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NDev Talk - Serverless Design Patterns
- 1. Serverless Design Patterns NDev Meetup 11/2018
- 2. Intro • Currently freelance software engineer and architect • Former AWS • API Gateway, Lambda • Prev: Verafin, D2L • MUN Comp Eng 2007
- 5. Building with serverless is awesome and easy! … but awkward at first
- 6. A Brief History of Cloud Compute… • Pre-2008: The dark ages: on-prem, hardware, VMWare • 2008: VMs on EC2 (IaaS) • 2011: Elastic Beanstalk (PaaS) • 2014: AWS Lambda (BaaS, FaaS) • 2015: Elastic Container Service • 2017: Fargate, EKS • 2018+: ??? (Re:Invent is tomorrow!)
- 7. Serverless? • What does it even mean? • Generally accepted properties: • Uses fully-managed cloud services • Pay-per-use (i.e. request). “Don’t pay for idle” • Auto-scales • Servers/hardware/OS, and potentially runtimes, are abstracted • Concept predates the term (2014) • i.e. S3 (2006) meets the definition of serverless
- 8. FaaS • (Stateless) Functions as a Service • AWS Lambda • Azure Functions • Google Cloud Functions • Auth0 WebTask • etc.
- 9. Other serverless services • AWS • S3 • DynamoDB* • Cognito • API Gateway • Aurora • …
- 10. Use-cases • Respond to events • i.e. drop an image in S3, automatically generate a thumbnail using Lambda • Event sources on AWS: DynamoDB, Kinesis, SQS, S3, Cloudwatch Events, API Gateway, etc. • Web/mobile application backend • REST/GraphQL API fronted by API Gateway/AppSync • Can reuse ExpressJS, Jersey/Spring/Spark, Flask, etc. • IoT backend
- 11. Use-cases • Stream processing • i.e. clickstreams, logs, event sourcing, etc. • Kinesis, Kafka, etc. • Edge computing • CDN, Lambda@Edge i.e. re-write routing or caching rules at runtime based on user request. • Greengrass • Workflows • Step Functions • Scheduled processing • CloudWatch events • Alexa Apps
- 12. Advantages • Automatic scaling • Good for bursty workloads • VMs and containers generally have very low utilization • Automatic multi-zone redundancy for high-availability • “Secure by default” • Faster time and lower cost to market. Easy to do cheap experiments
- 13. Advantages • Cost • Pay per 100ms. Free tier. Don’t pay for idle • Simplicity • Don't have to manage hardware, OS, patches, etc. • Developers focus on business logic, not infra. Don’t need “DevOps” team • Less infra: no load balancers, VPCs, security groups, etc
- 14. Disadvantages • Cold starts • Not ideal for highly latency-sensitive use-cases (i.e. p99+) • More $ at scale • Dev/test • Debugging and distributed tracing • Impedance mismatch with web server frameworks • Large batch processing: handling of large files or long-running processes • Lambda 15 min timeout • Lambda 500MB scratch disk • If workload can’t be partitioned or made into a workflow
- 16. Patterns • I want to host a website “serverlessly” • Static assets/JS hosted in S3 bucket • CDN and edge cache provided by CloudFront • Custom domain name tied to CloudFront distribution • HTTPS certificate for TLS
- 17. Patterns • I want to host a backend for a web or mobile application “serverlessly” • API Gateway for REST API backend over HTTPS • Lambda for backend implementation • Can use existing server-side HTTP frameworks: Express/Jersey/Spring/Flask/ etc. • Cognito for AuthN/AuthZ • Datastore in DynamoDB, Aurora, RDS, custom, etc. • See also: AWS AppSync, Mobile BaaS
- 18. Patterns • I want to process a stream of events or messages “serverlessly” • Event stream using Kinesis, SQS, DynamoDB streams, Kafka, etc. • Potentially many producers, consumers • Event listener implemented in Lambda • Automatically invoked with batches of events (configurable) • “Fan out”: invoke a separate function, or multiple functions, per event • Event-sourcing, “databases as cattle”, “turning the database inside out” • Dead Letter Queue for failures (SQS)
- 19. Patterns • I want to execute a scheduled job “serverlessly” • i.e. “serverless” cron job. Good for background processing, asynchronous workflows • Job implemented in AWS Lambda • CloudWatch Event trigger with cron expression
- 20. Patterns • I want to execute a complex workflow “serverlessly” • Workflow defined in Step Functions • State machine loops/conditions/retries/etc. • Can include human intervention • Can run for up to a year • Workflow tasks implemented in AWS Lambda • Example: https://aws.amazon.com/blogs/ compute/implementing-canary-deployments-of- aws-lambda-functions-with-alias-traffic-shifting/
- 21. Patterns • Adoption patterns • New services built using serverless • Async components outside of critical path • Lift-and-shift entire application into Lambda
- 22. Tools • Deployment • AWS CLI/SDK • SAM • SAM Local • Serverless • Apex • Chalice (Python) • Zappa • Test/debug • XUnit • SAM Local • Tracing • X-Ray • Libraries • aws-serverless-express • JS/Node/Express • aws-serverless-java-container • Java/Jersey/Spring • aws-lambda-go • Golang
- 23. Demo • Facebook Live “Like” button clone • Patterns used • Static web application • Web application backend / REST API / microservice • Stream processing • Scheduled asynchronous processing • Fully “infrastructure as code”, defined in SAM
- 25. Demo $ git clone [email protected]:rpgreen/ndevdemo.git
- 26. Future • Composable apps (Serverless Application Repository) • Composable functions • Custom agents and runtimes • Serverless containers (Fargate) • Less containers in general, far less VMs • More framework support for FaaS • Better tooling • Cold start minimization • NoCode (i.e. AppSync)