Serverless in production (O'Reilly Software Architecture)
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The document discusses the experiences and best practices for running serverless architectures in production, covering topics such as testing, CI/CD, logging, monitoring, configuration management, and managing cold starts. It emphasizes the need for small, fast, and independently deployable deployments while minimizing costs and operational effort. It also highlights various tools and approaches to enhance serverless implementation, including the importance of end-to-end testing and effective logging and monitoring strategies.
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![if [ "$1" = "deploy" ] && [ $# -eq 4 ]; then
STAGE=$2
REGION=$3
PROFILE=$4
npm install
AWS_PROFILE=$PROFILE 'node_modules/.bin/sls' deploy -s $STAGE -r $REGION
…
install serverless framework as
dev dependency](https://image.slidesharecdn.com/serverlessinproduction-171017152644/85/Serverless-in-production-O-Reilly-Software-Architecture-100-320.jpg)
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Similar to Serverless in production (O'Reilly Software Architecture) (20)
Serverless in production (O'Reilly Software Architecture)
- 1. Serverless in production an experience report Yan Cui
- 2. What’s in this talk? ! how to responsibly run a serverless architecture (aka. how to do ops in serverless) ! testing, CI/CD ! logging, distributed tracing, monitoring ! config management, securing secrets ! coldstarts ! gotchas/limitations + workarounds/hacks
- 3. hi,I’mYanCui
- 4. hi,I’mYanCui AWS user since 2009
- 12. apr, 2016
- 13. Before ! hidden complexities and dependencies ! low utilisation to leave headroom for large spikes ! EC2 scaling is slow, so scale earlier ! paying for lots of used resources ! up to 30 mins to deploy ! deployments required downtime
- 14. - Dan North “lead time to someone saying thank you is the only reputation metric that matters.”
- 16. “what would good look like for us?”
- 17. Deployments should… ! be small ! be fast ! have zero downtime ! require no lock-step
- 18. Features should… ! be independently deployable ! be loosely-coupled
- 19. We want to… ! minimise cost of unused resources ! minimise ops effort ! reduce technical mess ! deliver visible improvements to users faster
- 20. nov, 2016
- 21. 170 Lambda functions in prod 1.2 GB deployment packages in prod 95% cost saving vs EC2 15x no. of prod releases per month
- 22. time is a good fit
- 23. 1st function in prod! time is a good fit
- 24. ? time is a good fit 1st function in prod!
- 25. Practices ToolsPrinciples what is good? how to make it good? with what?
- 28. 170 functions WOOF! ? ? time is a good fit 1st function in prod!
- 31. building a better search experience
- 32. Legacy Monolith Amazon Kinesis Amazon Lambda Amazon CloudSearch
- 33. Legacy Monolith Amazon Kinesis Amazon Lambda Amazon CloudSearchAmazon API Gateway Amazon Lambda
- 34. building an analytics pipeline
- 35. Legacy Monolith Amazon Kinesis Amazon Lambda Google BigQuery
- 36. Legacy Monolith Amazon Kinesis Amazon Lambda Google BigQuery 1 developer, 2 days design production (his 1st serverless project)
- 37. Legacy Monolith Amazon Kinesis Amazon Lambda Google BigQuery “thank you, nothing ever got done this fast at Skype!”
- 38. - Dan North “lead time to someone saying thank you is the only reputation metric that matters.”
- 39. rebuilding the timeline feature
- 46. building better user recommendations
- 47. BigQuery
- 48. BigQuery
- 61. TESTING
- 62. amzn.to/29Lxuzu
- 63. Level of Testing 1.Unit do our objects do the right thing? are they easy to work with?
- 65. 1.Unit 2.Integration does our code work against code we can’t change? Level of Testing
- 66. handler
- 67. handler test by invoking the handler
- 68. Level of Testing 1.Unit 2.Integration 3.Acceptance does the whole system work?
- 70. “…We find that tests that mock external libraries often need to be complex to get the code into the right state for the functionality we need to exercise. The mess in such tests is telling us that the design isn’t right but, instead of fixing the problem by improving the code, we have to carry the extra complexity in both code and test…” Don’t Mock Types You Can’t Change
- 71. “…The second risk is that we have to be sure that the behaviour we stub or mock matches what the external library will actually do… Even if we get it right once, we have to make sure that the tests remain valid when we upgrade the libraries…” Don’t Mock Types You Can’t Change
- 72. Services Don’t Mock Types You Can’t Change
- 73. Paul Johnston The serverless approach to testing is different and may actually be easier. http://bit.ly/2t5viwK
- 75. LambdaAPI Gateway DynamoDB Unit Tests
- 76. LambdaAPI Gateway DynamoDB Unit Tests Mock/Stub
- 77. is our request correct? is the request mapping set up is the API resources configured correctly? are we assuming the correct schema? LambdaAPI Gateway DynamoDB is Lambda proxy configured correctly? is IAM policy set up correctly? is the table created? what unit tests will not tell you…
- 79. most Lambda functions are simple have single purpose, the risk of shipping broken software has largely shifted to how they integrate with external services observation
- 81. But it slows down my feedback loop… IT’S NOT ABOUT YOU!
