records AWS API calls for your account and
delivers log files to you for auditing. AWS Config provides a detailed inventory of
your AWS resources and configuration, and continuously records configuration
changes. Amazon Auto Scaling is a service that will provide an automated demand
management for a deployed workload. Amazon CloudWatch provides the ability to
alert on metrics, including custom metrics. Amazon CloudWatch also has a logging
feature that can be used to aggregate log files from your resources.
• Failure Management: AWS CloudFormation provides templates for the creation of
AWS resources and provisions them in an orderly and predictable fashion. Amazon
S3 provides a highly durable service to keep backups. Amazon Glacier provides
highly durable archives. AWS KMS provides a reliable key management system that
integrates with many AWS services.
Resources
Refer to the following resources to learn more about our best practices for Reliability.
Documentation
• Service Limits
• Service Limits Reports Blog
• Amazon Virtual Private Cloud
• AWS Shield
• Amazon CloudWatch
• Amazon S3
• AWS KMS
Whitepaper
• Reliability Pillar
• Backup Archive and Restore Approach Using AWS
• Managing your AWS Infrastructure at Scale
• AWS Disaster Recovery
• AWS Amazon VPC Connectivity Options
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Video
• How do I manage my AWS service limits?
• Embracing Failure: Fault-Injection and Service Reliability
Product
• AWS Premium Support
• Trusted Advisor
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.
Design Principles
There are five design principles for performance efficiency in the cloud:
• Democratize advanced technologies: Technologies that are difficult to implement
can become easier to consume by pushing that knowledge and complexity into
the cloud vendor's domain. Rather than having your IT team learn how to host
and run a new technology, they can simply consume it as a service. For example,
NoSQL databases, media transcoding, and machine learning are all technologies
that require expertise that is not evenly dispersed across the technical community.
In the cloud, these technologies become services that your team can consume
while focusing on product development rather than resource provisioning and
management.
• Go global in minutes: Easily deploy your system in multiple Regions around the
world with just a few clicks. This allows you to provide lower latency and a better
experience for your customers at minimal cost.
• Use serverless architectures: In the cloud, serverless architectures remove the need
for you to run and maintain servers to carry out traditional compute activities. For
example, storage services can act as static websites, removing the need for web
servers, and event services can host your code for you. This not only removes the
operational burden of managing these servers, but also can lower transactional
costs because these managed services operate at cloud scale.
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• Experiment more often: With virtual and automatable resources, you can quickly
carry out comparative testing using different types of instances, storage, or
configurations.
• Mechanical sympathy: Use the technology approach that aligns best to what you
are trying to achieve. For example, consider data access patterns when selecting
database or storage approaches.
Definition
There are four best practice areas for performance efficiency in the cloud:
1. Selection
2. Review
3. Monitoring
4. Tradeoffs
Take a data-driven approach to selecting 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. By reviewing your choices on a cyclical basis,
you will ensure that you are taking advantage of the continually evolving AWS
Cloud. Monitoring will ensure that you are aware of any deviance from expected
performance and can take action on it. Finally, your architecture can make tradeoffs
to improve performance, such as using compression or caching, or relaxing
consistency requirements.
Best Practices
Selection
The optimal solution for a particular system will vary based on the kind of workload
you have, often with multiple approaches combined. Well-architected systems use
multiple solutions and enable different features to improve performance.
In AWS, resources are virtualized and are available in a number of different types and
configurations. This makes it easier to find an approach that closely matches your
needs, and 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.
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The following questions focus on these considerations for performance efficiency.
(For a list of performance efficiency questions, answers, and best practices, see the
Appendix.)
PERF 1: How do you select the best performing architecture?
Often, multiple approaches are required to get optimal performance across a workload.
Well-architected systems use multiple solutions and enable different features to improve
performance.
When you select the patterns and implementation for your architecture use a data-
driven approach for the most optimal solution. AWS Solutions Architects, AWS
Reference Architectures, and AWS Partner Network (APN) Partners can help you
select an architecture based on what we have learned, 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 look at the four main resource types that
you should consider (compute, storage, database, and network).
Compute
The optimal compute solution for a particular system may vary based on application
design, usage patterns, and configuration settings. Architectures may 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.
In AWS, compute is available in three forms: instances, containers, and functions:
• Instances are virtualized servers and, therefore, you can change their capabilities
with the click of a button or an API call. Because in the cloud resource decisions
are no longer 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.
• 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.
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PERF 2: How do you select your compute solution?
The optimal compute solution for a system varies based on application design, usage patterns,
and configuration settings. Architectures may 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
The optimal storage solution for a particular system will vary based on the kind
of access method (block, file, or object), patterns of access (random or sequential),
throughput required, 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.
In AWS, storage is virtualized and is available in a number of different types. This
makes it easier to match your storage methods more closely with your needs, and also
offers storage options that are not easily achievable with on- premises infrastructure.
For example, Amazon S3 is designed for 11 nines of durability. You can also change
from using magnetic hard disk drives (HDDs) to SSDs, and easily move virtual drives
from one instance to another in seconds.
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 optimal database solution for a particular system can vary based on requirements
for availability, consistency, partition tolerance, latency, durability, scalability,
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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.
Amazon RDS provides a fully managed relational database. With Amazon RDS, you
can scale your database's compute and storage resources, often with no downtime.
Amazon DynamoDB is a fully managed NoSQL database that provides single-digit
millisecond latency at any scale. Amazon Redshift is a managed petabyte-scale
data warehouse that allows you to change the number or type of nodes as your
performance or capacity needs change.
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 sub-systems and enable different features
to improve performance. Selecting the wrong database solution and features for a system can
lead to lower performance efficiency.
Although a workload’s database approach (RDBMS, NoSQL) has significant impact on
performance efficiency, it is 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 a search
engine or data warehouse).
Network
The optimal network solution for a particular system will vary based on latency,
throughput requirements and so on. Physical constraints such as user or on-premises
resources will drive location options, which can be offset using edge techniques or
resource placement.
In AWS, networking is virtualized and is available in a number of different types and
configurations. This makes it easier to match your networking methods more closely
with your needs. AWS offers product features (for example, Enhanced Networking,
Amazon EBS-optimized instances, Amazon S3 transfer acceleration, dynamic Amazon
CloudFront) to optimize network traffic. AWS also offers networking features (for
example, Amazon Route 53 latency routing, Amazon VPC endpoints, and AWS Direct
Connect) to reduce network distance or jitter.
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PERF 5: How do you configure your networking solution?
The optimal network solution for a system varies based on latency, throughput requirements,
and so on. Physical constraints such as user or on-premises resources drive location options,
which can be offset using edge techniques or resource placement.
When selecting your network solution, you need to consider location. With AWS, you
can choose to place resources close to where they will be used to reduce distance.
By taking advantage of Regions, placement groups, and edge locations you can
significantly improve performance.
Review
When architecting solutions, there is a finite set of options that you can choose from.
However, over time new technologies and approaches become available that could
improve the performance of your architecture.
Using AWS, you can take advantage of our continual innovation, which is driven
by customer need. We release new Regions, edge locations, services, and features
regularly. Any of these 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.
Understanding where your architecture is performance-constrained will allow you to
look out for releases that could alleviate that constraint.
Monitoring
After you have implemented your architecture you will need to monitor its
performance so that you can remediate any issues before your customers are aware.
Monitoring metrics should be used to raise alarms when thresholds are breached.
The alarm can trigger automated action to work around any badly performing
components.
Amazon CloudWatch provides the ability to monitor and send notification alarms. You
can use automation to work around performance issues by triggering actions through
Amazon Kinesis, Amazon Simple Queue Service (Amazon SQS), and AWS Lambda.
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PERF 7: How do you monitor your resources to ensure they are performing as expected?
System performance can degrade over time. Monitor system performance to identify this
degradation and remediate internal or external factors, such as the operating system or
application load.
Ensuring that you do not see too many false positives, or are overwhelmed with data,
is key to having an effective monitoring solution. Automated triggers avoid human
error and can reduce the time to fix problems. Plan for game days where you can
conduct simulations in the production environment to test your alarm solution and
ensure that it correctly recognizes issues.
Tradeoffs
When you architect solutions, think about tradeoffs so you can select an optimal
approach. Depending on your situation you could trade consistency, durability, and
space versus 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 read-
only replicas to information stores such as database systems to reduce the load on
the primary database. AWS also offers caching solutions such as Amazon ElastiCache,
which provides an in-memory data store or cache, and Amazon CloudFront, which
caches copies of your static content closer to end users. Amazon DynamoDB
Accelerator (DAX) provides a read-through/write-through distributed caching tier in
front of Amazon DynamoDB, supporting the same API, but providing sub-millisecond
latency for entities that are in the cache.
PERF 8: How do you use tradeoffs to improve performance?
When architecting solutions, actively considering tradeoffs enables you to select an optimal
approach. Often you can improve performance by trading consistency, durability, and space for
time and latency.
Tradeoffs can increase the complexity of your architecture and require load testing to
ensure that a measurable benefit is obtained.
Key AWS Services
The AWS service that is essential to Performance Efficiency is Amazon CloudWatch,
which monitors your resources and systems, providing visibility into your overall
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performance and operational health. The following services and features support the
four areas in performance efficiency:
• Selection
• Compute: Auto Scaling is key to ensuring that you have enough instances to
meet demand and maintain responsiveness.
• Storage: Amazon EBS provides a wide range of storage options (such as SSD
and provisioned input/output operations per second (PIOPS)) that allow you to
optimize for your use case. Amazon S3 provides serverless content delivery, and
Amazon S3 transfer acceleration enables fast, easy, and secure transfers of files
over long distances.
• Database: Amazon RDS provides a wide range of database features (such as
PIOPS and read replicas) that allow you to optimize for your use case. Amazon
DynamoDB provides single-digit millisecond latency at any scale.
• Network: Amazon Route 53 provides latency-based routing. Amazon VPC
endpoints and AWS Direct Connect can reduce network distance or jitter.
• Review: The AWS Blog and the What's New section on the AWS website are
resources for learning about newly launched features and services.
• Monitoring: Amazon CloudWatch provides metrics, alarms, and notifications that
you can integrate with your existing monitoring solution, and that you can use with
AWS Lambda to trigger actions.
• Tradeoffs: Amazon ElastiCache, Amazon CloudFront, and AWS Snowball are
services that allow you to improve performance. Read replicas in Amazon RDS can
allow you to scale read-heavy workloads.
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
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• AWS re:Invent 2016: Scaling Up to Your First 10 Million Users (ARC201)
• AWS re:Invent 2017: Deep Dive on Amazon EC2 Instances
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.
Design Principles
There are five design principles for cost optimization in the cloud:
• 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 data center operations: AWS does the heavy lifting of
racking, stacking, and powering servers, so you can focus on your customers and
organization 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.
• Use managed and application level services to reduce cost of ownership: In the
cloud, managed and application level services remove the operational burden of
maintaining servers for tasks such as sending email or managing databases. As
managed services operate at cloud scale, they can offer a lower cost per transaction
or service.
Definition
There are four best practice areas for cost optimization in the cloud:
33

