Choreography vs Orchestration in serverless microservices

We went from a single monolith to a set of microservices that are small, lightweight, and easy to implement. Microservices enable reusability, make it easier to change and scale apps on demand but they also introduce new problems. How do microservices interact with each other toward a common goal? How do you figure out what went wrong when a business process composed of several microservices fails? Should there be a central orchestrator controlling all interactions between services or should each service work independently, in a loosely coupled way, and only interact through shared events? In this talk, we’ll explore the Choreography vs Orchestration question and see demos of some of the tools that can help.

Transcript

1. Choreography vs Orchestration in serverless microservices Mete Atamel Developer Advocate at Google @meteatamel atamel.dev speakerdeck.com/meteatamel Guillaume Laforge Developer Advocate at Google @glaforge glaforge.appspot.com
2. Choreography vs Orchestration
3. CHOREOGRAPHY ORCHESTRATION
4. Imagine a simple e-commerce transaction Services calling each other directly Frontend App Engine Order request Payment Processor Cloud Run Authorize & charge CC Shipper Cloud Functions Prepare & ship items Notifier Cloud Run Notify user
5. Simple REST: Pros and Cons Pros ➕ Better than a single monolith ➕ Easy to implement: Services simply call each other Cons ➖ Too much coupling between all the services ➖ Each service can be a SPOF ➖ Each service needs its own error / retry / timeout logic ➖ Who ensures the whole transaction is successful?
6. Choreography (event-driven) Event-driven services Frontend App Engine Order request Payment Processor Cloud Run Authorize & charge CC Shipper Cloud Functions Prepare & ship items Notifier Cloud Run Notify user Message Broker
7. Imagine a more complex transaction
8. Choreography: Pros and Cons Pros ➕ Services are loosely coupled, ➕ Services can be changed independently ➕ Services can be scaled independently ➕ No single point of failure ➕ Events are useful to extend the system beyond the current domain Cons ➖ Difficult to monitor the whole system ➖ Errors / retries / timeouts are problematic ➖ The business flow is not captured explicitly ➖ Who ensures the whole transaction is successful?
9. Orchestration Orchestrated services Frontend App Engine Order request Payment Processor Cloud Run Authorize & charge CC Shipper Cloud Functions Prepare & ship items Notifier Cloud Run Notify user Orchestrator
10. Orchestration: Pros and Cons Pros ➕ Business flow captured centrally and source controlled ➕ Each step can be monitored ➕ Errors / retries / timeouts are centralized ➕ Use simple REST, no need for events ➕ Services are still independent Cons ➖ A new orchestrator service to worry about ➖ Orchestrator could be a single point of failure ➖ Reliance on REST means more tight-coupling
11. Which one is better? Choreography or Orchestration?
12. It depends... Choreography Services are not closely related Services can exist in different bounded contexts Orchestration Can you describe the business logic in a flow chart? Are services closely related in a bounded context? Do you want to stay in REST?
13. Hybrid approach Orchestrated bounded contexts communicating via events Orchestrated Bounded Context Message Broker Orchestrated Bounded Context Orchestrated Bounded Context
14. Landscape
15. Choreography (event-driven) AWS: SQS, SNS, EventBridge Azure: Event Grid, Event Hubs, Service Bus Google Cloud: Pub/Sub, Eventarc Other: Kafka, Pulsar, Solace PubSub+, RabbitMQ, NATS...
16. Orchestration AWS: Step Functions Azure: Logic Functions Google Cloud: Workflows, Cloud Composer Other: Apache Airflow
17. Serverless Workflow Specification serverlessworkflow.io A sandbox-level project at CNCF for a specification Defines a declarative and domain-specific workflow language for orchestrating events and services
18. Serverless Workflow Specification serverlessworkflow.io Workflow projects need to implement & support the spec Spec doesn’t necessarily cover all aspects of a product and not all products cover the whole specification Services need to be described with OpenAPI
19. Orchestration: Google Cloud Workflows
20. Serverless Compute External API’s Google API’s etc... Workflows - orchestrate & integrate SaaS API’s Private API’s Other Clouds
21. - processPayment: params: [paymentDetails] call: http.post args: url: https://payment-processor.run.app/... body: input: ${paymentDetails} result: processResult - shipItems: call: http.post args: url: https://.../cloudfunctions.net/ship body: input: ${processResult.body} result: shipResult - notifyUser: call: http.post ... Payment Processor Cloud Run Authorize & charge CC Notifier Cloud Run Notify user Shipper Cloud Functions Prepare & ship items YAML or JSON syntax
22. Payment Processor Cloud Run Authorize & charge CC Notifier Cloud Run Notify user Shipper Cloud Functions Prepare & ship items Payment Processor Cloud Run Authorize & charge CC Notifier Cloud Run Notify user Shipper Cloud Functions Prepare & ship items WAIT Payment Processor Cloud Run Authorize & charge CC Notifier Cloud Run Notify user Shipper Cloud Functions Prepare & ship items shipmentDetails userDetails Step Sequencing Serverless Pause Variable passing JSON Parsing Steps
23. Errors and retries Payment Processor Cloud Run Authorize & charge CC Notifier Cloud Run Notify user Shipper Cloud Functions Prepare & ship items MAX: 5 times BACKOFF Payment Processor Cloud Run Authorize & charge CC Notifier Cloud Run Notify user Shipper Cloud Functions Prepare & ship items Pager Cloud Run Escalate to support SUCCESS ERROR Configurable retries Configurable exception handling
24. Conditionals and 3rd party calls Notifier Cloud Run Notify user Shipper Cloud Functions Prepare & ship items Pager Cloud Run Escalate to support SUCCESS ERROR Out of Stock? No Request from the supplier Yes Read inventory Inventory DB Update inventory Inventory DB Supplier API
25. Other useful features Subworkflows to encapsulate common reusable flows Connectors ßeta to connect to other Google Cloud services & APIs
26. Deploy, execute, manage workflows # Deploy a workflow # Execute a workflow # See the result
28. Case study: Pic-a-daily, A microservice-based picture sharing application
29. Pic-a-daily: A photo sharing application g.co/codelabs/serverless-workshop
30. Choreographed (event-driven) architecture
31. 3 different event handling approaches
32. Orchestrated architecture
33. Lessons learned
34. Lessons Learned ➕ Simple REST was refreshing (vs. 3 eventing formats) ➕ Less code (eg. no event parsing, no Image Analysis & Garbage Collector functions) ➕ Less setup (eg. no Pub/Sub, no Scheduler, no Eventarc) ➕ Easier error handling (eg. the whole chain stops on error)
35. Lessons Learned ➖ New service to learn with its quirks and limited docs ➖ Code vs. YAML, in a single YAML file (code is easier to write and test than YAML!) ➖ Debugging / testing / logging is not mature, no IDE support ➖ Lost parallelism ➖ Loss of eventing flexibility
36. Cloud Workflows Cloud Workflows tips cloud.google.com/workflows bit.ly/gcw-tips Quickstart cloud.google.com/workflows/docs/quickstarts Codelab: Intro to serverless orchestration with Workflows codelabs.developers.google.com/codelabs/cloud-workflows-intro Thank you Mete Atamel @meteatamel atamel.dev speakerdeck.com/meteatamel Guillaume Laforge @glaforge glaforge.appspot.com