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Serverless in production, an experience report (BuildStuff)

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AWS Lambda has changed the way we deploy and run software, but the serverless paradigm has created new challenges to old problems: How do you test a cloud-hosted function locally? How do you monitor them? What about logging and config management? And how do we start migrating from existing architectures?

Yan Cui shares solutions to these challenges, drawing on his experience running Lambda in production and migrating from an existing monolithic architecture.

Published in: Technology
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Serverless in production, an experience report (BuildStuff)

  1. 1. from the TRENCHESTRENCHES what you should know before you go to production AWS LAMBDAAWS LAMBDA
  2. 2. Yan Cui http://theburningmonk.com @theburningmonk AWS user since 2009
  3. 3. Yan Cui Server Architect Principal Engineer Lead Developer Senior Developer http://theburningmonk.com @theburningmonk Senior Developer
  4. 4. Yan Cui Server Architect Principal Engineer Lead Developer Senior Developer http://theburningmonk.com @theburningmonk Senior Developer
  5. 5. apr, 2016
  6. 6. hidden complexities and dependencies low utilisation to leave room for traffic spikes EC2 scaling is slow, so scale earlier lots of cost for unused resources up to 30 mins for deployment deployment required downtime
  7. 7. - Dan North “lead time to someone saying thank you is the only reputation metric that matters.”
  8. 8. “what would good look like for us?”
  9. 9. be small be fast have zero downtime have no lock-step DEPLOYMENTS SHOULD...
  10. 10. FEATURES SHOULD... be deployable independently be loosely-coupled
  11. 11. WE WANT TO... minimise cost for unused resources minimise ops effort reduce tech mess deliver visible improvements faster
  12. 12. nov, 2016
  13. 13. 170 Lambda functions in prod 1.2 GB deployment packages in prod 95% cost saving vs EC2 15x no. of prod releases per month
  14. 14. time is a good fit
  15. 15. 1st function in prod! time is a good fit
  16. 16. ? time is a good fit 1st function in prod!
  17. 17. ALERTING CI / CD TESTING LOGGING MONITORING
  18. 18. Practices ToolsPrinciples what is good? how to make it good? with what?
  19. 19. Principles outlast Tools
  20. 20. 170 functions WOOF! ? ? time is a good fit 1st function in prod!
  21. 21. SECURITY DISTRIBUTED TRACING CONFIG MANAGEMENT
  22. 22. evolving the PLATFORM
  23. 23. rebuilt search
  24. 24. Legacy Monolith Amazon Kinesis Amazon Lambda Amazon CloudSearch
  25. 25. Legacy Monolith Amazon Kinesis Amazon Lambda Amazon CloudSearchAmazon API Gateway Amazon Lambda
  26. 26. new analytics pipeline
  27. 27. Legacy Monolith Amazon Kinesis Amazon Lambda Google BigQuery
  28. 28. Legacy Monolith Amazon Kinesis Amazon Lambda Google BigQuery 1 developer, 2 days design production (his 1st serverless project)
  29. 29. Legacy Monolith Amazon Kinesis Amazon Lambda Google BigQuery “nothing ever got done this fast at Skype!” - Chris Twamley
  30. 30. - Dan North “lead time to someone saying thank you is the only reputation metric that matters.”
  31. 31. Rebuilt with Lambda
  32. 32. Rebuilt with Lambda
  33. 33. BigQuery
  34. 34. BigQuery
  35. 35. grapheneDB BigQuery
  36. 36. grapheneDB BigQuery
  37. 37. grapheneDB BigQuery
  38. 38. getting PRODUCTION READY
  39. 39. CHOOSE A FRAMEWORK DEPLOYMENT
  40. 40. http://serverless.com
  41. 41. https://github.com/awslabs/serverless-application-model
  42. 42. http://apex.run
  43. 43. https://apex.github.io/up
  44. 44. https://github.com/claudiajs/claudia
  45. 45. https://github.com/Miserlou/Zappa
  46. 46. http://gosparta.io/
  47. 47. TESTING
  48. 48. amzn.to/29Lxuzu
  49. 49. Level of Testing 1.Unit do our objects do the right thing? are they easy to work with?
  50. 50. Level of Testing 1.Unit 2.Integration does our code work against code we can’t change?
  51. 51. handler
  52. 52. handler test by invoking the handler
  53. 53. Level of Testing 1.Unit 2.Integration 3.Acceptance does the whole system work?
  54. 54. Level of Testing unit integration acceptance feedback confidence
  55. 55. “…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