1. Expenditure Awareness
2. Cost-Effective Resources
3. Matching supply and demand
4. Optimizing Over Time
As with the other pillars, there are tradeoffs to consider. For example, do you want
to prioritize for speed to market or for cost? In some cases, it’s best to prioritize for
speed—going to market quickly, shipping new features, or simply meeting a deadline
—rather than investing in upfront cost optimization. Design decisions are sometimes
guided by haste as opposed to empirical data, as the temptation always exists to
overcompensate “just in case” rather than spend time benchmarking for the most
cost-optimal workload over time. This often leads to drastically over-provisioned
and under-optimized deployments, which remain static throughout their life cycle.
The following sections provide techniques and strategic guidance for the initial and
ongoing cost optimization of your deployment.
Best Practices
Expenditure 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 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 can use Cost Explorer to track your spend, and gain insights into exactly
where you spend. Using AWS Budgets, you can send notifications if your usage
or costs are not inline with your forecasts. You can use tagging on resources to
apply business and organization information to your usage and cost; this provides
additional insights to optimization from an organization perspective.
34

The following questions focus on these considerations for cost optimization. (For a list
of cost optimization questions, answers, and best practices, see the Appendix.)
COST 1: 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 2: 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 3: 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.
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, and the AWS Simple Monthly Calculator
allows you to calculate your data transfer costs.
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.
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 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. Reserved Instances allow you to reserve capacity and offer savings of up
to 75% off On-Demand pricing. With Spot Instances, you can leverage unused
35

