Trends and development practices in Serverless architectures
2 likes461 views
AWS ISV Event - Unlocking Business Agility with the AWS Serverless Application Model Matt Fellows, Principal Consultant from DiUS will talk about the evolution to serverless architectures, and discuss key development and testing practices for these modern distributed systems
![Lambda
Handler
Challenges > Vendor lock-in > Lambda Anti-pattern
{
"Records": [
{
"EventVersion": "1.0",
"EventSubscriptionArn": "somearn",
"EventSource": "aws:sns",
"Sns": {
...
}
}
]
}
{
"Success": true
}](https://image.slidesharecdn.com/awssydneyworkshop-2018-06-08-180608033305/85/Trends-and-development-practices-in-Serverless-architectures-40-320.jpg)
More Related Content
What's hot (15)
Similar to Trends and development practices in Serverless architectures (20)
More from DiUS (20)
Recently uploaded (20)
Trends and development practices in Serverless architectures
- 1. Testing large-scale, serverless and asynchronous systems Matt Fellows @matthewfellows ...without end-to-end integrated tests! #AWSAgility
- 3. WHAT WE ARE KNOWN FOR 3 Microservices Evolution Drivers for levelling up ● Increase time-to-value ● Increase utilisation / cost reduction ● Raise abstraction; focus on composition ● Scale product teams ● Massively distributed, real-time apps ● API contracts (e.g. OAS) ● Ubiquity of cloud computing ● Rise of containers ● Unreliable networking / components ● Rise of the Service Mesh ● Improved observability Why Serverless? > Drivers
- 4. Trends
- 5. 5 Data Pipelines Trends > Data pipelines
- 6. 6 Trends > Data pipelines
- 7. 7 https://aws.amazon.com/blogs/big-data/automating-analytic-workflows-on-aws/ Trends > Data pipelines
- 8. 8 https://www.slideshare.net/nateware/aws-gdc2015-gameanalyticsfinal Trends > Data pipelines
- 9. 9 Trends > Data pipelines > Before Systems of Record Integration / Middleware APIs Presentation Synchronous, coupled invocation Data locked here
- 10. 10 Trends > Data pipelines > After System of Record Event API Local cache / materialised view API 3. Event processed into local view of data 1. Change of system state 2. Event is shared
- 11. Observations Architecture > Microservices ● Democratisation of data ○ “Everyone gets a data” ● Hollywood Principle ● Pipelines are the new batch ● Prerequisite for AI/ML ● Composition and enrichment ● Lambda to “glue” steps together
- 12. 12 IT Ops. Automation Trends > IT Ops Automation
- 13. Before... ● Ad-hoc ● Cron jobs running on instances ● Scripts > code ● Shared “Job” machines, with broad security permissions and “all-the-tools” ● Lots of manual “glue” and orchestration Trends > IT Ops Automation
- 14. 14 Trends > IT Ops Automation Decide Alarm Schedule Event subscription Notify Pagerduty Act Isolate instance from ASG Ship logs to Splunk Offsite backup Orient Security Analysis Application Anomaly / Canary Detection Policy Violation Chaos Engineering Observe Flow Logs CloudTrail CloudWatch Logs Application Event Configured Rule
- 15. New approach ● Scheduled Lambda to replace “cron” jobs ● Real-time cron - event-driven ● Function written and deployed as code - first class citizens Rise of the OODA loop Trends > IT Ops Automation
- 16. 16 The new uService Trends > Microservices
- 17. 17 Trends > Microservices > Before Instances Team 1 Team 2 Team 3 Team ...
- 18. 18 API Gateway Trends > Microservices > Before Services Services Team 1: Orders Team 2: Identity Services Team ... Team 3: Experience
- 19. 19 Trends > Microservices > After > New Patterns API External Events API Outside World Microservice Interface API Master Data API Inside bounded context Event Emitters API Materialised view / cache Events and Processing Data Event Handlers Processing Offline Processing
- 20. 20 Provisioning Amazon ML Trends > Microservices > After > Example Team 1 Bounded Context Place Order API External Events Order Status API Outside World Internal Events Microservice Interface Data, Events and Processing Suggestions API Publish Event to external subscribers Insights / Predictions Customer / Other Event Orders Push API Inside bounded context CRM Materialised view of customer Provisioning Event External Events … API
- 21. 21 Trends > Microservices > Evolution Sizeofthing Number of communicating things Monolith SOA Serverless Microservices Fn Luckily, built on the same primitive!