  56. 56. “…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
  57. 57. Don’t Mock Types You Can’t Change Services
  58. 58. Paul Johnston The serverless approach to testing is different and may actually be easier. http://bit.ly/2t5viwK
  59. 59. LambdaAPI Gateway DynamoDB
  60. 60. LambdaAPI Gateway DynamoDB Unit Tests
  61. 61. LambdaAPI Gateway DynamoDB Unit Tests Mock/Stub
  62. 62. is our request correct? is the request mapping set up correctly?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…
  63. 63. 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
  64. 64. But it slows down my feedback loop… IT’S NOT ABOUT YOU!
  65. 65. …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
  66. 66. “…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
  67. 67. Legacy Monolith Amazon Kinesis Amazon Lambda Amazon CloudSearchAmazon API Gateway Amazon Lambda
  68. 68. Legacy Monolith Amazon Kinesis Amazon Lambda Amazon CloudSearchAmazon API Gateway Amazon Lambda Test Input
  69. 69. Legacy Monolith Amazon Kinesis Amazon Lambda Amazon CloudSearchAmazon API Gateway Amazon Lambda Test Input Validate
  70. 70. integration tests exercise system’s Integration with its external dependencies my code
  71. 71. acceptance tests exercise system End-to-End from the outside my code
  72. 72. integration tests differ from acceptance tests only in HOW the Lambda functions are invoked observation
  73. 73. CI + CD PIPELINE
  74. 74. “the earlier you consider CI + CD, the more time you save in the long run” - me
  75. 75. “…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
  76. 76. “deployment scripts that only live on the CI box is a disaster waiting to happen” - me
  77. 77. Jenkins build config deploys and tests unit + integration tests deploy acceptance tests
  78. 78. 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 elif [ "$1" = "int-test" ] && [ $# -eq 4 ]; then STAGE=$2 REGION=$3 PROFILE=$4 npm install AWS_PROFILE=$PROFILE npm run int-$STAGE elif [ "$1" = "acceptance-test" ] && [ $# -eq 4 ]; then STAGE=$2 REGION=$3 PROFILE=$4 npm install AWS_PROFILE=$PROFILE npm run acceptance-$STAGE else usage exit 1 fi
  79. 79. build.sh allows repeatable builds on both local & CI
  80. 80. Auto Auto Manual
  81. 81. LOGGING
  82. 82. 2016-07-12T12:24:37.571Z 994f18f9-482b-11e6-8668-53e4eab441ae GOT is off air, what do I do now?
  83. 83. 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
  84. 84. function name date function version
  85. 85. me Logs are not easily searchable in CloudWatch Logs.
  86. 86. LOG OVERLOAD
  87. 87. CENTRALISE LOGS
  88. 88. CENTRALISE LOGS MAKE THEM EASILY SEARCHABLE
  89. 89. + + the elk stack
  90. 90. CloudWatch Logs
  91. 91. CloudWatch Logs AWS Lambda ELK stack
  92. 92. CloudWatch Events
  93. 93. http://bit.ly/2f3zxQG
  94. 94. DISTRIBUTED TRACING
  95. 95. “my followers didn’t receive my new post!” - a user
  96. 96. where could the problem be?
  97. 97. correlation IDs* * eg. request-id, user-id, yubl-id, etc.
  98. 98. ROLL YOUR OWN CLIENTS
  99. 99. kinesis client http client sns client
  100. 100. http://bit.ly/2k93hAj
  101. 101. ROLL YOUR OWN CLIENTS X-RAY
  102. 102. Amazon X-Ray
  103. 103. Amazon X-Ray
  104. 104. traces do not span over API Gateway
  105. 105. http://bit.ly/2s9yxmA
  106. 106. MONITORING + ALERTING
  107. 107. “where do I install monitoring agents?”
  108. 108. you can’t
  109. 109. • invocation Count • error Count • latency • throttling • granular to the minute • support custom metrics
  110. 110. • same metrics as CW • better dashboard • support custom metrics https://www.datadoghq.com/blog/monitoring-lambda-functions-datadog/
  111. 111. my code
  112. 112. my code
  113. 113. my code internet internet press button something happens
  114. 114. “how do I batch up and send logs in the background?”
  115. 115. you can’t (kinda)
  116. 116. 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
  117. 117. CloudWatch Logs AWS Lambda ELK stack logs metrics CloudWatch
  118. 118. http://bit.ly/2gGredx
  119. 119. DASHBOARDS
  120. 120. DASHBOARDS SET ALARMS
  121. 121. DASHBOARDS SET ALARMS TRACK APP-LEVEL METRICS
  122. 122. Not Only CloudWatch
  123. 123. “you really don't want your monitoring system to fail at the same time as the system it monitors” - me