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 4: 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 5: How do you meet cost targets when you select resource type and size?
Ensure that you choose the appropriate resource size for the task at hand. By selecting the
most cost effective type and size, you minimize waste.
COST 6: How do you use pricing models to reduce cost?
Use the pricing model that is most appropriate for your resources to minimize expense.
COST 7: 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.
Matching supply and demand
Optimally matching supply to demand delivers the lowest cost for a workload, but
there also needs to be sufficient extra supply to allow for provisioning time and
individual resource failures. Demand can be fixed or variable, requiring metrics and
automation to ensure that management does not become a significant cost.
In AWS, you can automatically provision resources to match demand. Auto Scaling
and demand, buffer, and 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.
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COST 8: How do you match supply of resources with demand?
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 match supply against demand, actively think about the patterns of
usage and the time it takes to provision new resources.
Optimizing Over Time
As AWS releases new services and features, it is 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.
Managed services from AWS can significantly optimize the workload, so it is essential
to be aware of new managed services and features as they become available. For
example, running an Amazon RDS database can be cheaper than running your own
database on Amazon EC2.
COST 9: How do you evaluate new services?
architectural 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
Key AWS Services
The tool that is essential to Cost Optimization is Cost Explorer, which helps you
gain visibility and insights into your usage, across your workloads and throughout
your organization. The following services and features support the four areas in cost
optimization:
• Expenditure Awareness: AWS Cost Explorer allows you to view and track your
usage in detail. AWS Budgets notify you if your usage or spend exceeds actual or
forecast budgeted amounts.
• Cost-Effective Resources: You can use Cost Explorer for Reserved Instance
recommendations, and see patterns in how much you spend on AWS resources
37

over time. Use Amazon CloudWatch and Trusted Advisor to help right size your
resources. You can use Amazon Aurora on RDS to remove database licensing costs.
AWS Direct Connect and Amazon CloudFront can be used to optimize data transfer.
• Matching supply and demand: Auto Scaling allows you to add or remove resources
to match demand without overspending.
• Optimizing Over Time: The AWS News Blog and the What's New section on the
AWS website are resources for learning about newly launched features and services.
AWS Trusted Advisor inspects your AWS environment and ﬁnds opportunities to
save you money by eliminating unused or idle resources or committing to Reserved
Instance capacity.
Resources
Refer to the following resources to learn more about our best practices for Cost
Optimization.
Documentation
• Analyzing Your Costs with Cost Explorer
• AWS Cloud Economics Center
• AWS Detailed Billing Reports
Whitepaper
• Cost Optimization Pillar
Video
• Cost Optimization on AWS
Tool
• AWS Total Cost of Ownership (TCO) Calculators
• AWS Simple Monthly Calculator
38

The Review Process
The review of architectures needs to be done in a consistent manner, with a blame-
free 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.
AWS Well-Architected 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
1
that are difficult to change, and then before
the go live date. Post go live 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 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:
1
Many decisions are reversible, two-way doors. Those decisions can use a light-weight process. One-way
doors are hard or impossible to reverse and require more inspection before making them.
39

• 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.)
• 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 propriety
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.
40

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.
41

Contributors
The following individuals and organizations contributed to this document:
• Philip Fitzsimons: Sr. Manager Well-Architected, Amazon Web Services
• Brian Carlson: Operations Lead Well-Architected, Amazon Web Services
• Ben Potter: Security Lead Well-Architected, Amazon Web Services
• Rodney Lester: Reliability Lead Well-Architected, Amazon Web Services
• John Ewart: Performance 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
42

Further Reading
AWS Disaster Recovery
AWS KMS
AWS Security Best Practices
AWS re:Invent 2016: Scaling Up to Your First 10 Million Users (ARC201)
AWS re:Invent 2017: Deep Dive on Amazon EC2 Instances
AWS Amazon VPC Connectivity Options
AWS Cloud Economics Center
AWS Cloud Security
AWS Compliance
AWS Detailed Billing Reports
AWS Limit Monitor
AWS Premium Support
AWS Risk and Compliance
AWS Security Blog
AWS Security Overview
AWS Security State of the Union
AWS Shield
AWS Simple Monthly Calculator
AWS Total Cost of Ownership (TCO) Calculators
AWS Well-Architected homepage
Amazon S3
Amazon CloudWatch
Amazon EBS Volume Performance
Amazon S3 Performance Optimization
Amazon Virtual Private Cloud
Amazon leadership principles
Analyzing Your Costs with Cost Explorer
Backup Archive and Restore Approach Using AWS
43

Cost Optimization on AWS
Cost Optimization Pillar whitepaper
DevOps and AWS
DevOps at Amazon
Embracing Failure: Fault-Injection and Service Reliability
How do I manage my AWS service limits?
Managing your AWS Infrastructure at Scale
Operational Excellence Pillar whitepaper
Performance Eﬃciency Pillar whitepaper
Reliability Pillar whitepaper
Security Pillar whitepaper
Service Limits
Service Limits Reports Blog
Shared Responsibility Overview
TOGAF
Trusted Advisor
Zachman Framework
44

Document Revisions
Major revisions:
Date Description
November 2018 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.
June 2018 Updates to simplify question text, standardize answers,
and improve readability.
November 2017 Operational Excellence moved to front of pillars and
rewritten so it frames other pillars. Refreshed other
pillars to reﬂect evolution of AWS.
November 2016 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 2015 Updated the Appendix with current Amazon
CloudWatch Logs information.
October 2015 Original publication.
45

Appendix: Questions, Answers, and Best
Practices
Operational Excellence
Prepare
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 operations efforts on
external customer needs. This will ensure that you have a thorough understanding of the
operations support that is required to achieve business outcomes.
• Evaluate internal customer needs: Involve key stakeholders, including business,
development, and operations teams, when determining where to focus operations 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 compliance requirements: Evaluate external factors, such as regulatory
compliance requirements and industry standards, to ensure that you are aware of
guidelines or obligations that 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), so that you
can include their impact when determining where to focus operations efforts.
• Evaluate tradeoffs: Evaluate the impact of tradeoffs between competing interests, to
help make informed decisions when determining where to focus operations efforts. For
example, accelerating speed to market for new features may be emphasized over cost
optimization.
• Manage benefits and risks: Manage benefits and risks to make informed decisions when
determining where to focus operations efforts. For example, it may be beneficial to deploy
a system with unresolved issues so that significant new features can be made available to
customers.
46