- 22. Observations Architecture > Microservices ● Microservices still a thing ○ ..but are now just the interface of the iceberg ● Further decomposition of services into smaller functions ● Event-driven + asynchronous > synchronous invocation ● Lambda and managed services as “glue” ● Architectural composition BUT - More things to manage
- 23. Summary Architecture > Microservices ● Serverless as a higher-order system ○ Composition ● IT Operations Automation ○ Better discipline (OODA) ○ Everything as code ● Microservices still a thing, new designs emerging ○ Event-driven and loosely coupled ○ “Iceberg” patterns
- 24. 24 Much Compose! So speed! Architecture > Functions + Serverless (Cloud Native)Architecture > Functions + Serverless (Cloud Native)
- 25. 25 New challenges Architecture > Functions + Serverless (Cloud Native)
- 26. 26 If you can’t build a good monolith you shouldn’t be doing microservices Architecture > Microservices
- 27. ...the µServices ride ● Ability to write a modular monolith ● Strong grasp on your domain model ● Ability to design loosely coupled services ○ = state + transactions ● Ability to scale and decouple teams ● Ability to deploy continuously ● A strong “DevOps” culture ● Be comfortable with decentralised, complex systems + uncertainty Architecture > Microservices
- 28. 28 If you can’t build good microservices you shouldn’t be doing serverless Architecture > Functions + Serverless (Cloud Native)
- 29. 29 What practices do we need in this new world? Architecture > Functions + Serverless (Cloud Native)
- 31. 31 Demo: AWS Meetup Lounge CloudFront API Gateway Authentication You! awslounge.onegeek.com.au Twitter Fetch Twitter feed Twitter Push IoT Message Broker Sentiment Analysis Checkpoint Amazon ML #AWSAgility
- 32. 32 Demo: AWS Meetup Lounge Demo
- 34. 34 Smaller functions = more things! Challenges > Async
- 35. WHAT WE ARE KNOWN FOR 35 Options ● ... Challenges ● Observability + Tracing ● Structured logging ● Shift responsibility into platform ● Good acceptance tests Challenges > Vendor lock-in
- 36. 36 Vendor lock-in Challenges > Vendor lock-in
- 37. 37 https://twitter.com/alambert/status/958050456101642241 Challenges > Vendor lock-in
- 38. WHAT WE ARE KNOWN FOR 38 Options ● Multi-cloud = lowest common denominator ● There is always a vendor (even if it’s you!) ● You’ll never be completely vendor agnostic ● Multi-cloud abstraction ● Avoid altogether ● Structure your code better Challenges Challenges > Vendor lock-in
- 39. WHAT WE ARE KNOWN FOR 39 Options ● Multi-cloud = lowest common denominator ● There is always a vendor (even if it’s you!) ● You’ll never be completely vendor agnostic ● Multi-cloud abstraction ● Avoid altogether ● Structure your code better Challenges Challenges > Vendor lock-in
- 40. Lambda Handler Challenges > Vendor lock-in > Lambda Anti-pattern { "Records": [ { "EventVersion": "1.0", "EventSubscriptionArn": "somearn", "EventSource": "aws:sns", "Sns": { ... } } ] } { "Success": true }
- 41. MQ Handler WebSocket handler MQ Adapter WS Adapter Azure Function Adapter Google Cloud Fn Adapter Azure Function Handler Google Cloud Fn Handler Lambda Handler Lambda Adapter Service Repository Adapter (Anti-corruption layer) Ports Business Logic Collaborators ... Challenges > Vendor lock-in > Ports and Adaptors
- 42. 42 Challenges > Vendor lock-in > Ports and Adaptors > Sentiment Analysis Example Twitter feed Sentiment Analysis IoT Message Broker
- 43. Challenges > Vendor lock-in > Ports and Adaptors > Lambda Port
- 44. Challenges > Vendor lock-in > Ports and Adaptors > SNS Adapter
- 45. Challenges > Vendor lock-in > Ports and Adaptors > Lambda Sentiment Service
- 46. Summary Architecture > Microservices ● Separate protocol handling from business logic ● Business logic shouldn’t change with introduction of a new protocol ● Port, Adapter and Business Logic are independently testable
- 47. 47 How do you test locally? Challenges > Testing Locally
- 48. WHAT WE ARE KNOWN FOR 48 Options Challenges > Testing Locally ● Stub services (e.g. Localstack) ● Multiple handlers ● Stub API (e.g. Moto) ● Unit tests
- 49. 49 Challenges > Testing Locally
- 50. WHAT WE ARE KNOWN FOR 50 Options ● Feature arms race ● Trustworthy? ● Integration style = slower ● All cloud providers? ● Stub services (e.g. Localstack) ● Stub API (e.g. Moto) ● Multiple handlers ● Unit tests Challenges > Testing Locally Challenges
- 51. WHAT WE ARE KNOWN FOR 51 Writing good unit tests ● Follow test pyramid ● Stub out AWS APIs ● Test your business logic separately from any serverless features (e.g. lambda handler) ● Callback pyramid of death ● Tests are hard to write ● Your business logic knows about AWS ● You have to stub multiple services per test ● Large methods ● Confusing control flow Challenges > Testing Locally > Unit Test Code Smells
