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Serverless in production, an experience report (London js community)

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AWS Lambda has changed the way we deploy and run software, but this new 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?

In this talk Yan and Diana will discuss solutions to these challenges by drawing from real-world experience running Lambda in production and migrating from an existing monolithic architecture.

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Serverless in production, an experience report (London js community)

  1. 1. in production an experience reportan experience report what you should know before you go to production ServerlessServerless
  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. Diana Ionita Senior Developer Senior Developer Senior Developer
  6. 6. apr, 2016
  7. 7. 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
  8. 8. - Dan North “lead time to someone saying thank you is the only reputation metric that matters.”
  9. 9. “what would good look like for us?”
  10. 10. be small be fast have zero downtime have no lock-step DEPLOYMENTS SHOULD...
  11. 11. FEATURES SHOULD... be deployable independently be loosely-coupled
  12. 12. WE WANT TO... minimise cost for unused resources minimise ops effort reduce tech mess deliver visible improvements faster
  13. 13. nov, 2016
  14. 14. 170 Lambda functions in prod 1.2 GB deployment packages in prod 95% cost saving vs EC2 15x no. of prod releases per month
  15. 15. time is a good fit
  16. 16. 1st function in prod! time is a good fit
  17. 17. ? time is a good fit 1st function in prod!
  18. 18. ALERTING CI / CD TESTING LOGGING MONITORING
  19. 19. Practices ToolsPrinciples what is good? how to make it good? with what?
  20. 20. Principles outlast Tools
  21. 21. 170 functions WOOF! ? ? time is a good fit 1st function in prod!
  22. 22. SECURITY DISTRIBUTED TRACING CONFIG MANAGEMENT
  23. 23. evolving the PLATFORM
  24. 24. rebuilt search
  25. 25. Legacy Monolith Amazon Kinesis Amazon Lambda Amazon CloudSearch
  26. 26. Legacy Monolith Amazon Kinesis Amazon Lambda Amazon CloudSearchAmazon API Gateway Amazon Lambda
  27. 27. new analytics pipeline
  28. 28. Legacy Monolith Amazon Kinesis Amazon Lambda Google BigQuery
  29. 29. Legacy Monolith Amazon Kinesis Amazon Lambda Google BigQuery 1 developer, 2 days design production (his 1st serverless project)
  30. 30. Legacy Monolith Amazon Kinesis Amazon Lambda Google BigQuery “nothing ever got done this fast at Skype!” - Chris Twamley
  31. 31. - Dan North “lead time to someone saying thank you is the only reputation metric that matters.”
  32. 32. Rebuilt with Lambda
  33. 33. Rebuilt with Lambda
  34. 34. BigQuery
  35. 35. BigQuery
  36. 36. grapheneDB BigQuery
  37. 37. grapheneDB BigQuery
  38. 38. grapheneDB BigQuery
  39. 39. getting PRODUCTION READY
  40. 40. CHOOSE A FRAMEWORK DEPLOYMENT
  41. 41. http://serverless.com
  42. 42. https://github.com/awslabs/serverless-application-model
  43. 43. http://apex.run
  44. 44. https://apex.github.io/up
  45. 45. https://github.com/claudiajs/claudia
  46. 46. https://github.com/Miserlou/Zappa
  47. 47. http://gosparta.io/
  48. 48. TESTING
  49. 49. amzn.to/29Lxuzu
  50. 50. Level of Testing 1.Unit do our objects do the right thing? are they easy to work with?
  51. 51. Level of Testing 1.Unit 2.Integration does our code work against code we can’t change?
  52. 52. handler
  53. 53. handler test by invoking the handler
  54. 54. Level of Testing 1.Unit 2.Integration 3.Acceptance does the whole system work?
  55. 55. Level of Testing unit integration acceptance feedback confidence
  56. 56. “…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
  57. 57. “…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
  58. 58. Don’t Mock Types You Can’t Change Services
  59. 59. Paul Johnston The serverless approach to testing is different and may actually be easier. http://bit.ly/2t5viwK
  60. 60. LambdaAPI Gateway DynamoDB
  61. 61. LambdaAPI Gateway DynamoDB Unit Tests
  62. 62. LambdaAPI Gateway DynamoDB Unit Tests Mock/Stub
