Many organizations see great potential in embracing the major trend in IT-Architectures: Microservices. There is the prospect of solving common problems with conventional Architectures, especially how to deal with monoliths. On one side development organizations with focus on the JEE platform feel challenged how to best implement Microservices using JEE Technology. On the other side are JEE platform providers enhancing and changing their offerings to align with the Microservices trend. This session looks into the advantages and draw backs of the JEE approach and discusses technical as well as organizational aspects. Another focus is on how the IBM WebSphere Liberty Profile Server fits to the task and compares this approach with others.

1. 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)

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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

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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

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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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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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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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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