- 52. 52 Challenges > Testing Locally > Unit Test > Twitter Fetch Checkpoint Twitter Fetch
- 53. Challenges > Testing Locally > Unit Test > Lambda Service Look ma, no AWS Code
- 54. Challenges > Testing Locally > Unit Test > Lambda Service Look ma, no AWS Code
- 55. 55 Challenges > Testing Locally > Unit Test > Sentiment Analysis Example Twitter feed Sentiment Analysis
- 56. Integration-style test of handler Challenges > Testing Locally > Unit Test > Lambda Handler
- 57. Summary Architecture > Microservices ● Business logic should be tested separately from port + adapter ● Majority of tests, should be fast unit tests ● Stub AWS Services where required ● (Lambda) Handlers can be locally integration tested with pre-canned JSON events
- 58. 58 Async - who is my consumer? Challenges > Async
- 59. 59 Async - delay in feedback Challenges > Async
- 60. WHAT WE ARE KNOWN FOR 60 Options ● Local integration testing ● Cloud env. integration testing ● Contract testing Challenges > Async
- 61. WHAT WE ARE KNOWN FOR 61 Options ● Can’t run complete local environment ● Many moving parts ● Problems with integration testing... ● Local integration testing ● Cloud env. integration testing ● Contract testing Challenges Challenges > Async
- 62. WHAT WE ARE KNOWN FOR 62 Options ● Can’t run complete local environment ● Many moving parts ● Problems with integration testing... ● Local integration testing ● Cloud env. integration testing ● Contract testing Challenges Challenges > Async
- 63. 63 Contract tests Challenges > Async
- 64. 64 IoT Message Broker Sentiment Analysis Contract { 'Positive': 0.234, 'Negative': 10.123, 'Neutral': 7.334, 'Mixed': 0 } Consumer Provider Challenges > Async > Contract Tests
- 65. 65 CloudFront API Gateway Authentication You! awslounge.onegeek.com.au Twitter Fetch Twitter feed Twitter Push IoT Message Broker Sentiment Analysis Checkpoint Amazon ML #awsmelb Challenges > Async > Contract Tests
- 66. 66 Authentication Twitter Fetch Twitter feed Twitter Push IoT Message Broker Sentiment Analysis Checkpoint #awsmelb Challenges > Async > Contract Tests > Contracts are everywhere! Contract Contract Contract Contract Contract Contract Contract Contract
- 67. WHAT WE ARE KNOWN FOR 67 Problems with automated e2e tests ● Slow ● Easy to break ● Hard to fix ● Scales badly across teams ● Lots of set up maintenance ● $$ potentially costly Challenges > Async > Contract Tests
- 68. 68 C P mock Challenges > Async > Contract Tests Understanding Test Symmetry
- 69. WHAT WE ARE KNOWN FOR 69 Test symmetry Solved problems New problems ● Hard to keep both sides in sync ● Fast feedback ● Few dependencies ● No dedicated environment ● Reliable ● Easy to debug Challenges > Async > Contract Tests
- 70. 70 C P mock Challenges > Async > Contract Tests
- 71. 71 C P mock Challenges > Async > Contract Tests
- 72. PPCC mock contract Challenges > Async > Contract Tests
- 73. Bug turnaround - minutes Contracts tests Challenges > Async > Contract Tests
- 74. Know before you commit Contracts tests Challenges > Async > Contract Tests
- 75. Make changes with speed and confidence Contracts tests Challenges > Async > Contract Tests
- 76. Deploy independently Contracts tests Challenges > Async > Contract Tests
- 77. Better API design (Consumer) Contracts tests Challenges > Async > Contract Tests
- 78. 78 ● Open source ● Multiple languages ○ Javascript ○ Go ○ Python ○ JVM ○ .NET ○ + more pact.io ● HTTP contracts ● Message contracts ● … protocol agnostic! Challenges > Async > Contract Tests
- 79. Challenges > Async > Contract Tests Expectations on Sentiment Analyser made clear
- 80. 80 Acceptance Tests vs Canary Release Challenges > Async
- 81. Summary 81 Summary Problems ● Serverless complexity > uServices ● Testing cloud native services ● Avoiding vendor lock-in ● Handling events and asynchronous Fn’s ● More Fn’s = more things!
- 82. Summary 82 Summary Problems Solutions ● Microservices+ ● Create cloud and protocol anti-corruption layer ● Mock out AWS SDK in unit tests ● Use contract tests ● Reduce reliance on end-to-end environments ● Balance ad-hoc exploratory + acceptance tests ● Serverless complexity > uServices ● Testing cloud native services ● Avoiding vendor lock-in ● Handling events + asynchronous Fn’s ● More Fn’s = more things!
- 83. Testing large-scale, serverless and asynchronous systems Matt Fellows @matthewfellows ...without end-to-end integrated tests!