OPS 2 How do you design your workload so that you can understand its state?
Design your workload so that it provides the information necessary for you to understand its
internal state (for example, metrics, logs, and traces) across all components. This enables you
to provide effective responses when appropriate.
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
• 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 of resources it depends on. Examples of these are external
databases, DNS, and network connectivity. Use this information to determine when a
• 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 in
identifying the root cause of issues.
47

OPS 3 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 deployed, and enable rapid identification and remediation of issues introduced
through deployment 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 to gain confidence your workload will
operate as intended.
• 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.
• 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.
48

OPS 4 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 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.
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OPS 5 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 an 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. Review must include at a minimum
the operational readiness of the teams and the workload, and security considerations.
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.
• 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. Implment 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 identify issues: Playbooks are documented processes to investigate
issues. Enable consistent and prompt responses to failure scenarios by documenting
investigation processes in playbooks. Implement playbooks as code and trigger playbook
execution in response to events where appropriate, to ensure consistency, speed
responses, and reduce errors caused by manual processes.
• 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.
50

Operate
OPS 6 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 and customer outcomes. Evaluate KPIs to determine workload success.
• Define workload metrics: Define workload metrics to measure the achievement of KPIs.
Define workload metrics to measure the health of the workload. 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.
• Learn expected patterns of activity for workload: Establish patterns of workload activity
to determine when behavior is outside of the expected values 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 required.
• Alert when workload anomalies are detected: Raise an alert when workload anomalies
are detected so that you can respond appropriately if required.
• 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.
51

OPS 7 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 and customer outcomes. Evaluate KPIs to determine operations success.
• Define operations metrics: Define operations metrics to measure the achievement of KPIs.
Define operations metrics to measure the health of the operations. Evaluate metrics to
determine if the operations are achieving desired outcomes, and to understand operations
health.
• 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 processes.
• Learn the expected patterns of activity for operations: Establish baselines for metrics to
provide expected values as the basis for comparison.
• Alert when operations outcomes are at risk: Raise an alert when operations outcomes are
at risk so that you can respond appropriately if required.
• Alert when operations anomalies are detected: Raise an alert when operations anomalies
are detected so that you can respond appropriately if required.
• 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.
52

OPS 8 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.
• Use a process for root cause analysis: Have a process to identify and document the root
cause of an event so that you can develop mitigations to limit or prevent recurrence and
you can develop procedures for prompt and effective responses. Communicate root cause
as appropriate, tailored to target audiences.
• 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.
• Enable push notifications: Communicate directly with your users (for example, with email
or SMS) when the services they use are impacted, and 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.
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Evolve
OPS 9 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.
• Implement feedback loops: Include feedback loops in your procedures and workloads to
help you identify issues and areas that need improvement.
• 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.
54

Security
Identity and Access Management
SEC 1 How do you manage credentials and authentication?
Credentials and authentication mechanisms include passwords, tokens, and keys that grant
access directly or indirectly in your workload. Protect credentials with appropriate mechanisms
to help reduce the risk of accidental or malicious use.
Best practices:
• Define identity and access management requirements: Identity and access management
configurations need to be defined to meet your organizational, legal, and compliance
requirements.
• Secure AWS root user: Secure the AWS root user with MFA, no access keys, and limit its
use to help secure your AWS account.
• Enforce use of multi-factor authentication: Enforce multi-factor authentication (MFA)
with software or hardware mechanisms to provide additional access control.
• Automate enforcement of access controls: Enforce access controls through automated
tools and by reporting irregularities. This helps you maintain your credential management
requirements.
• Integrate with centralized federation provider: Integrate with a federated identity
provider or directory service to authenticate all users in a centralized place. This reduces
the requirement for multiple credentials and reduces management complexity.
• Enforce password requirements: Enforce policies for minimum length, complexity, and
reuse of passwords to help protect against brute force and other password attacks.
• Rotate credentials regularly: Rotate credentials regularly to help reduce the risk of old
credentials being used by unauthorized systems or users.
• Audit credentials periodically: Audit credentials to ensure the defined controls (for
example, MFA) are enforced, rotated regularly, and have appropriate access level.
55

SEC 2 How do you control human access?
Control human access by implementing controls inline with defined business requirements to
reduce risk and lower the impact of unauthorized access. This applies to privileged users and
administrators of your AWS account, and also applies to end users of your application
Best practices:
• Define human access requirements: Clearly define access requirements for users based on
job function to reduce the risks from unnecessary privileges.
• Grant least privileges: Grant users only the minimum privileges you have defined to
reduce the risk of unauthorized access.
• Allocate unique credentials for each individual: Credentials are not shared between any
users to help segregation of users and traceability.
• Manage credentials based on user lifecycles: Integrate access management with user
lifecycle. For example, decommission a user to revoke unused and unnecessary credentials
when a user leaves or changes roles.
• Automate credential management: Automate credential management to enforce
minimum privileges and disable unused credentials. Automate auditing, reporting, and
management of the lifecycle of users.
• Grant access through roles or federation: Use IAM roles instead of IAM users or static
access keys to allow for secure cross-account access and federated users.
SEC 3 How do you control programmatic access?
Control programmatic or automated access with appropriately defined, limited, and segregated
access to help reduce the risk of unauthorized access. Programmatic access includes access that
is internal to your workload, and access to AWS related resources.
Best practices:
• Define programmatic access requirements: Clearly define access requirements for
automated or programmatic access to reduce the risks from unnecessary privileges.
• Grant least privileges: Grant automated or programmatic access only the minimum
privileges you have defined to reduce the risk of unauthorized access.
• Automate credential management: Automate credential management to enforce
minimum privileges and disable unused credentials. Automate auditing, reporting, and
management of dynamic authentication.
• Allocate unique credentials for each component: Credentials are not shared between any
component to help segregation and traceability. For example, use different IAM roles for
AWS Lambda functions and EC2 instances.
• Grant access through roles or federation: Use IAM roles or federation instead of IAM users
or static access keys to allow for secure programmatic access.
• Implement dynamic authentication: Credentials are dynamically acquired and frequently
rotated by a service or system.
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Detective Controls
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:
• Define requirements for logs: Define requirements for retention and access control for
logs to meet your organizational, legal, and compliance requirements.
• Define requirements for metrics: Collecting metrics and defining baselines allows you to
gain insights to potential security threats.
• Define requirements for alerts: Define who should receive alerts and what they should do
with the alerts they receive.
• Configure service and application logging: Configure logging throughout the workload,
including application logs, AWS services logs, and resource logs.
• Analyze logs centrally: All logs should be collected centrally and automatically analyzed
to detect anomalies and indicators of malicious activity or compromise.
• Automate alerting on key indicators: Key indicators, including metrics and events related
to security, should be monitored and trigger automated alerts based on thresholds.
• Develop investigation processes: Develop processes to investigate different types of
events, including escalation paths for incident response processes.
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SEC 5 How do you defend against emerging security threats?
Staying up to date with AWS and industry best practices and threat intelligence helps you
be aware of new risks. This enables you to create a threat model to identify, prioritize, and
implement appropriate controls to help protect your workload.
Best practices:
• Keep up to date with organizational, legal, and compliance requirements: Stay up to
date with organizational, legal, and compliance requirements that enable you to adjust
your security posture to comply.
• Keep up to date with security best practices: Stay up to date with both AWS and industry
security best practices to evolve protection of the workload.
• Keep up to date with security threats: Understand attack vectors by staying up to date
with the latest security threats. This helps you implement detective and preventive
controls.
• Evaluate new security services and features regularly: Evaluate security services from
both AWS and APN Partners, including new features to limit risk of threats.
• Deﬁne 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 adjust your
security posture to respond.
• Implement new security services and features: Adopt security services and features to
implement controls that help protect your workload.
58

