Serverless Architecture 101 ⚡
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The document discusses the adoption of serverless architecture, highlighting benefits such as agility, performance, cost savings, and security. It outlines various strategies for implementing serverless solutions, including transitioning from on-premises to cloud environments and optimizing operations. The case study of AXA showcases the practical application of serverless technology to enhance innovation and efficiency in their business operations.
Serverless Architecture 101 ⚡
- 1. Thanh Nguyen +84 938203080 nnthanh101@gmail.com Serverless Architecture 101 ⚡
- 2. Agenda Why are Customers adopting a Serverless-first Strategy? AXA >> Rearchitecting with Serverless to accelerate innovation Thinking Serverless from Business Problem to Serverless Solution ⚡ Getting started with serverless for developers Demo & Discussion Quiz
- 3. © 2021 3 What do our customers need to drive success? Get to market faster High performance and scalability Security and isolation by design Lower total cost of ownership
- 4. © 2021 4 CIO’s say that 80% of developers’ time is spent on the operations and maintenance of applications and only 20% of the time is actually spent on innovation Source: Deloitte 2019
- 5. © 2021 6 Why are customers building with a serverless-first strategy? Agility Performance Cost Security
- 6. © 2021 7 How are customers adopting a serverless strategy? Lift and shift REDUCE the amount of DIY MIGRATE to AWS MODERNIZE onAWS Retire SaaS Refactor Replatform BUILD NEW INNOVATION
- 7. © 2021 8 Computing evolution – A paradigm shift LEVEL OF ABSTRACTION FOCUS ON BUSINESS LOGIC PHYSICAL MACHINES Requires “guess” planning Lives for years on-premises Heavy investments (capex) Low innovation factor Deploy in months
- 8. © 2021 9 Computing evolution – A paradigm shift LEVEL OF ABSTRACTION FOCUS ON BUSINESS LOGIC VIRTUAL MACHINES Hardware independence Faster provisioning speed (minutes/hours) Trade capex for opex More scale Elastic resources Faster speed and agility Reduced maintenance
- 9. © 2021 10 Computing evolution – A paradigm shift LEVEL OF ABSTRACTION FOCUS ON BUSINESS LOGIC CONTAINERIZATION Platform independence Consistent runtime environment Higher resource utilization Easier and faster deployments Isolation and sandboxing Start speed (deploy in seconds)
- 10. © 2021 11 Computing evolution – A paradigm shift AWS Lambda AWS Fargate LEVEL OF ABSTRACTION FOCUS ON BUSINESS LOGIC Continuous scaling Fault tolerance built-in Pay for value Zero maintenance SERVERLESS
- 11. © 2021 12 Leap Frog Adoption C A PA C I T Y P R O C E S S E S C O S T M O D E L S OP ER AT I ON AL P R OCESS ES DEV ELOP MEN T MODELS ON-PREMISES CLOUD “LEGACY”ARCHITECTURES MODERNARCHITECTURES AWS EC2 AWS ECS AWS FARGATE AWS EKS Containers AWS ECS AWS FARGATE AWS EKS
- 12. © 2021 13 What is Serverless? No infrastructure provisioning, no management Automatic scaling Pay for value Highly available and secure
- 13. © 2021 Serverless Architecture Event Source Function Services / Other Node.js Python Java C# Go Ruby BringYour Own Changes in data state Requests to endpoints Changes in resource state
- 14. © 2021 15 Lambda execution model © 2020, AmazonWeb Services, Inc. or its affiliates. All rights Synchronous (push) Asynchronous (event) Stream-based Amazon API Gateway Lambda function Amazon DynamoDB Amazon SNS /order Lambda function Amazon S3 Reqs Amazon Kinesis Changes AWS Lambda service Function
- 15. © 2021 16 AWS Lambda AWS Fargate Amazon API Gateway Amazon SNS Amazon SQS AWS Step Functions COMPUTE DATA STORES INTEGRATION AWS AppSync Amazon Aurora Serverless Amazon S3 Amazon DynamoDB Amazon EventBridge
