Operating Microservices at Hyperscale — Tech in Asia PDC 2019
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Presented at Tech in Asia PDC 2019 in Jakarta. Most developers today are adopting a microservices based application design. Microservices can provide higher system reliability, fine-grained scalability, and faster development cycles. At hyperscale (thousands to millions of requests per second), however, additional thought, careful design, and greater operational rigor are required. In this session, learn fundamental design principles and best practices for hyperscale applications.
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Operating Microservices at Hyperscale — Tech in Asia PDC 2019
- 1. Operating Microservices at Hyperscale Donnie Prakoso, MSc Senior Technical Evangelist, ASEAN Amazon Web Services @donnieprakoso donnieprakoso
- 2. > hello, world Donnie Prakoso, MSc Senior Technical Evangelist, ASEAN @donnieprakoso donnieprakoso • Speak in Go and Python • I talk a lot about microservices and machine learning • I AWS User Groups • Self-proclaimed Barista and Café Racer enthusiasts
- 4. ListenIterate Experiment Innovation flywheel Experiments power the engine of rapid innovation
- 5. Development transformation at Amazon: 2001–2002 Monolithic application + teams 2001 Lesson learned: Decompose for agility 2002 Microservices + two pizza teams
- 6. Changes to the team structure
- 7. Full ownership Full accountability DevOps Focused innovation Two-pizza teams
- 8. Changes to the architectural patterns
- 9. When the impact of change is small, release velocity can increase Monolith Does everything Microservices Does one thing
- 10. When a small team can make a change, release velocity can increase Multiple teams Loosely connected One team Focus and ownership
- 11. New services and features released per year 0 500 1000 1500 2000 2500 2011 2012 2013 2014 2015 2016 2017 2018
- 12. Amazon S3 Object storage built to store and retrieve any amount of data from anywhere
- 13. Deployment at scale Thousands of teams Microservices CI/CD Serverless > 60 million deployments a year*
- 14. Journey to Hyperscale Your Microservices 1. Understand important components in Microservices architecture 2. Utilizing Event-Driven Architectures 3. Increase software release velocity — CI/CD 4. Changing operational model — Serverless
- 15. APIs are the front door of microservices
- 16. Microservice API API Microservice Microservice Event API Microservice Event API Microservice Application Mobile client Client Internet of Things (IoT) Persistence Persistence
- 17. APIs are the “hardened contract” between teams
- 18. Manage APIs with Amazon API Gateway Mobile apps Websites Services Internet Amazon CloudFront Amazon CloudWatch monitoring API Gateway cache Any other AWS service All publicly accessible endpoints Lambda functions Endpoints in your VPC Regional API endpoints AWS Lambda functions Endpoints on Amazon Elastic Compute Cloud (Amazon EC2) Your virtual private cloud (VPC) Amazon Web Services (AWS)
- 19. AWS AppSync Managed serverless GraphQL service Connect to data sources in your account Add data sync, real-time, and offline capabilities for any data source or API GraphQL facade for any AWS service Conflict detection and resolution in the cloud Enterprise security features: IAM, Amazon Cognito, OIDC, API keys
- 21. Decouple state from code using messaging
- 22. Decouple state from code using messaging Queues Simple Fully managed Any volume Pub/sub Simple Fully managed Flexible Amazon Simple Queue Service (Amazon SQS) Amazon Simple Notification Service (Amazon SNS) Messaging Synchronization Rapid Fully managed Real time Amazon CloudWatch Events
- 24. Amazon SNS “CheckoutEventsTopic” Event storage and backup pipeline Event search and analytics pipeline Event replay pipeline Checkout event processing pipeline filtered orders (amount >= $100) Orders to replay All orders AWS Cloud Ecommerce users Internet Lambda “CheckoutFunction” Amazon SQS “CheckoutQueue” Lambda “CheckoutFunction” Amazon DynamoDB “CheckoutTable” Event-driven architecture
- 25. NASA Image and Video Library Amazon SNS Amazon SQS
- 27. Stream processing Ingest Data streams Data processing Real time Data store Microservices Performance at scale Fast and flexible Amazon Kinesis data streams DynamoDB Data-stream capture