Infrastructure Protection
SEC 6 How do you protect your networks?
Public and private networks require multiple layers of defense to help protect from external
and internal network-based threats.
Best practices:
• Define network protection requirements: Define controls for protection of your networks
to meet your organizational, legal, and compliance requirements.
• Limit exposure: Limit the exposure of the workload to the internet and internal networks
by only allowing minimum required access.
• Automate configuration management: Enforce and validate secure configurations
automatically by using a configuration management service or tool to reduce human error.
• Automate network protection: Automate protection mechanisms to provide a self
defending network based on threat intelligence and anomaly detection.
• Implement inspection and protection: Inspect and filter your traffic at the application
level; for example, by using a web application firewall, to help protect against threats.
• Control traffic at all layers: Apply controls for controlling both ingress and egress traffic,
including data loss prevention. For Amazon Virtual Private Cloud (VPC) this includes
security groups, Network ACLs, and subnets. For AWS Lambda, consider running in your
private VPC to control traffic.
SEC 7 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:
• Define compute protection requirements: Define the protection controls for your
compute resources to meet your organizational, legal, and compliance requirements.
• Scan for and patch vulnerabilities: Frequently scan for and patch vulnerabilities in your
code base and in your infrastructure to help protect against new threats.
• Automate configuration management: Enforce and validate secure configurations
automatically by using a configuration management service or tool to reduce human error.
• Automate compute protection: Automate defense with intrusion prevention, including
the ability to protect against unknown threats; for example, use virtual patching.
• Reduce attack surface: Reduce the attack surface, including hardening EC2 operating
systems and configuring container and serverless resources, to help limit exposure.
• Implement managed services: Implement services that manage resources, such as
Amazon RDS, AWS Lambda, and Amazon ECS, to reduce security maintenance tasks.
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Data Protection
SEC 8 How do you classify your data?
Classification provides a way to categorize data, based on levels of sensitivity, to help you
determine appropriate protective and retention controls.
Best practices:
• Define data classification requirements: Define data classification requirements to meet
your organizational, legal, and compliance requirements.
• Define data protection controls: Protect data according to its classification level; for
example, secure publicly accessible data by using best practices while protecting sensitive
data with additional controls.
• Implement data identification: Classify data with easily identifiable indicators; for
example, use tags for Amazon S3 buckets and objects that classify the data in the buckets.
• Automate identification and classification: Automate identification and classification of
data to reduce the risk of human error.
• Identify the types of data: Be aware of the types of data in your workload to help you
implement controls to meet organizational, legal, and compliance requirements.
SEC 9 How do you protect your data at rest?
Protect your data at rest by defining your requirements and implementing controls, including
encryption, to reduce the risk of unauthorized access or loss.
Best practices:
• Define data management and protection at rest requirements: Define data management
and protection at rest requirements, such as encryption and data retention, to meet your
organizational, legal, and compliance requirements.
• Implement secure key management: Encryption keys must be stored securely, and
rotated with strict access control; for example, by using a key management service such as
AWS Key Management Service. Consider using different keys for segregation of different
data classification levels and retention requirements.
• Enforce encryption at rest: Enforce your defined encryption requirements based on the
latest standards and best practices to help protect your data at rest.
• 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.
• Provide mechanisms to keep people away from data: Keep all users away from directly
accessing sensitive data. For example, provide a dashboard instead of direct access to a
data store, and provide tools to indirectly manage the data.
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SEC 10 How do you protect your data in transit?
Protecting your data in transit by defining your requirements and implementing controls,
including encryption, reduces the risk of unauthorized access or exposure.
Best practices:
• Define data protection in transit requirements: Define data protection in transit
requirements, such as encryption standards, based on data classification to meet your
organizational, legal, and compliance requirements. Best practices are to encrypt and
authenticate all traffic, and to enforce the latest standards and ciphers.
• Implement secure key and certificate management: Store encryption keys and
certificates securely and rotate them with strict access control; for example, by using a
certificate management service such as AWS Certificate Manager.
• Enforce encryption in transit: Enforce your defined encryption requirements based on
the latest standards and best practices to help you meet your organizational, legal, and
compliance requirements.
• Automate detection of data leak: Use a tool or detection mechanism to automatically
detect attempts to move data outside of defined boundaries; for example, to detect a
database system that is copying data to an unknown host.
• Authenticate network communications: Verify the identity of communications by using
protocols, such as Transport Layer Security (TLS) or IPsec, to reduce the risk of data
tampering or loss.
61