- 82. me test your system, not (just) your code
- 84. …if a service can’t provide you with a relatively easy way to test the interface in reality, then you should consider using another one. Paul Johnston
- 85. “…Wherever possible, an acceptance test should exercise the system end-to-end without directly calling its internal code. An end-to-end test interacts with the system only from the outside: through its interface…” Testing End-to-End
- 86. Legacy Monolith Amazon Kinesis Amazon Lambda Amazon CloudSearchAmazon API Gateway Amazon Lambda
- 87. Legacy Monolith Amazon Kinesis Amazon Lambda Amazon CloudSearchAmazon API Gateway Amazon Lambda Test Input
- 88. Legacy Monolith Amazon Kinesis Amazon Lambda Amazon CloudSearchAmazon API Gateway Amazon Lambda Test Input Validate
- 89. integration tests exercise system’s Integration with its external dependencies
- 90. acceptance tests exercise system End-to-End from the outside
- 91. integration tests differ from acceptance tests only in HOW the Lambda functions are invoked observation
- 95. CI/CD PIPELINE
- 96. “…We prefer to have the end-to-end tests exercise both the system and the process by which it’s built and deployed… This sounds like a lot of effort (it is), but has to be done anyway repeatedly during the software’s lifetime…” Testing End-to-End
- 97. me Deployment scripts that only live on the CI box is a disaster waiting to happen.
- 98. Jenkins build config deploys and tests unit + integration tests deploy acceptance tests
- 99. if [ "$1" = "deploy" ] && [ $# -eq 4 ]; then STAGE=$2 REGION=$3 PROFILE=$4 npm install AWS_PROFILE=$PROFILE 'node_modules/.bin/sls' deploy -s $STAGE -r $REGION …
- 100. if [ "$1" = "deploy" ] && [ $# -eq 4 ]; then STAGE=$2 REGION=$3 PROFILE=$4 npm install AWS_PROFILE=$PROFILE 'node_modules/.bin/sls' deploy -s $STAGE -r $REGION … install serverless framework as dev dependency
- 101. can be run locally & on the CI box
- 103. auto auto manual
- 104. LOGGING
- 106. 2016-07-12T12:24:37.571Z 994f18f9-482b-11e6-8668-53e4eab441ae GOT is off air, what do I do now?
- 107. 2016-07-12T12:24:37.571Z 994f18f9-482b-11e6-8668-53e4eab441ae GOT is off air, what do I do now? UTC Timestamp API Gateway Request Id your log message
- 109. me Logs are not easily searchable in CloudWatch Logs.
- 110. LOG OVERLOAD
- 111. CENTRALISE LOGS
- 112. CENTRALISE LOGS MAKE THEM EASILY SEARCHABLE
- 113. + + the elk stack
- 114. CloudWatch Logs
- 115. CloudWatch Logs AWS Lambda ELK stack
- 116. CloudWatch Events
- 117. CloudWatch Logs
- 119. DISTRIBUTED TRACING
- 121. “my followers didn’t receive my new post!” - a user
- 122. where could the problem be?
- 123. correlation IDs* * eg. request-id, user-id, yubl-id, etc.
- 125. kinesis client http client sns client
- 126. http://bit.ly/2k93hAj kinesis global.CONTEXT log.info(…) api-b global.CONTEXT global.CONTEXT global.CONTEXT x-correlation-id = … x-correlation-xxx = … API Gateway Kinesis SNS API Gateway API Gatewayapi-a api-c sns headers[“User-Agent”] headers[“Debug-Log-Enabled”] MessageAttributes: [ “x-correlation-id”: … “User-Agent”: … “Debug-Log-Enabled”: … ] global.CONTEXT headers[“User-Agent”] headers[“Debug-Log-Enabled”] headers[“x-correlation-id”] headers[“User-Agent”] headers[“Debug-Log-Enabled”] headers[“x-correlation-id”] data.__context capture forward function event
- 128. Amazon X-Ray
- 129. Amazon X-Ray
- 130. traces do not span over API Gateway
- 132. “where do I install monitoring agents?”