  63. 63. 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…
  64. 64. 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
  65. 65. But it slows down my feedback loop… IT’S NOT ABOUT YOU!
  66. 66. …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
  67. 67. “…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
  68. 68. Legacy Monolith Amazon Kinesis Amazon Lambda Amazon CloudSearchAmazon API Gateway Amazon Lambda
  69. 69. Legacy Monolith Amazon Kinesis Amazon Lambda Amazon CloudSearchAmazon API Gateway Amazon Lambda Test Input
  70. 70. Legacy Monolith Amazon Kinesis Amazon Lambda Amazon CloudSearchAmazon API Gateway Amazon Lambda Test Input Validate
  71. 71. integration tests exercise system’s Integration with its external dependencies my code
  72. 72. acceptance tests exercise system End-to-End from the outside my code
  73. 73. integration tests differ from acceptance tests only in HOW the Lambda functions are invoked observation
  74. 74. CI + CD PIPELINE
  75. 75. “the earlier you consider CI + CD, the more time you save in the long run” - me
  76. 76. “…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
  77. 77. “deployment scripts that only live on the CI box is a disaster waiting to happen” - me
  78. 78. Jenkins build config deploys and tests unit + integration tests deploy acceptance tests
  79. 79. 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
  80. 80. build.sh allows repeatable builds on both local & CI
  81. 81. Auto Auto Manual
  82. 82. LOGGING
  83. 83. 2016-07-12T12:24:37.571Z 994f18f9-482b-11e6-8668-53e4eab441ae GOT is off air, what do I do now?
  84. 84. 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
  85. 85. function name date function version
  86. 86. Yan Logs are not easily searchable in CloudWatch Logs.
  87. 87. LOG OVERLOAD
  88. 88. CENTRALISE LOGS
  89. 89. CENTRALISE LOGS MAKE THEM EASILY SEARCHABLE
  90. 90. + + the elk stack
  91. 91. CloudWatch Logs
  92. 92. CloudWatch Logs AWS Lambda ELK stack
  93. 93.
  94. 94. CloudWatch Events
  95. 95. CloudWatch Events CreateLogGroup subscribe-log-group Log group create-subscription stream ship-to-ELK capturedby
  96. 96. http://bit.ly/2f3zxQG
  97. 97. DISTRIBUTED TRACING
  98. 98. “my followers didn’t receive my new post!” - a user
  99. 99. where could the problem be?
  100. 100. correlation IDs* * eg. request-id, user-id, yubl-id, etc.
  101. 101. ROLL YOUR OWN CLIENTS
  102. 102. kinesis client http client sns client
  103. 103. http://bit.ly/2k93hAj
  104. 104. ROLL YOUR OWN CLIENTS X-RAY
  105. 105. Amazon X-Ray
  106. 106. Amazon X-Ray
  107. 107. traces do not span over API Gateway
  108. 108. MONITORING + ALERTING
  109. 109. “where do I install monitoring agents?”
  110. 110. you can’t
  111. 111. • invocation Count • error Count • latency • throttling • granular to the minute • support custom metrics
  112. 112. • same metrics as CW • better dashboard • support custom metrics https://www.datadoghq.com/blog/monitoring-lambda-functions-datadog/
  113. 113. my code
  114. 114. my code
  115. 115. my code internet internet press button something happens
  116. 116. “how do I batch up and send metrics in the background?”
  117. 117. you can’t (kinda)
  118. 118. 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
  119. 119. CloudWatch Logs AWS Lambda ELK stack logs metrics CloudWatch
  120. 120. http://bit.ly/2gGredx
  121. 121. DASHBOARDS
  122. 122. DASHBOARDS SET ALARMS
  123. 123. DASHBOARDS SET ALARMS TRACK APP-LEVEL METRICS
  124. 124. Not Only CloudWatch
  125. 125. “you really don't want your monitoring system to fail at the same time as the system it monitors” - Yan
  126. 126. CONFIG MANAGEMENT
  127. 127. easily and quickly propagate config changes
  128. 128. me Environment variables make it hard to share configurations across functions.
  129. 129. me Environment variables make it hard to implement fine-grained access to sensitive info.
  130. 130. CENTRALISED CONFIG SERVICE
  131. 131. config service goes here
  132. 132. SSM Parameter Store
  133. 133. sensitive data should be encrypted in-flight, and at rest (credentials, connection string, etc.)