  124. 124. CONFIG MANAGEMENT
  125. 125. easily and quickly propagate config changes
  126. 126. me Environment variables make it hard to share configurations across functions.
  127. 127. me Environment variables make it hard to implement fine-grained access to sensitive info.
  128. 128. CENTRALISED CONFIG SERVICE
  129. 129. config service goes here
  130. 130. SSM Parameter Store
  131. 131. sensitive data should be encrypted in-flight, and at rest (credentials, connection string, etc.)
  132. 132. role-based access
  133. 133. SSM Parameter Store HTTPS role-based access encrypted in-flight
  134. 134. SSM Parameter Store encrypt role-based access
  135. 135. SSM Parameter Store encrypted at-rest
  136. 136. HTTPS role-based access SSM Parameter Store encrypted in-flight
  137. 137. CENTRALISED CONFIG SERVICE CLIENT LIBRARY
  138. 138. fetch & cache at Cold Start
  139. 139. invalidate at interval + signal
  140. 140. http://bit.ly/2yLUjwd
  141. 141. PRO TIPS
  142. 142. max 75 GB total deployment package size* * limit is per AWS region
  143. 143. Janitor Monkey
  144. 144. Janitor Lambda http://bit.ly/2xzVu4a
  145. 145. disable versionFunctions in
  146. 146. install Serverless framework as dev dependency at project level dev dependencies are excluded since 1.16.0
  147. 147. http://bit.ly/2vzBqhC
  148. 148. http://amzn.to/2vtUkDU
  149. 149. UNDERSTAND COLDSTARTS
  150. 150. Amazon X-Ray 1st invocation 2nd invocation cold start
  151. 151. source: http://bit.ly/2oBEbw2
  152. 152. http://bit.ly/2rtCCBz
  153. 153. C# http://bit.ly/2rtCCBz
  154. 154. Java http://bit.ly/2rtCCBz
  155. 155. NodeJs, Python http://bit.ly/2rtCCBz
  156. 156. EMBRACE NODE.JS & PYTHON
  157. 157. what about type safety?
  158. 158. complexity ceiling of a Node.js app complexity
  159. 159. complexity ceiling of a Node.js app complexity referential transparency immutability as default type inference option types union types …
  160. 160. for managing complexity complexity ceiling of a Node.js app complexity referential transparency immutability as default type inference option types union types …
  161. 161. complexity ceiling of a Node.js app complexity complexity ceiling of a Node.js Lambda function
  162. 162. if you can limit the complexity of your solution, maybe you won’t need the tools for managing that complexity. me
  163. 163. AVOID COLDSTARTS
  164. 164. CloudWatch Event AWS Lambda
  165. 165. CloudWatch Event AWS Lambda ping ping ping ping
  166. 166. CloudWatch Event AWS Lambda ping ping ping ping
  167. 167. CloudWatch Event AWS Lambda ping ping ping ping HEALTH CHECKS?
  168. 168. AVOID HARD ASSUMPTIONS ABOUT FUNCTION LIFETIME
  169. 169. USE STATE FOR OPTIMISATION
  170. 170. max 5 mins execution time
  171. 171. USE RECURSION FOR LONG RUNNING TASKS
  172. 172. CONSIDER PARTIAL FAILURES
  173. 173. “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://docs.aws.amazon.com/lambda/latest/dg/retries-on-errors.html
  174. 174. should function fail on partial/any failures?
  175. 175. SNS Kinesis SQS after 3 attempts share processing logic events are processed in chronological order failed events are retried out of sequence
  176. 176. PROCESS SQS WITH RECURSIVE FUNCTIONS
  177. 177. http://bit.ly/2npomX6
  178. 178. AVOID HOT KINESS STREAMS
  179. 179. “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://docs.aws.amazon.com/streams/latest/dev/service-sizes-and-limits.html
  180. 180. “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://docs.aws.amazon.com/lambda/latest/dg/concurrent-executions.html
  181. 181. when no. of processors goes up…
  182. 182. ReadProvisionedThroughputExceeded can have too many Kinesis read operations…
  183. 183. ReadRecords.IteratorAge unpredictable spikes in read ‘latency’…
  184. 184. can kinda workaround…
  185. 185. http://bit.ly/2uv5LsH
  186. 186. clever, but costly
  187. 187. for subsystems that don’t have to be realtime, or are task- based (ie. order doesn’t matter), consider other triggers such as S3 or SNS.me
  188. 188. @theburningmonk theburningmonk.com github.com/theburningmonk
  189. 189. @theburningmonk theburningmonk.com github.com/theburningmonk http://bit.ly/2yQZj1H all my blog posts on Lambda

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