Microservices with JEE
Best Practices and a Close Look using
WebSphere Liberty Profile
Michael Hofmann, ARS Computer und Consulting GmbH
and
Erin Schnabel, IBM
IBM InterConnect 2017 Conference (Session ID: BMC-4741)

© ARS Computer und Consulting GmbH 2017
Microservices with JEE
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IBM Redbook
Motivation
market interest
missing literature about
microservices
with Java showing best practices
even less literature on
microservices with Java EE
Target
Microservices with Java and
Java EE from development
to production

© ARS Computer und Consulting GmbH 2017
Microservices with JEE
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Twelve factor applications
“A methodology for building
software-as-a-service applications”
Factors are independent of
 programming language
 backing services
 cloud provider
http://12factor.net/

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Factor 2 - Dependencies
Key points:
 App declares all dependencies
 App doesn’t rely on “pre-requisite”
system-wide packages
 use dependency isolation tool (build
time, e.g. Gradle)
Runtime aspect:
 Liberty Features declared in
server.xml
 Package application with Liberty

© ARS Computer und Consulting GmbH 2017
Microservices with JEE
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Factor 3 - Config
Key points:
 Config includes anything that
can vary between deploys
 does not include internal
application config
Liberty:
 central config file
 can be managed in source
repository (scm)
 dynamic reload
 JNDI variables

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Microservices with JEE
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Factor 4 - Backing Services
Key points:
Backing services
e.g. Datastore, Watson, ….
Resources can be
attached and detached at will
Java and Java EE support a lot
of different backing services…

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Backing Service
Polyglot Persistence
 SQL
 NoSQL
Messaging Systems
 Java Messaging System (JMS) Client
 AMQP
 MQTT

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Factor 5 – Build, Release, Run
Key points:
strict separation between
stages: Build, Release, Run
e.g. no code changes at runtime
The Liberty way:
Build pipeline!
Git commit to master -> build -> live!
Liberty in docker container
Liberty own packaging feature

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Package … deploy … config
One single executable JAR file
 Spring Boot
 Wildfly Swarm (JBoss)
 IBM WebSphere Liberty
All alternatives
 Application together with
 external configuration (immutable artifact) and
 necessary runtime
 in minimalised form
 augmented with functions for metrics and health care

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Microservices with JEE
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Factor 8 - Concurrency
Key points:
Recommends splitting processes
based on the type of work
Scale by making more processes
Liberty supports:
Autoscaling
Dynamic Routing
Cluster
Elasticity

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Scalability
 Core characteristic of a microservice
 Better when microservices scale automatically
 Disadvantage of static provisioning
 Spring Boot und Wildfly Swarm depend on infrastructure
 Liberty has additional features

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Liberty features for Scalability
 Fast startup time
 Low memory footprint
 IBM supports Liberty in a docker container
 Liberty Collectives and Cluster with Autoscaling und Dynamic-
Routing
Automatic scaling with Liberty exclusive features possible!

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IBM WAS Liberty Collective

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Microservices with JEE
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IBM WAS Liberty Collective with Dynamic Routing

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Liberty elasticity
Scaling Controller installs new Liberty servers
Minimal installation package
(server + app)
Host leader
 communicates with Scaling Controller
 monitors workload
 informs members about commands from Scaling Controller
Polyglot environments
 StrongLoop server
 Liberty server
 Liberty Docker containers

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Factor 11 - Logs
Key points:
A 12-factor app never concerns
itself with routing or storage of
its output stream
Process streams are captured
by the execution environment
Usage of:
Liberty feature for ELK-Stack
Create correlation-ID with UUID
to track calls across service
boundaries

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Factor 12 – Admin processes
Key points:
Keep admin task code with
application code
Run admin tasks in an identical
environment to the app
 Run against a “Release”
/ Same config
Same dependency isolation:
 gradlew
 bundle exec
 python virtualenv

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Liberty Monitoring/Administration
Liberty feature: monitor-1.0
 Collects performance data at runtime
 Accessible with JMX or REST
 Liberty feature: adminCenter-1.0
 Admin-Web-Client:
 used heap memory
 loaded classes
 active JVM threads
 CPU usage
 other metrics, depending on resource

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High demands on prod stage
 Liberty healthManager-1.0 and healthAnalyzer-1.0
 Max. percent of request timeouts and max. response time
 Intense memory consumption
 Potential Memory-Leaks
 Results in the following actions:
 Server restart
 Create Heap or Thread Dump
 Toggle server to Maintenance Mode
 Executed on:
Host, Cluster or Server

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http://MicroProfile.io

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Contact information
Michael Hofmann, ARS Computer und Consulting GmbH
michael.hofmann@ars.de
www.ars.de
Erin Schnabel, IBM
schnabel@us.ibm.com
Twitter: @ebullientworks