Serverless Design Patterns Guide
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Serverless technologies like AWS Lambda has drastically simplified the task of building reactive systems - drop a file into S3 and a Lambda function would be triggered to process it, push an event into a Kinesis stream and magically it'll be processed by a Lambda function in real-time, you can even use Lambda to automate the process of auditing and securing your AWS account by automatically reacting to rule violations to your security policy. Join us in this talk to see some architectural design patterns that have emerged with AWS Lambda, and learn how to pick the right event source based on the tradeoffs you want. Amongst the many patterns we'll explore, here are a few to whet your appetite : pub-sub, cron, push-pull, saga and decoupled invocation.
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Serverless Design Patterns Guide
- 1. SERVERLESS DESIGN PATTERNS by YAN CUI @theburningmonk
- 3. 2014
- 9. “Serverless”
- 11. Gojko Adzic It is serverless the same way WiFi is wireless. http://bit.ly/2yQgwwb
- 12. Serverless means… don’t pay for it if no-one uses it don’t need to worry about scaling don’t need to provision and manage servers
- 13. “Function-as-a-Service” AWS Lambda Azure Functions Google Cloud Functions Auth0 Webtask Spotinst Functions Kubeless IBM Cloud Functions
- 14. AWS Lambda
- 15. AWS Lambda API Gateway IOT SNS Kinesis CloudWatch
- 19. SERVERLESS WILL FUNDAMENTALLY CHANGE HOW WE BUILD BUSINESS AROUND TECHNOLOGY AND HOW YOU CODE. Simon Wardley
- 20. more Scalable (and scales faster!)
- 21. Cheaper (don’t pay for idle servers)
- 22. Resilience (built-in redundancy and multi-AZ)
- 23. idea production choose language + framework master language + framework figure out deployment configure AMI configure ELB configure autoscaling capacity planning over-provision for launch are we doing microservices? configure CI/CD
- 24. idea production choose language + framework master language + framework figure out deployment configure AMI configure ELB configure autoscaling capacity planning over-provision for launch are we doing microservices? configure CI/CD
- 25. idea production greater Velocity from idea to product
- 27. Less ops responsibility on your shoulders
- 31. events are an enabler for COMPOSABILITY
- 34. PATTERNS
- 35. WARNING!!
- 36. A DESIGN PATTERN IS NOT... A RECIPE FOR SUCCESS
- 37. Pattern /pat(ə)n/ A pattern is the repeated or regular way in which something happens or is done.
- 38. UNDERSTAND YOUR PROBLEMS AND CONSTRAINTS OVER FOLLOWING A PATTERN. me
- 40. I’m not trying to sell you a “magic” elixir!
- 41. there are no silver bullets
- 42. Pattern /pat(ə)n/ A pattern is the repeated or regular way in which something happens or is done.
- 43. CRON
- 48. OPS AUTOMATION
- 49. AWS Lambda CloudWatch Logs
- 50. CloudWatch Logs
- 51. AWS Lambda CloudWatch Logs AWS Lambda
- 52. CloudWatch Logs
- 53. AWS Lambda CloudWatch Logs CloudTrail
- 57. AWS Lambda CloudWatch Logs CloudWatch Events CloudTrail AWS Lambda
- 58. AWS Lambda CloudWatch Logs CloudWatch Events CloudTrail AWS Lambda AWS Lambda
- 59. AWS Lambda CloudWatch Logs CloudWatch Events CloudTrail AWS Lambda AWS Lambda
- 60. auto-update CloudWatch retention policy auto-create alarms for new APIs auto-create dashboards for new APIs alert on suspicious console logins alert on EC2 activities in unused regions …
- 61. WEB APPS
- 63. API Gateway AWS Lambda DynamoDBRoute53 CloudFront S3 Browser
- 64. API Gateway AWS Lambda DynamoDBRoute53 CloudFront S3 Browser Cognito
- 65. Federated Identities Sync User Flows Registration Verify email/phone Secure sign-in Forgotten password Change password Sign out Cognito User Pools
- 66. Federated Identities Sync Leading Practices Secure password handling with SRP protocol Encrypt all data server-side Password policies Token-based authentication MFA Support CAPTCHA Cognito User Pools
- 67. what is Cognito? Cognito Federated Identities Cognito User Pools Facebook TwitterGoogle … identity providers authenticate
- 68. what is Cognito? Cognito Federated Identities Cognito User Pools Facebook TwitterGoogle … identity providers authenticate token
- 69. what is Cognito? Cognito Federated Identities Cognito User Pools Facebook TwitterGoogle … identity providers authenticate token token
- 70. validate what is Cognito? Cognito Federated Identities Cognito User Pools Facebook TwitterGoogle … identity providers authenticate token token
- 71. validate what is Cognito? Cognito Federated Identities Cognito User Pools Facebook TwitterGoogle … identity providers authenticate token token IAM credential
- 72. validate what is Cognito? Cognito Federated Identities Cognito User Pools Facebook TwitterGoogle … identity providers API Gateway S3 DynamoDB SNSIOT Kinesis authenticate token token IAM credential IAM credential
- 73. what about Multi-Region support?