- 16. AXA:RearchitectingwithServerlessto accelerate innovation Multinational insurance firm that engages in property-casualty insurance, life and savings, and asset management Present in 57 countries, with 160,000 employees and distributors, to serve our 108 million clients AXA Group Operations Emerging technologies and data division Explores and scales value of data and emerging technologies with potential to disrupt current insurance business model AXA GO 6 years in business Flagship project – automotive telematics, which combine data science and data processing chain Team-developed and maintained solution (data science, network, mobile, backend, and so on) Telematics team
- 17. Business rational • Develop data-driven motor insurance policies • Pay per mile, per day, per risk profile, with periodic premium adjustment • Provide immediate “post-trip” risk feedback to help customer drive safer Where we are today • Live connection with black boxes, smartphones, and native car connectivity as GPS sources • 5 offers on EU market • 40,000+ customers • 60,000+ vehicle trips per day AXA-TEXproject –TelematicsExchange platform
- 18. AXA-TEX– High-levelfunctional view Sources Acquisition Storage Analysis …. Processing OBD Presentation Box Smartphone Weather Mapping Algorithms and Data Lake Connected Car Dashboard App API
- 19. 1 AWS account, multiple environments Over 50 Amazon EC2 instances in total Designed for portability to AXA data center • Deployment with Ansible • Limited AWS technologies used • Infrastructure withTerraform AXA-TEXas webuilt it in 2015 (v1) Elastic Load Balancing AWS Cloud Admin Shinken Syslog Scoring Business logic Flume Datafront HAProxy Business logic Nginx Analytics Carbon Grafana Kibana Dashboards Nginx Business logic Worker Apache Kafka Zookeeper MongoDB PostgreSQL Business logic Elasticsearch Elasticsearch Efforts to manage • Setup of monitoring tools • Regular fix / security updates needed • Difficult to add new components • Deployment complex and slow • HSM and IPSec links to manage due to strong security constraints
- 20. Whyweneeded tochange? Focus on features We want to spend more time developing functionalities than managing a system Easier scaling Scalability of our architecture is possible, but both manual and difficult Lack of scalability of some components due to hasty decisions Less system engineering Amazon EC2 management requires regular system updates, advanced monitoring and major operational challenges More security We are subject to strong constraints that are difficult for our team to manage
- 21. TEXv2
- 22. Messaging / event streaming ESBs Amazon Managed Streaming for Apache Kafka (Amazon MSK) Amazon Kinesis Amazon SQS / Amazon SNS Kafka on Amazon EC2 AWS operational responsibilitymodels On-premises Cloud - IaaS TEX v1 Less More Compute Virtual machine Amazon EC2 AWS Elastic Beanstalk AWS Lambda AWS Fargate Relational database PostgreSQL PostgreSQL on Amazon EC2 Amazon RDS Amazon Aurora Aurora Serverless Amazon DynamoDB MongoDB MongoDB on Amazon EC2 Amazon DocumentDB Document- oriented database Cloud - Serverless
- 23. Moving toserverless –Compute Virtual machine on-premises Amazon EC2 Elastic Beanstalk Lambda Fargate TEX v1 Usage Asynchronous processing of car data stream Benefits • High scalability • Cost optimization • Integration with other AWS services (e.g., Kinesis) Usage • Communication with telematics boxes via UDP • Long batches Benefits • Flexibility of containers • Serverless infrastructure 90% 10%
- 24. Moving toserverless – Messaging/Streaming Usage Message queue to compute driver score Benefits Automatic scalability Usage • Car event streaming • Multiple consumers • Need to preserve order Benefits • Easy to scale by increasing number of shards • Possibility to TEX v1 Amazon MSK Kinesis Amazon SQS / Amazon SNS Kafka on Amazon EC2 Kafka on-premises