Incident Response
SEC 11 How do you respond to an incident?
Preparation is critical to timely investigation and response to security incidents to help
minimize potential disruption to your organization.
Best practices:
• Identify key personnel and external resources: Identify internal and external personnel
and resources that would help your organization respond to an incident.
• Identify tooling: Identify tooling that would help your organization respond to an
incident.
• Develop incident response plans: Create incident response plans, starting with the most
likely scenarios for your workload and organization. Include how you would communicate
and escalate both internally and externally.
• Automate containment capability: Automate containment of an incident to reduce
response times and organizational impact.
• Identify forensic capabilities: Identify the forensic investigation capabilities that are
available, including external specialists.
• Pre-provision access: Ensure that security personnel have the correct access pre-
provisioned into AWS so that an appropriate response can be made to an incident.
• Pre-deploy tools: Ensure that security personnel have the right tools pre-deployed into
AWS so that an appropriate response can be made to an incident.
• Run game days: Practice incident response game days (simulations) regularly, incorporate
lessons learned into plans, and continuously improve responses and plans.
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Reliability
Foundations
REL 1 How do you manage service limits?
Default service limits exist to prevent accidental provisioning of more resources than you need.
There are also limits on how often you can call API operations to protect services from abuse.
If you are using AWS Direct Connect, you have limits on the amount of data you can transfer
on each connection. If you are using AWS Marketplace applications, you need to understand
the limitations of the applications. If you are using third-party web services or software as a
service, you also need to be aware of the limits of those services.
Best practices:
• Aware of limits but not tracking them: You are aware there are limits, but are not tracking
your current limits.
• Monitor and manage limits: Evaluate your potential usage, increase your regional limits
appropriately, and allow planned growth in usage.
• Use automated monitoring and management of limits: Implement tools to alert you
when thresholds are being approached. As part of AWS Enterprise Support, you can also
automate the limit increase request.
• Accommodate ﬁxed service limits through architecture: Be aware of unchangeable
service limits and architect around these.
• Ensure a suﬃcient gap between the current service limit and the maximum usage to
accommodate failover: When a resource fails it may still be counted against limits until
it is successfully terminated. Ensure your limits 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.
• Manage service limits across all relevant accounts and regions: If you are using multiple
AWS accounts or AWS Regions, ensure you request the same limits in all environments in
which you run your production workloads.
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REL 2 How do you manage your network topology?
Applications can exist in one or more environments: your existing data center infrastructure,
publicly accessible public cloud infrastructure, or private addressed public cloud infrastructure.
Network considerations such as intra- and inter-system connectivity, public IP address
management, private address management, and name resolution are fundamental to using
resources in the cloud.
Best practices:
• Use highly available connectivity between private addresses in public clouds and on-
premises environment: Use multiple AWS Direct Connect (DX) circuits and multiple VPN
tunnels between separately deployed private IP address spaces. Use multiple DX locations
for high availability. If you use multiple AWS Regions, you will also need multiple DX
locations in at least 2 regions. You may 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.
• Use highly available network connectivity for the users of the workload: Use a highly
available DNS, CloudFront, API Gateway, load balancing, and reverse proxy as the
public facing endpoint of your application. You may want to evaluate AWS Marketplace
appliances for load balancing or proxying.
• Enforce non-overlapping private IP address ranges in multiple private address spaces
where they are connected: The IP ranges of each of your VPCs must not conﬂict if they
are peered or connected via VPN. The same is true for private connectivity to your on-
premises environments and other cloud providers. You must have a way to allocate private
IP ranges when needed.
• Ensure IP subnet allocation accounts for expansion and availability: Individual
Amazon VPC IP address ranges must be large enough to accommodate an application's
requirements, including factoring in future expansion and allocation of IP addresses to
subnets across Availability Zones. This includes load balancers, AWS Lambda functions,
EC2 instances, and container-based applications. Additionally, keep some IP addresses
available for possible future expansion.
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Change Management
REL 3 How does your system adapt to changes in demand?
A scalable system provides elasticity to add and remove resources automatically so that they
closely match the current demand at any given point in time.
Best practices:
• Procure resources upon detection of lack of service within a workload: Scaling of
resources is performed manually when availability is impacted.
• Procure resources manually upon detection that more resources may be needed soon
for a workload: Manually scale compute and storage as need is anticipated.
• Procure resources automatically when scaling a workload up or down: Use services that
automatically scale, such as Amazon S3, Amazon CloudFront, Amazon Auto Scaling, and
AWS Lambda. You can also use third-party tools and AWS SDKs to automate scaling.
• Load test the workload: Adopt a load testing methodology to measure if scaling activity
will meet workload requirements.
REL 4 How do you monitor your resources?
Logs and metrics are a powerful tool to gain insight into the health of your workloads. You can
configure your workload to monitor logs and metrics and send notifications when thresholds
are crossed or significant events occur. Ideally, when low-performance thresholds are crossed
or failures occur, the workload has been architected to automatically self-heal or scale in
response.
Best practices:
• Monitor the workload in all tiers: Monitor the tiers of the workload with Amazon
CloudWatch or third-party tools. Monitor AWS services with Personal Health Dashboard.
• Send notifications based on the monitoring: Organizations that need to know receive
notifications when significant events occur.
• Perform automated responses on events: Use automation to take action when an event is
detected; for example, to replace failed components.
• Conduct reviews regularly: Frequently review the monitoring of the workload based on
significant events and changes to evaluate the architecture and implementation.
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REL 5 How do you implement change?
Uncontrolled changes to your environment make it difficult to predict the effect of a change.
Controlled changes to provisioned resources and workloads are necessary to ensure that the
workloads and the operating environment are running known software and can be patched or
replaced in a predictable manner.
Best practices:
• Deploy changes in a planned manner: Deployments and patching follow a documented
process.
• Deploy changes with automation: Deployments and patching are automated.
Failure Management
REL 6 How do you back up data?
Back up data, applications, and operating environments (defined as operating systems
configured with applications) to meet requirements for mean time to recovery (MTTR) and
recovery point objectives (RPO).
Best practices:
• Identify all data that needs to be backed up and are perform backups or reproduce the
data from sources: Back up important data using Amazon S3, Amazon EBS snapshots, or
third-party software. Alternatively, if the data can be reproduced from sources to meet
RPO, you may not require a backup.
• Perform data backup automatically or reproduce the data from sources automatically:
Automate backups or the reproduction from sources using AWS features (for example,
snapshots of Amazon RDS and Amazon EBS, versions on Amazon S3, etc.), AWS
Marketplace solutions, or third-party solutions.
• Perform periodic recovery of the data to verify backup integrity and processes: Validate
that your backup process implementation meets Recovery Time Objective and Recovery
Point Objective through a recovery test.
• Secure and encrypt backups or ensure the data is available from a secure source for
reproduction: Detect access via authentication and authorization like AWS IAM, and detect
data integrity compromise by using encryption.
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REL 7 How does your system withstand component failures?
If your workloads have a requirement, implicit or explicit, for high availability and low mean
time to recovery (MTTR), architect your workloads for resilience and distribute your workloads
to withstand outages.
Best practices:
• Monitor all layers of the workload to detect failures: Continuously monitor the health of
your system and report degradation as well as complete failure.
• Implement loosely coupled dependencies: Dependencies such as queuing systems,
streaming systems, workflows, and load balancers are loosely coupled.
• Implement graceful degradation to transform applicable hard dependencies into soft
dependencies: When a component's dependencies are unhealthy, the component itself
does not report as unhealthy. It can continue to serve requests in a degraded manner.
• Automating complete recovery because technology constraints exist in parts or all of
the workload requiring a single location: Elements of the workload can only run in one
Availability Zone or one data center, requiring you to implement a complete rebuild of the
workload with defined recovery objectives.
• Deploy the workload to multiple locations: Distribute workload load across multiple
Availability Zones and AWS Regions (for example, DNS, ELB, Application Load Balancer,
and API Gateway). These locations can be as diverse as needed.
• Automate healing on all layers: Use automated capabilities upon detection of failure to
perform an action to remediate.
• Send notifications upon availability impacting events: Notifications are sent upon
detection of significant events, even if the issue was automatically healed.
REL 8 How do you test resilience?
Test the resilience of your workload to help you find latent bugs that only surface in
production. Exercise these tests regularly.
Best practices:
• Use playbooks for unanticipated failures: You have playbooks for failure scenarios that
have not been anticipated to identify root causes and assist in strategies for prevention or
mitigation.
• Conduct root cause analysis (RCA) and share results: Review system failures based on
significant events to evaluate the architecture and identify the root cause. Have a method
to communicate these causes to others as needed.
• Inject failures to test resiliency: Test failures regularly, ensuring coverage of failure
pathways.
• Conduct game days regularly: Use game days to regularly exercise your failure procedures
with the people who will be involved in actual failure scenarios.
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REL 9 How do you plan for disaster recovery?
Disaster recovery (DR) is critical should restoration of data be required from backup methods.
Your definition of and execution on the objectives, resources, locations, and functions of this
data must align with RTO and RPO objectives.
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.
• Test disaster recovery implementation to validate the implementation: Regularly test
failover to DR to ensure that RTO and RPO are met.
• Manage configuration drift on all changes: Ensure that AMIs and the system
configuration state are up-to-date at the DR site or region, as well as the limits on AWS
services.
• Automate recovery: Use AWS or third-party tools to automate system recovery.
68