- 133. you can’t
- 134. • invocation Count • error Count • latency • throttling • granular to the minute • support custom metrics
- 135. • invocation Count • error Count • latency • throttling • granular to the minute • support custom metrics
- 139. Why not IOPipe? ! pervasive access to your entire application ! adds latency for tracking
- 140. me The only “background” processing you get are the capabilities the platform provides out of the box.
- 141. “how do I batch up and send logs/metrics in the background?”
- 142. you can’t (kinda)
- 143. console.log(“hydrating yubls from db…”); console.log(“fetching user info from user-api”); console.log(“MONITORING|1489795335|27.4|latency|user-api-latency”); console.log(“MONITORING|1489795335|8|count|yubls-served”); timestamp metric value metric type metric namemetrics logs
- 144. CloudWatch Logs AWS Lambda ELK stack logs metrics CloudWatch
- 145. CloudWatch Logs
- 146. CloudWatch Logs AWS Lambda ELK stack logs metrics CloudWatch memory used memory size billed duration
- 149. DASHBOARDS
- 152. Not Only CloudWatch
- 154. don’t put all your eggs in one basket aka. you don’t want your monitoring system to fail at the same time as the systems it monitors
- 155. CONFIG MANAGEMENT
- 156. Lambda
- 157. me Environment variables make it hard to share configurations across functions.
- 158. me Environment variables make it hard to implement fine-grained access to sensitive info.
- 160. couples ability to deploy with access to sensitive data, which often don’t overlap in a large engineering team or in a regulated environment
- 165. Why not consul or etcd? ! multiple EC2 instances in multi-AZ for HA ! have to manage servers, patch OS, patch software, etc. ! learning curve for configuring the service ! learning curve for using the CLI tools
- 167. SSM Parameter Store
- 168. SSM Parameter Store HTTPS role-based access encrypted in-flight
- 169. SSM Parameter Store encrypt role-based access
- 170. SSM Parameter Store encrypted at-rest
- 171. HTTPS role-based access SSM Parameter Store encrypted in-flight
- 172. SSM Parameter Store decrypt role-based access
- 174. Requirements for client library ! standardise and encapsulate how you manage configs ! supports client-side caching (fetch & cache at coldstart) ! invalidate cache at interval ! invalidate cache explicitly when staleness is detected
- 176. PRO TIPS
- 177. max 75 GB total deployment package size* * limit is per AWS region
- 178. Janitor Monkey
- 181. install Serverless framework as dev dependency at project level dev dependencies are excluded since 1.16.0
- 185. Amazon X-Ray 1st invocation 2nd invocation cold start
- 191. me C# and Java experiences ~100 times the cold start time of Python and also suffer from much higher standard deviation
- 192. me memory size improves cold start time linearly
- 193. AVOID COLDSTARTS
- 194. CloudWatch Event AWS Lambda
- 195. CloudWatch Event AWS Lambda ping ping ping ping
- 196. CloudWatch Event AWS Lambda ping ping ping ping
- 197. CloudWatch Event AWS Lambda ping ping ping ping HEALTH CHECKS?
- 198. AWS Lambda docs Take advantage of container re-use to improve the performance of your function. Make sure any externalized configuration or dependencies that your code retrieves are stored and referenced locally after initial execution. Limit the re-initialization of variables/objects on every invocation. Instead use static initialization/ constructor, global/static variables and singletons. Keep alive and reuse connections (HTTP, database, etc.) that were established during a previous invocation. http://amzn.to/2jzLmkb
- 199. max 5 mins execution time
- 202. AWS Lambda docs AWS Lambda polls your stream and invokes your Lambda function. Therefore, if a Lambda function fails, AWS Lambda attempts to process the erring batch of records until the time the data expires. http://amzn.to/2vs2lIg
- 203. vs processing halts until failed events are retried successfully/ expired from stream prioritize realtime-ness, retry failed events with best effort, then skip
- 204. SNS Kinesis SQS after 3 attempts share processing logic events are processed in chronological order failed events are retried out of sequence
- 208. AWS Lambda docs Each shard can support up to 5 transactions per second for reads, up to a maximum total data read rate of 2 MB per second. http://amzn.to/2ubyaot
- 209. AWS Lambda docs If your stream has 100 active shards, there will be 100 Lambda functions running concurrently. Then, each Lambda function processes events on a shard in the order that they arrive. http://amzn.to/2ubyaot
- 210. when no. of processors goes up…
- 211. ReadProvisionedThroughputExceeded can have too many Kinesis read operations…
- 212. ReadRecords.IteratorAge unpredictable spikes in read ‘latency’…
- 215. clever, but costly
- 216. new tool, new problems but they’re easier to deal with