- 28. Track status of data and execution Remove redundant code Build workflows to orchestrate everything
- 29. AWS Step Functions With serverless polling With new service integration Start End Lambda functions Start End No Lambda functions
- 30. Object storage Durable and scalable Comprehensive security Query-in-place AWS serverless storage and database options Non-relational Performance at scale Fully managed Enterprise-ready Relational Fully managed High performance Cost effective
- 31. Cloud-native architectures are small pieces, loosely joined
- 32. Changes to the operational model
- 33. AWS operational responsibility models On premises Cloud Less More Compute Virtual machine Amazon EC2 AWS Elastic Beanstalk LambdaAWS Fargate Databases MySQL MySQL on Amazon EC2 Amazon RDS MySQL Amazon RDS Aurora Aurora Serverless DynamoDB Storage Storage Amazon S3 MessagingEnterprise service buses (ESBs) Amazon MQ Kinesis Amazon SQS/Amazon SNS Analytics Apache Hadoop Hadoop on Amazon EC2 Amazon EMR Amazon Elasticsearch Service Amazon Athena
- 34. More granular control also means more moving parts which will increase complexity use serverless to help you
- 35. What is serverless? No infrastructure management Automatic scaling Pay for value Highly available and secure
- 36. Lambda Fargate API Gateway Amazon SNS Amazon SQS AWS Step Functions Compute Data stores Integration Aurora ServerlessAmazon S3 DynamoDB AWS AppSync
- 37. Serverless compute engine for containers Long-running Bring existing code Fully managed orchestration Fargate Let’s focus on compute for now Serverless event-driven code execution Short-lived All language runtimes Data-source integrations Lambda
- 38. Making development easier with Lambda Accessible for all developers Enable new application patterns Greater productivity Support for all runtimes with Lambda Layers and Runtime API ISO, PCI, HIPAA, SOC, GDPR, and FedRamp compliances 15-minute functions Amazon SQS for Lambda Automatic load balancing for Lambda Support for Kinesis Data Streams Enhanced Fan-Out and HTTP/2 Toolkits for popular integrated development environments (IDEs): VSCode, IntelliJ, and PyCharm Simplified deployment with nested apps
- 39. Author and debug Lambda applications on AWS using your favorite IDEs Python, Node Python Java Developer preview .NET, Node
- 40. Serverless containers with Fargate Bring existing code Containers as first-class primitive Production ready No changes required of existing code, works with existing workflows and microservices built on Amazon ECS Time- and event-based scheduling, network integration, individually metered and billed; native service discovery ISO-, PCI-, HIPAA-, SOC- compliant. Launch tens or tens of thousands of containers in seconds in nine global regions (+ seven in 2018)
- 41. Changes to the delivery of software
- 42. Monolith development lifecycle MonitorReleaseTestBuild Developers Delivery pipelines Services
- 43. Microservice development lifecycle Developers Services MonitorReleaseTestBuild Delivery pipelines MonitorReleaseTestBuild MonitorReleaseTestBuild MonitorReleaseTestBuild MonitorReleaseTestBuild MonitorReleaseTestBuild
- 44. How Amazon does DevOps (microservices, two pizza teams) (governance, templates)
- 45. We released the AWS developer tools for continuous integration and continuous delivery (CI/CD) AWS CodeBuild + third party AWS CodeCommit AWS CodeBuild AWS CodeDeploy AWS X-Ray Source Build Test Deploy Monitor AWS CodePipeline
- 46. CI/CD – Don’t Only Run It, Own it Source MyAppSource CodeCommit Build MyAppBuild Build Deploy safetyCheck Approval ProductionDeploy CodeDeploy Lambda Function safetyCheck New update! SNS Topic
- 47. X-Ray is built for modern applications Identify customer impact Support for serverless Map all services and ephemeral resources Follow end-to-end interactions
- 48. Conclusion
- 49. Increase customer value Build better products Innovate more often Release features faster Focus on business logic Decouple software systems Our goal is to automate and abstract away as much as is possible so customers can focus on building applications for their business We are witnessing a paradigm shift
- 50. Thank you! Donnie Prakoso Senior Technical Evangelist, ASEAN Amazon Web Services @donnieprakoso donnieprakoso