1. Java Microservices in the cloud
Doug Harvey
CapTech Consulting

2. “a crummy commercial?”
CapTech is a national consulting firm with offices in Philadelphia, Washington, Richmond, Charlotte, Atlanta, Denver, Orlando…
CapTech has a Java practice that goes back to 1998
CapTech specializes in System Integration and development

3. Fad or Trend? Applets Spring EJB’s REST Swing Google Glass Javascript
Microservices?

4. Not a fad imho Synergy the design pattern itself
open-source contributors
containers
cloud

5. Why Microservices?

6. Problems with the monolith
Granular Tuning
Regression Testing
Developer Interaction
Database dependencies

7. Advantages of the monolith
Reporting
Batch processing
Transaction Management
Logging

8. Microservices?
Not the use of service objects, e.g. Domain-Driven Design
One Operating System Process
“Smart endpoints / dumb pipes” (therefore NOT ESB)
Decentralized data management (purpose-specific persistence, usually per-component)
Replaceable Component Architecture
Change of mindset - services are the app

9. Characteristics of a Microservice

10. Persistence

11. Definitions
Component - a self-contained, separately- deployable OS process
Library - code that is shared among components (does not run on its own)
API-gateway - a component whose main purpose is to orchestrate & aggregate by calling other components

12. Framework vs Component
Framework – library (jar)
Component – executable
Choice is sometimes not so obvious
Rules engine?
I8N?
Configuration?

13. Anatomy of a Microservice

14. The 12-Factor App
I. Codebase - One codebase tracked in revision control, many deploys
II. Dependencies - Explicitly declare and isolate dependencies
III. Config - Store config in the environment
IV. Backing Services -Treat backing services as attached resources
V. Build, release, run - Strictly separate build and run stages
VI. Processes - Execute the app as one or more stateless processes
VII. Port binding - Export services via port binding
VIII. Concurrency - Scale out via the process model
IX. Disposability - Maximize robustness with fast startup and graceful shutdown
X. Dev/prod parity - Keep development, staging, and production as similar as possible
XI. Logs - Treat logs as event streams
XII. Admin processes - Run admin/management tasks as one-off processes

15. Contracts Contracts are sacred Backward compatibility is paramount
Different versions must be able to co-exist
Contract testing separate from other testing
Tools available: Pact, Pacto

16. Containers What is a container? Why use containers?
Which containers to use? Docker, Rocket, Drawbridge, LXD, other

17. Why use containers? Isolation file system ports support software
dependencies
Scalability
Developer productivity (run dependencies locally)

18. Caching Microservices = increased network traffic
Caching avoids redundant calls
Distributed caching
Products: Redis, Hazlecast, etc.
Building with Caching transparency

19. What about those monolith advantages?
Reporting/Batch Processing - Elastic Search (or other shadow database)
Logging - Logstash & Kibana
Transactions…

20. Transactions What if a “transaction” spans service calls?
This is not unique to micro services
Design directions:
Keep db transactions at individual service level
Use alternate methods to restore consistency (CQRS, Event Sourcing, Eventual Consistency, Delayed Rollback )

21. What about security? Options: shared session (is he kidding?)
client certs
custom token (signed, self-contained)
Oath2 (most likely - supports SSO)

22. What is needed? API Gateway Service Discovery Load balancing
Integrated REST client
Circuit Breaker

23. How do we do all this in Java?
Roll-your-own?
Container or container-less?
Open-source frameworks?
Spring? boot, cloud (netflix)
Dropwizard?
Vertx

24. Why Spring Boot? Momentum no more container dependencies
less Mockito-style mocking
provides robust, extensible monitoring
memory is cheap
Spring Cloud - powerful annotations

25. Netflix offers (via Spring Cloud)
Eureka - service registry
Ribbon - load balancer (client side)
Feign - rest client via configuration
Zuul - reverse proxy/ API gateway
Hystrix - circuit-breaker

26. Eureka DNS for components Contributes to load-balancing
Does proactive monitoring (health checks)
Not java-specific
Spring supports via annotations

27. Ribbon Client-side load balancing Integration with Eureka
Circuit-breaker integration

28. Feign Abstracts calling to REST endpoints
Uses Ribbon for load blanking
Spring annotations
Example:

29. Daring Code Demo

30. Zuul Allows for one “front door” for consumers
Consumers don’t need to find services
Allows for one authentication endpoint

31. Hystrix
Implements circuit-breaker pattern: once failures for a component instance reach a threshold, breaker trips - preventing further calls to that instance
Integrates with other tools to allow declarative fallback when services fail or are not available (Feign, Ribbon, RxJava)
Includes monitoring dashboard for view of health of components

32. RxJava What is it? Java implementation of Reactive Pattern
Use with other Netflix frameworks provides synergy
Very useful in orchestrating several interdependent simultaneous or sequential REST service calls

33. Gradle vs Maven Gradle has some advantages in microservices world:
Groovy-based DSL instead of XML
Supports Convention over Configuration like Maven, but allows for procedural “tasks”
Excellent with sub-projects (like “client”)
leveragable in deployment as well as build/dependency management

34. Anatomy - Java Detail

35. What about testing? Less need for mocking
Contract testing is important
Component testing is important
Unit testing need is still the same

36. What about the cloud? Most cloud providers now directly support Docker
A Docker container with one spring boot microservice can be a deployable asset stored in a repository (like Artifactory)

37. Cloud Principle #1
Write no code that depends upon a particular cloud provider

38. Cloud Principle #2
Do take advantage of the monitoring and deployment facilities of your cloud provider

39. Example: Amazon EC2 Container Service (ECS)
Cluster – logical group of containers
Container instance – EC2 with ECS agent registered into a cluster
Task Definitions – app description with one or more containers
Task – an instantiation of a task definition running on a container instance
Services – run and maintain a specified number of instances of a task definition simultaneously

40. ServiceDiscovery on ECS

41. Conclusion Think differently: “the services are the application”
Leverage open-source
containers are your friend