  134. 134. role-based access
  135. 135. SSM Parameter Store HTTPS role-based access encrypted in-flight
  136. 136. SSM Parameter Store encrypt role-based access
  137. 137. SSM Parameter Store encrypted at-rest
  138. 138. HTTPS role-based access SSM Parameter Store encrypted in-flight
  139. 139. CENTRALISED CONFIG SERVICE CLIENT LIBRARY
  140. 140. fetch & cache at Cold Start
  141. 141. invalidate at interval + signal
  142. 142. http://bit.ly/2yLUjwd
  143. 143. PRO TIPS
  144. 144. max 75 GB total deployment package size* * limit is per AWS region
  145. 145. Janitor Monkey
  146. 146. Janitor Lambda http://bit.ly/2xzVu4a
  147. 147. disable versionFunctions in
  148. 148. install Serverless framework as dev dependency at project level dev dependencies are excluded since 1.16.0
  149. 149. http://bit.ly/2vzBqhC
  150. 150. http://amzn.to/2vtUkDU
  151. 151. UNDERSTAND COLDSTARTS
  152. 152. Amazon X-Ray 1st invocation 2nd invocation cold start
  153. 153. source: http://bit.ly/2oBEbw2
  154. 154. http://bit.ly/2rtCCBz
  155. 155. C# http://bit.ly/2rtCCBz
  156. 156. Java http://bit.ly/2rtCCBz
  157. 157. NodeJs, Python http://bit.ly/2rtCCBz
  158. 158. EMBRACE NODE.JS & PYTHON
  159. 159. what about type safety?
  160. 160. complexity ceiling of a Node.js app complexity
  161. 161. complexity ceiling of a Node.js app complexity referential transparency immutability as default type inference option types union types …
  162. 162. for managing complexity complexity ceiling of a Node.js app complexity referential transparency immutability as default type inference option types union types …
  163. 163. complexity ceiling of a Node.js app complexity complexity ceiling of a Node.js Lambda function
  164. 164. if you can limit the complexity of your solution, maybe you won’t need the tools for managing that complexity. me
  165. 165. AVOID COLDSTARTS
  166. 166. CloudWatch Event AWS Lambda
  167. 167. CloudWatch Event AWS Lambda ping ping ping ping
  168. 168. CloudWatch Event AWS Lambda ping ping ping ping
  169. 169. CloudWatch Event AWS Lambda ping ping ping ping HEALTH CHECKS?
  170. 170. AVOID HARD ASSUMPTIONS ABOUT FUNCTION LIFETIME
  171. 171. USE STATE FOR OPTIMISATION
  172. 172. max 5 mins execution time
  173. 173. USE RECURSION FOR LONG RUNNING TASKS
  174. 174. CONSIDER PARTIAL FAILURES
  175. 175. “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
  176. 176. should function fail on partial/any failures?
  177. 177. SNS Kinesis SQS after 3 attempts share processing logic events are processed in chronological order failed events are retried out of sequence
  178. 178. PROCESS SQS WITH RECURSIVE FUNCTIONS
  179. 179. http://bit.ly/2npomX6
  180. 180. AVOID HOT KINESIS STREAMS
  181. 181. “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
  182. 182. “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
  183. 183. when no. of processors goes up…
  184. 184. ReadProvisionedThroughputExceeded can have too many Kinesis read operations…
  185. 185. ReadRecords.IteratorAge unpredictable spikes in read ‘latency’…
  186. 186. can kinda workaround…
  187. 187. http://bit.ly/2uv5LsH
  188. 188. clever, but costly
  189. 189. 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
  190. 190. @theburningmonk theburningmonk.com github.com/theburningmonk
  191. 191. API Gateway and Kinesis Authentication & authorisation (IAM, Cognito) Testing Running & Debugging functions locally Log aggregation Monitoring & Alerting X-Ray Correlation IDs CI/CD Performance and Cost optimisation Error Handling Configuration management VPC Security Leading practices (API Gateway, Kinesis, Lambda) http://bit.ly/2AA5zzk
  192. 192. API Gateway and Kinesis Authentication & authorisation (IAM, Cognito) Testing Running & Debugging functions locally Log aggregation Monitoring & Alerting X-Ray Correlation IDs CI/CD Performance and Cost optimisation Error Handling Configuration management VPC Security Leading practices (API Gateway, Kinesis, Lambda) http://bit.ly/2AA5zzk get 40% off with: ytcui

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