- 25. Data Database TEX v1 Database TEX v2 Current trips MongoDB on Amazon EC2 DynamoDB Moving toserverless:Databases Data Database TEX v1 Database TEX v2 Current trips MongoDB on Amazon EC2 DynamoDB Driver scores / trips history Elasticsearch on Amazon EC2 Aurora Serverless – PostgreSQL Cartography PostgreSQL on Amazon EC2
- 26. Messaging / event streaming ESBs Amazon MSK Kinesis Amazon SQS / Amazon SNS Kafka on Amazon EC2 AWS operational responsibilitymodels Compute Virtual machine Amazon EC2 Elastic Beanstalk Lambda Fargate On-premises Less More Relational database PostgreSQL PostgreSQL on Amazon EC2 Amazon RDS Aurora Aurora Serverless DynamoDB MongoDB MongoDB on Amazon EC2 Amazon DocumentDB Document- oriented database TEX v1 TEX v2 Cloud - IaaS Cloud - Serverless
- 27. TEXv2 –Simplified processing pipeline Supervision and monitoring KMS ACM Secrets Manager CloudWatch Route 53 Parameter Store AWS Cloud Athena EMR Kinesis Firehose Fargate Specific Tools S3 Data lake Aurora Trips Aurora Scores Persistence AXA entities Lambda API GW Data presentation Enrichment Traffic data provider Weather data provider Lambda Aurora Cartography Amazon ElastiCach e API GW Ingestion Driving data provider S3 Lambda Lambda CloudWatch Events Processing DynamoDB Sessions Kinesis Kinesis SQS Lambda Enrichment Lambda Trip Creation Lambda Driving Score
- 28. Business logic scaling effect • Smoothly scale depending on road traffic • Development environment – no traffic ≃$0 for Lambda • Production environment – lower cost than fault-tolerant servers dedicated to business logic TEXv2 – Lambda activities Kinesis incoming records Data enrichment Lambda invocations
- 29. AXA Landing Zone • Activation of monitoring and security tools, such as CloudTrail, Amazon GuardDuty, service control policies, and so on • Authentication management • Ensure compliance with Config • Centralized billing Presentation made at AWS re:Invent 2019 TEXv2 –AWSAccounts organization Developers Terraform deployment Read only Terraform deployment Data scientists AXA Landing Zone Project Project Project Git Analytics Tools TEX Production Preprod and UAT Integration Developer account Developer account Developer account AXA organization VPC peering TEX Foundation AXA Foundation Prime accounts One AWS account per variant – prod, preprod, development Analytics account • Read-only access for the production • VPC peering for Aurora access • Monitored actions of data scientists Tools account • CI / CD (Jenkins) • Artifact library (S3) • DNS management
- 30. TEXv2 – Did we succeedin resolvingour issues? Less system engineering Easier scaling More security Focus on features ✓ ✓ ✓ ✓ A full class of issues disappeared with the serverless migration The architecture and the infrastructure just scale Some components may need manual tuning We spend less time in maintaining the infrastructure, So we are more comfortable in adding new features We do not think about it anymore Remaining tasks are on database performance with business logic
- 31. Lessons learned Aurora Serverless requires aVPC configuration Kinesis shards and Aurora units need manual tuning Full serverless is not always possible, hybrid approach should be kept in mind and integrated in infrastructure as code Fewer features with Aurora Serverless than with Amazon RDS equivalents Kinesis costs, even if not used Serverless still needs configuration Hybrid architecture Techno maturity Lambda can scale too much and be costly if bug in logic or architecture – set alarms and limits Control automatic scaling
- 32. State management Monolithic container for functionality One version, one server Server is an atomic unit of thinking The challenges of this model How do weuseServers?