Performance Efficiency
Selection
PERF 1 How do you select the best performing architecture?
Often, multiple approaches are required to get optimal performance across a workload.
Well-architected systems use multiple solutions and enable different features to improve
performance.
Best practices:
• Understand the available services and resources: Learn about and understand the wide
range of services and resources available to you on AWS. Identify which services and
configuration options are relevant to your workload and understand how to use them to
achieve optimal performance.
• Define a process for architectural choices: Use existing internal experience and
knowledge of AWS, or use external resources, such as published use cases, relevant
documentation, or whitepapers to define a process to choose resources and services. For
example, a process that encourages experimentation and benchmarking different services
as they might be used in your workload.
• Factor cost or budget into decisions: Workloads often have budgets that they need to
operate within, and the budget is a critical part of efficient operation. Use internal cost
controls and consider budget when selecting resource types and sizes based on predicted
resource needs.
• Use policies or reference architectures: Use internal policies or existing reference
architectures to make the best architectural choices for your workload. Evaluate which
services and configuration are best for your workload to maximize performance and
efficiency.
• Use guidance from AWS or an APN Partner: Use AWS resources, such as Solutions
Architects, or an APN Partner to guide your decisions. These resources can help review and
suggest improvements to your architecture to achieve an optimal level of performance.
• Benchmark existing workloads: Benchmark the performance of an existing workload to
understand how it performs on AWS. Use the data collected from these benchmarks to
drive architectural decisions.
• Load test your workload: Deploy the latest version of your system on AWS using different
resource types and sizes, and use monitoring to capture performance metrics that identify
bottlenecks or excess capacity. Use this information when designing or improving your
architecture and resource selection based on how it performs.
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PERF 2 How do you select your compute solution?
The optimal compute solution for a system varies based on application design, usage patterns,
and configuration settings. Architectures may 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.
Best practices:
• Evaluate the available compute options: Look at and 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, single versus multi-tenancy, and so on.
• Collect compute-related metrics: One of the best ways to understand how your systems
are performing is to record and track the true utilization of various resources. This data can
then be fed back into making more accurate determinations of 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 when choosing 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, while a bursting workload may benefit more from an
elastic container system such as Amazon Elastic Container Service.
• Use the available elasticity of resources: AWS provides the flexibility to expand or reduce
your resources dynamically through a variety of mechanisms (for example: AWS Auto
Scaling, Amazon Elastic Container Service, and AWS Lambda) to meet changes in demand.
Combined with compute-related metrics, a workload can automatically respond to these
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 may be observed to be more memory-intensive than initially thought, so moving
to a different instance family or size may improve both performance and efficiency.
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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 Amazon S3, Amazon EBS, Amazon Elastic File System (Amazon
EFS), and Amazon EC2 instance store.
• Evaluate available configuration options: Evaluate the various characteristics and
configuration options and how they relate to storage. Understand where and how to use
PIOPS, SSDs, magnetic storage, Amazon S3, Amazon Glacier, or ephemeral storage to
optimize storage space and performance for your workload.
• Make decisions based on access patterns and metrics: Choose storage systems and
configure them by considering how the workload accesses data. Make performance
improvements, such as choosing caching services or instances that best match your
access patterns, utilizing optimal key distributions when storing data in Amazon S3 or
DynamoDB, striping storage volumes, or partitioning data based on system measurements.
Increase storage efficiency by choosing object storage, such as Amazon S3, or block
storage, such as Amazon Elastic Block Store. Configure the storage options you choose to
match your data access patterns.
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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 sub-systems 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,
what its performance demands are, and so on. Use this data to select the best performing
database approach for your workload (for example, relational databases, NoSQL, data
warehouses, 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 further optimize database performance or
efficiency, such as PIOPs, memory and compute resources, caching, and so on.
• 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 affect system performance or
overall efficiency.
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PERF 5 How do you configure your networking solution?
The optimal network solution for a system varies based on latency, throughput requirements,
and so on. Physical constraints such as user or on-premises resources drive location options,
which can be offset using edge techniques 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.
• Understand available product options: Understand the service-level features that are
available to optimize network-related performance; for example, EC2 instance network
capability, enhanced networking, Amazon EBS-optimized instances, Amazon S3 Transfer
Acceleration, and dynamic content delivery with Amazon CloudFront.
• Evaluate available networking features: Evaluate networking features in AWS that
increase performance. Measure the impact of these features through testing, metrics,
and analysis. For example, take advantage of network-level features that are available
(including Amazon Route 53 latency-based routing, Amazon VPC endpoints, or AWS Direct
Connect) to reduce latency, network distance, or jitter.
• Use minimal network ACLs: Design your network to minimize the number of ACLs
while still meeting requirements. Having too many ACLs can negatively impact network
performance, reducing system performance or efficiency.
• Leverage encryption offloading and load-balancing: Use load balancing for offloading
encryption termination (TLS) to improve performance and to manage and route traffic
effectively. Distribute traffic across multiple resources or services to allow your workload to
take advantage of the elasticity that AWS provides.
• Choose network protocols to improve performance: When choosing protocols for
communication between systems and networks, make decisions based on how those
protocols will impact workload performance.
• Choose location based on network requirements: Use the location options available (for
example, AWS Region, Availability Zone, placement groups, and edge locations) to reduce
network latency or improve throughput.
• Optimize network configuration based on metrics: Use data that is collected and
analyzed to make informed decisions about optimizing your network configuration.
Measure the impact of those changes and use the impact measurements to make future
decisions.
73

