Performing chaos in a serverless world - ServerlessDays Hamburg October 2 2020

Presented at ServerlessDays Hamburg, October 2nd, 2020.

@gunnargrosch
Serverless Chaos Demo
failure-lambda
failure-azurefunctions
failure-cloudfunctions

Chaos engineering is the practice of hypothesis testing through planned experiments to gain a better understanding of a system’s behavior. The principles of chaos engineering have been around for years, and we have now reached the point where chaos engineering has gone from just being a buzzword and practice used by a few large organizations in very specific fields, to it being put in to use by companies of all sizes and industries.

Planning and performing chaos experiments on traditional infrastructure with virtual machines and microservices using containers has been battle-tested by many large organizations, but serverless functions and managed services present different failure modes and level of abstraction.

In this talk we focus on how to apply the principles of chaos engineering to serverless, both for serverless functions and managed services. This covers how hypothesis can be formed to fit serverless, what the experiments can achieve and how to practically perform them.

With tools for chaos engineering, both commercial and open-source, getting more mature most of them still have focus primarily on virtual machines and containers. We’ll look at what tools are out there to help with chaos experiments for serverless and managed services, but also how you can build your own.

Join as we move from talking about the principles to performing real chaos in a serverless world!

Transcript

1. @gunnargrosch Gunnar Grosch October 2, 2020 Performing chaos in a serverless world ServerlessDays Hamburg
2. @gunnargrosch Abstract The principles of chaos engineering have been battletested for years using traditional infrastructure and containerized microservices. But how do they work with serverless functions and managed services?
3. @gunnargrosch Agenda • What is chaos engineering? • Motivations behind chaos engineering • Running chaos experiments • Challenges with serverless • Serverless chaos experiments
4. @gunnargrosch About me Background in development, operations, and management Organizer of user groups and conferences AWS Serverless Hero Father of three
5. @gunnargrosch What is chaos engineering?
6. @gunnargrosch What is chaos engineering? Chaos engineering is not about breaking things
7. @gunnargrosch What is chaos engineering? Chaos engineering is not only for production
8. @gunnargrosch What is chaos engineering? “Chaos Engineering is the discipline of experimenting on a system in order to build confidence in the system’s capability to withstand turbulent conditions in production” principlesofchaos.org
9. @gunnargrosch What is chaos engineering? Chaos engineering is about performing controlled experiments to inject failures
10. @gunnargrosch What is chaos engineering? Chaos engineering is about finding the weaknesses in a system and fixing them before they break
11. @gunnargrosch What is chaos engineering? Chaos engineering is about building confidence in your system and in your organization
12. @gunnargrosch Motivations behind chaos engineering
13. @gunnargrosch Motivations behind chaos engineering Are your customers getting the experience they should? Is downtime or issues costing you money? Are you confident in your monitoring and alerting? Is your organization ready to handle outages? Are you learning from incidents?
14. @gunnargrosch Motivations behind chaos engineering Don’t ask what happens if a system fails; ask what happens when it fails
15. @gunnargrosch Motivations behind chaos engineering “Chaos engineering should be done regularly” Reliability Pillar AWS Well-Architected Framework
16. @gunnargrosch Running chaos experiments
17. @gunnargrosch Running chaos experiments Define steady state Form your hypothesis Plan and run your experiment Measure and learn
18. @gunnargrosch Challenges with serverless
19. @gunnargrosch Challenges with serverless “Serverless allows you to build and run applications and services without thinking about servers” Amazon Web Services (AWS)
20. @gunnargrosch Challenges with serverless “There are still servers in serverless” Serverhuggers
21. @gunnargrosch Challenges with serverless No servers to manage Less heavy lifting Lots of services to choose from Per function and service configuration More granular architectures
22. @gunnargrosch Serverless chaos experiments
23. @gunnargrosch Serverless chaos experiments Inject errors into your code Remove downstream services Alter the concurrency of functions Restrict the capacity of tables Client Amazon Simple Storage Service (Amazon S3) Amazon API Gateway AWS Lambda Amazon DynamoDB AWS Lambda Amazon Simple Storage Service (Amazon S3)
24. @gunnargrosch Serverless chaos experiments Security policy errors CORS configuration errors Service configuration errors Function disk space failure Client Amazon Simple Storage Service (Amazon S3) Amazon API Gateway AWS Lambda Amazon DynamoDB AWS Lambda Amazon Simple Storage Service (Amazon S3)
25. @gunnargrosch Serverless chaos experiments Add latency to your functions Cold starts Cloud provider issues Runtime or code issues Integration issues Timeouts Client Amazon Simple Storage Service (Amazon S3) Amazon API Gateway AWS Lambda Amazon DynamoDB AWS Lambda Amazon Simple Storage Service (Amazon S3)
26. @gunnargrosch Failure-lambda NodeJS NPM package for NodeJS Lambdas https://github.com/gunnargrosch/failure-lambda Configuration using Parameter Store Several failure modes Latency Status code Exception Disk space Denylist const failureLambda = require('failure-lambda’) exports.handler = failureLambda(async (event, context) => { ... }) { "isEnabled": false, "failureMode": "latency", "rate": 1, "minLatency": 100, "maxLatency": 400, "exceptionMsg": "Exception message!", "statusCode": 404, "diskSpace": 100, “denylist": [ "s3.*.amazonaws.com", "dynamodb.*.amazonaws.com" ] }
27. @gunnargrosch Serverless chaos demo
28. @gunnargrosch Serverless chaos demo
29. @gunnargrosch Serverless chaos demo Client Amazon S3 Amazon API Gateway AWS Lambda Amazon DynamoDB AWS Lambda AWS Lambda
30. @gunnargrosch Client Amazon S3 Amazon API Gateway AWS Lambda Amazon DynamoDB AWS Lambda AWS Lambda Serverless chaos demo What if my function takes an extra 300 ms for each invocation? What if my function returns an error code? What if I can’t get data from DynamoDB? Hypothesis: If we inject failure to functions then my application will use graceful degradation.
31. @gunnargrosch Demo
32. @gunnargrosch What’s next? “Chaos engineering should be done regularly” Reliability Pillar AWS Well-Architected Framework
33. @gunnargrosch What’s next? “Chaos engineering should be done regularly, and be part of your CI/CD cycle” Reliability Pillar AWS Well-Architected Framework
34. @gunnargrosch Demo
35. @gunnargrosch What’s next? “Chaos engineering should be done regularly” Reliability Pillar AWS Well-Architected Framework
36. @gunnargrosch Summary Serverless doesn’t make your application resilient Chaos engineering helps us find weaknesses and fix them Chaos engineering is about building confidence Chaos engineering should be done regularly It’s not rocket science; you can do it!
37. @gunnargrosch Do you want more? Follow @serverlesschaos on Twitter Serverless Chaos Demo app: https://demo.serverlesschaos.com Failure-lambda: https://github.com/gunnargrosch/failure-lambda Failure-cloudfunctions: https://github.com/gunnargrosch/failure-cloudfunctions Failure-azurefunctions: https://github.com/gunnargrosch/failure-azurefunctions Chaos-lambda: https://github.com/adhorn/aws-lambda-chaos-injection/ Serverless chaos lab: https://github.com/jpbarto/serverless-chaos-lab YouTube videos and repositories: https://grosch.se
38. @gunnargrosch Thank you! Gunnar Grosch @gunnargrosch