- 34. Features first Focus on Events Stateless Data-flow Use the Services Avoid monolithic thinking Events are triggers that cause action The key to scaling effectively Make data decisions early on Don’t reinvent the wheel GeneralApproach toThinkingServerless
- 35. Attributes Runs on demand Supports many runtimes Responds to events Stateless Automatically scales Best practices Avoid lift-and-shift One function per purpose Keep functions small Choose the right runtime for the job Use functions for business logic and plumbing between services ✍️Understanding howAWS Lambda fitsin
- 36. Infrastructure is disposable Asynchronous versus synchronous processing You can mix and match runtimes Security still matters: build in from the start Automation AWS Serverless Application Model (AWS SAM) The AWS Cloud Development Kit (AWS CDK) Serverless Framework ✍️GoodServerlesspractices
- 37. 1. Form upload Create a serverless application to support a customer review form submitted from a webpage
- 38. 1. Form upload Create a serverless application to support a customer review form submitted from a webpage Amazon API Gateway AWS Lambda Amazon DynamoDB
- 39. 1. Form upload Create a serverless application to support a customer review form submitted from a webpage Amazon API Gateway AWS Lambda Amazon DynamoDB AWS Lambda Amazon Translate
- 40. 1. Form upload Create a serverless application to support a customer review form submitted from a webpage AWS Lambda Amazon S3
- 41. 1. Form upload Create a serverless application to support a customer review form submitted from a webpage AWS Lambda Amazon SNS Amazon Comprehend
- 42. 1. Form upload Create a serverless application to support a customer review form submitted from a webpage Amazon Cognito Amazon API Gateway
- 43. A global retailer wants to implement a virtual queue for customers. Use an IoT button to manage a “now serving” counter. 2.Createa virtualqueue
- 44. A global retailer wants to implement a virtual queue for customers. Use an IoT button to manage a “now serving” counter. 2.Createa virtualqueue IoT button AWS IoT Core AWS Lambda Amazon DynamoDB AWS Lambda Amazon API Gateway Customer display
- 45. A global retailer wants to implement a virtual queue for customers. Use an IoT button to manage a “now serving” counter. 2.Createa virtualqueue AWS Lambda AWS IoT Core Customer display
- 46. A global retailer wants to implement a virtual queue for customers. Use an IoT button to manage a “now serving” counter. 2.Createa virtualqueue AWS Lambda Amazon S3 Amazon Polly
- 47. A global retailer wants to implement a virtual queue for customers. Use an IoT button to manage a “now serving” counter. 2.Createa virtualqueue Amazon EventBridge rule (scheduled) AWS Lambda Amazon SNS
- 48. A global retailer wants to implement a virtual queue for customers. Use an IoT button to manage a “now serving” counter. 2.Createa virtualqueue
- 49. Create a serverless web application to support an e-commerce business High volume, spiky, unpredictable traffic patterns Geographically distributed Requires high performance front-end, low latency 3.WebApplication
- 50. Create a serverless web application to support a national e-commerce business 3.Web application Browser Amazon Route 53 AWS Amplify console GitHub repo
- 51. Create a serverless web application to support a national e-commerce business 3.Web application Amazon Cognito Auth0
- 52. Create a serverless web application to support a national e-commerce business 3.Web application Amazon API Gateway AWS Lambda Amazon S3 AWS Lambda Amazon S3 AWS Lambda Amazon DynamoDB
- 55. 3.Thefront door
- 58. © 2021, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark © 2020, AmazonWeb Services, Inc. or its affiliates. All rights reserved. Serverl ess vocabu lary Live Demo https://dashboard.job4u.io KPI Dashboard on AWS Data Ingestion API Operations Runbook: logging, monitoring, alerting on issues Scaling: how to scale Performance Dashboard Security Shared Responsibility between AWS & Customer IP Blocking: limit access to come from an IP range (e.g. on-premises network)
- 60. © 2021, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark © 2020, AmazonWeb Services, Inc. or its affiliates. All rights reserved. Serverl ess vocabu lary LAB https://webapp.serverlessworkshops.io/ https://github.com/aws-samples/getting- started-with-serverless