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:
• Keep up-to date on new resources and services: Evaluate ways to improve performance
as new services, design patterns, or product offerings become available. Consider how
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 which
improvements in performance or efficiency would be gained by using them.
• 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 are available to improve performance or make efficiency gains in your
workload.
74

Monitoring
PERF 7 How do you monitor your resources to ensure they are performing as expected?
System performance can degrade over time. Monitor system performance to identify this
degradation and remediate internal or external factors, such as the operating system or
application load.
Best practices:
• Record performance-related metrics: Use Amazon CloudWatch, a third-party service, or
self-managed monitoring tools 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 at
expected levels.
• Establish KPIs to measure workload performance: Identify the KPIs that indicate whether
the system is performing as intended. For example, an API-based workload may use overall
response latency as an indication of overall performance, and an e-commerce site may
choose to use the number of purchases being made as its KPI.
• Use monitoring to generate alarm-based notiﬁcations: Using the performance-related
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 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, a system that can predict expected 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.
75

Tradeoffs
PERF 8 How do you use tradeoffs to improve performance?
When architecting solutions, actively considering 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 the customer experience. For example, a website that has a lot of customer
interaction would benefit from using edge services such as Amazon CloudFront 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 may be trading to achieve higher performance. For example, using
Amazon ElastiCache can help to reduce 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, consider how those choices will impact customers and workload
efficiency. For example, if using key-value storage such as Amazon DynamoDB would
significantly increase system performance, it is also important to evaluate how the
eventually consistent nature of Amazon DynamoDB could affect customers.
• Measure the impact of performance improvements: As changes are made to improve
performance, evaluate metrics and data that were collected to determine the impact that
the performance improvement had on the workload, its components, and any 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 a number of
strategies to improve performance. For example, use 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.
76

Cost Optimization
Expenditure Awareness
COST 1 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.
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. Also develop cost targets and goals for 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, 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.
77

COST 2 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 AWS Cost and Usage Report: Configure the AWS Cost and Usage Report to
capture detailed usage and billing information.
• 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.
• Define and implement tagging: Define a tagging schema based on organization,
and workload attributes, and cost allocation categories. Implement tagging across all
resources.
• Configure billing and cost management tools: Configure AWS Cost Explorer and AWS
Budgets inline with your organization policies.
• 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 this 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.
• Allocate costs based on workload metrics: Allocate this 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.
78

COST 3 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:
• 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 in an unplanned manner: Decommission resources on an
unplanned basis. This is typically triggered by events such as periodic audits and is usually
performed manually.
• 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.
79

Cost-Effective Resources
COST 4 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 components of this workload to optimize cost inline 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, and 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
this workload remains cost effective over its lifetime.
80

COST 5 How do you meet cost targets when you select resource type and size?
Ensure that you choose the appropriate resource size for the task at hand. By selecting the
most cost effective type and size, you minimize waste.
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 estimates: Estimate resource size or type based
on workload and resource characteristics; for example, compute, memory, throughput, or
write intensive. This estimate 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 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 a manual process of re-sizing.
COST 6 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: Perform an analysis on the workload using the Reserved
Instance Recommendations feature in AWS Cost Explorer.
• Implement different pricing models, with low coverage: Implement reserved capacity,
Spot Instances, Spot Blocks or Spot Fleet, in the workload but with low coverage, at less
than 80 percent of overall recommendations.
• Implement pricing models for all components of this workload: Permanently running
resources have high coverage with reserved capacity, with at least 80 percent of
recommendations implemented. Short term capacity is configured to use Spot Instances,
Spot Blocks 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: typically 25 to 75
percent of the year, depending on the resource type.
• 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.
81

COST 7 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.
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.
Matching supply and demand
COST 8 How do you match supply of resources with demand?
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.
• Provision resources reactively or unplanned: Resource levels change due to demand,
however provisioning is in an unplanned manner, typically manually, and triggered by
adverse events or changes in the workload. Resourcing is slow to change, and typically
results in over or under provisioning.
• Provision resources dynamically: Resources are provisioned in a planned manner. This
can be demand-based, such as through automatic scaling; buffer-based, where demand
is spread over time with lower overall resourcing used; 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.
82

Optimizing Over Time
COST 9 How do you evaluate new services?
architectural decisions to ensure they continue to be the most cost effective.
Best practices:
• Establish a cost optimization function: Create a team that regularly reviews cost and
usage across the organization.
• 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.
• Review and implement services in an unplanned way: Adopt new services in an
unplanned way.
• Review and analyze this workload regularly: Existing workloads are regularly reviewed as
per defined processes.
• 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.
83

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