- 76. API Gateway AWS Lambda DynamoDB Route53 CloudFront S3 Browser API Gateway AWS Lambda eu-west-1 us-east-1
- 78. DATA LAKES
- 79. S3 Buckets
- 80. S3 Buckets IAM
- 83. S3 BucketsKinesis Streams Kinesis Firehose KMS MacieIAM
- 84. S3 BucketsKinesis Streams Kinesis Firehose AWS Lambda KMS MacieIAM
- 85. S3 BucketsKinesis Streams Kinesis Firehose AWS Lambda KMS MacieIAM AWS Lambda
- 86. S3 BucketsKinesis Streams Kinesis Firehose AWS Lambda AWS Lambda KMS MacieIAM AWS Lambda
- 87. S3 BucketsKinesis Streams Kinesis Firehose AWS Lambda AWS Lambda KMS MacieIAM AWS Lambda DynamoDB ElasticSearch
- 88. S3 BucketsKinesis Streams Kinesis Firehose AWS Lambda AWS Lambda KMS MacieIAM AWS Lambda Google BigQuery
- 89. S3 BucketsKinesis Streams Kinesis Firehose AWS Lambda AWS Lambda Athena QuickSight KMS MacieIAM AWS Lambda
- 90. S3 BucketsKinesis Streams Kinesis Firehose AWS Lambda AWS Lambda Athena QuickSight KMS MacieIAM AWS Lambda
- 92. Decoupled Invocation How can a service handle normal request loads, peak request loads, and a continuous period of high load without failing?
- 93. business logic requires expensive processing
- 94. API Gateway max integration timeout is 29 seconds http://amzn.to/2BwW5Bx
- 95. downstream systems not as scalable
- 97. decouple reply from the initial request
- 100. workerAPIClient POST /do_something 202 /result_location GET /result_location 202 /result_location do work
- 101. workerAPIClient POST /do_something 202 /result_location GET /result_location 202 /result_location do work work done
- 102. workerAPIClient POST /do_something 202 /result_location GET /result_location 202 /result_location do work work done GET /result_location 200 OK
- 103. amortises spikes in load
- 105. allows fast response back to caller whilst promises to finish work later
- 107. allows flexible retry strategies by removing the urgency of having to reply to caller right away
- 108. DynamoDB API Gateway POST task id created at result xxx xxx <null> xxx xxx <null> … … … task results not ready PutItem
- 109. DynamoDB API Gateway POST task id created at result xxx xxx <null> xxx xxx <null> … … … task results not ready SQS
- 110. DynamoDB API Gateway 202 task id created at result xxx xxx <null> xxx xxx <null> … … … task results not ready SQS
- 111. use “created at” timestamp to timeout polling requests and avoid infinite retry
- 112. DynamoDBAPI Gateway GET task id created at result xxx xxx <null> xxx xxx <null> … … … task results not ready SQS
- 113. DynamoDBAPI Gateway 202 task id created at result xxx xxx <null> xxx xxx <null> … … … task results not ready SQS
- 114. DynamoDB task id created at result xxx { … } xxx <null> … … task results done UpdateItem xxx xxx … SQS
- 115. DynamoDBAPI Gateway GET task id created at result xxx xxx { … } xxx xxx <null> … … … task results done
- 116. DynamoDBAPI Gateway 200 { … }
- 117. also consider using Kinesis Streams or DynamoDB Streams as queue
- 118. but SNS is a poor choice (invocation-per-message means no amortisation)
- 119. PUB-SUB
- 121. one message, many consumers
- 122. good for decoupling data processing
- 123. independent failures partial failures are easier to manage
- 124. SNS, Kinesis Streams, DynamoDB Streams, etc…
- 125. SNS
- 126. 2 retries then DLQ SNS
- 127. 2 retries then DLQ invocation per msg SNS
- 128. 2 retries then DLQ invocation per msg might run into throttling limits consider impact on downstream SNS
- 129. suffers from temporal issues
- 130. msg/s time max throughput erred and retried
- 131. msg/s time max throughput erred and retried
- 133. Kinesis
- 135. retried until success invocation per shard Kinesis
- 136. better handling of temporal issues
- 140. Kinesis Streams or DynamoDB Streams?
- 141. what is your source of truth?
- 142. limited to events from one table
- 143. records describe DynamoDB events, not events from your domain
- 144. auto-scales no. of shards
- 145. cannot extend data retention beyond 24 hours
- 146. charged based on no. of requests ($0.02 per 100,000 read request units)
- 148. 1 msg/s for a month, 1KB per msg $0.47 1 x 60s x 60m x 24hr x 30days @ $0.014 per mil + 24hrs x 30days @ $0.015 per hr $10.836 1 x 60s x 60m x 24hr x 30days @ $0.5 per mil $1.296 DynamoDB StreamsSNSKinesis Streams 1 Write Capacity Unit @ $0.47 per unit
- 149. 1k msg/s for a month, 1KB per msg 1k x 60s x 60m x 24hr x 30days @ $0.014 per mil + 24hrs x 30days @ $0.015 per hr $47.088 1k x 60s x 60m x 24hr x 30days @ $0.5 per mil $1296.00 DynamoDB StreamsSNSKinesis Streams $470.00 1k Write Capacity Unit @ $0.47 per unit
- 150. DON’T take these projections at face value!
- 151. SNS
- 152. no restriction on destination target SNS
- 153. no restriction on destination target need to handle partial failures & retries SNS
- 154. PUSH-PULL
- 156. tasks are distributed to pool of consumers one task, one consumer
- 157. good for divide-and-conquer to improve throughput and processing time
- 158. one function, many concurrent invocations SNS
- 159. SQS one function, many concurrent invocations
- 160. manual polling not a supported event source DLQ support SQS
- 161. manual polling not a supported event source DLQ support invocation per “poller” SQS
- 162. find out more at: http://bit.ly/2npomX6
- 163. consider the cost implications at scale
- 164. 1 msg/s for a month, 1KB per msg 1 x 60s x 60m x 24hr x 30days @ $0.4 per mil $1.0368 1 x 60s x 60m x 24hr x 30days @ $0.014 per mil + 24hrs x 30days @ $0.015 per hr $10.836 1 x 60s x 60m x 24hr x 30days @ $0.5 per mil $1.296 SQSSNSKinesis
- 165. 1k msg/s for a month, 1KB per msg 1k x 60s x 60m x 24hr x 30days @ $0.014 per mil + 24hrs x 30days @ $0.015 per hr $47.088 1k x 60s x 60m x 24hr x 30days @ $0.4 per mil $1036.80 1k x 60s x 60m x 24hr x 30days @ $0.5 per mil $1296.00 SQSSNSKinesis
- 167. one function, many concurrent invocations SNS
- 168. need mechanism for collecting results
- 169. one function, many concurrent invocations job id task no. result xxx 001 xxx xxx 002 xxx xxx 003 xxx xxx 004 xxx … … … job results each invocation saves its own result SNS DynamoDB 001 002 003 004
- 170. one function, many concurrent invocations max item size is 400KB SNS job id task no. result xxx 001 xxx xxx 002 xxx xxx 003 xxx xxx 004 xxx … … … job results each invocation saves its own result DynamoDB 001 002 003 004
- 171. one function, many concurrent invocations invocations save results in the same folder SNS S3 001 002 003 004 max object size is 5TB!!
- 172. how do we know when all the results are in?
- 173. one function, many concurrent invocations job id tasks left xxx 42 yyy 81 … … job status atomic decrement no. of tasks left the parent function initialises no. of tasks left SNS DynamoDB 001 002 003 004
- 174. job id tasks left xxx 42 yyy 0 … … job status SNS DynamoDB one function, many concurrent invocations all results are in 001 002 003 004
- 175. DynamoDB one function, many concurrent invocations invocation that sees “tasks left” reach 0 SNS SNS trigger reducer 001 002 003 004
- 176. what about Step Functions?
- 177. doesn’t support spawning arbitrary no. of functions in a step yet
- 178. SAGA
- 179. pattern for managing failures where each action has a compensating action for rollback
- 181. Begin transaction Start book hotel request End book hotel request Start book flight request End book flight request Start book car rental request End book car rental request End transaction
- 182. model actions and compensating actions as Lambda functions
- 183. actions
- 184. compensating actions
- 185. state machine in AWS Step Functions as the coordinator for the saga
- 187. input
- 192. source code available here: https://github.com/theburningmonk/lambda-saga-pattern
- 194. 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) Canary deployments http://bit.ly/prod-ready-serverless get 40% off with: ytcui