Why Teams call analytics are critical to your entire business
Mule soa
1.
2. 1. Business context and problems faced
2. The idea of a service-oriented online architecture
3. How and why we selected Mule
4. Overview and examples of Mule use cases
5. Best practices and learnings
2
3. ■ We did not Google „open source ESB“ to select Mule …
■ Instead we did a qualitative and quantitative comparison of major open source ESB
products using different criteria:
■ Primary: professional maintenance, commercial support with SLAs, licensing, performance,
operations by IT department possible
■ Secondary: documentation, code quality, activity and size of community, Spring support, sync
and async communication, supported standards, app server integration, development tools
■ Mule quickly emerged as the favored ESB product, followed by Fuse ESB and WSO2
■ Static analysis of the Mule sources (Sonar,
Structure101) showed acceptable quality
■ Modularization and project structure looks well-
thought-out and enables light-weight deployment
■ Good code quality, in spite of found violations and
partially low documentation
■ Test coverage is reasonably high to ensure correct
function in case of changes
How and why we selected Mule
3
4. ■ Different load scenarios with constant and
increasing parallel requests (Apache JMeter)
■ Measurement of performance relevant
metrics using Software-EKG
■ Live profiling of system behavior (JProfiler)
■ All findings have been reported to MuleSoft
■ Together with MuleSoft we were able to solve
all the found issues:
■ MuleSoft supplied a working patch for the
Registry synchronization issue within 2 days
■ Other issues could simply be addressed using
the optimized configuration parameters (thread
pool settings, …) supplied to us
■ This was decisive for the confidence and the
final decision for Mule ESB
How and why we selected Mule
4
5. 1. Business context and problems faced
2. The idea of a service-oriented online architecture
3. How and why we selected Mule
4. Overview and examples of Mule use cases
5. Best practices and learnings
5
6. ■Requirement: Mule
ESB had to be deployed
as a Java web
application to be
operated by the IT
department
■Embedding Mule into a
web app is pretty
straight forward using
the a context listener
■Custom listener 6
Overview and examples of Mule use cases
7. Overview and examples of Mule use cases
7
■ Access to the endpoint is controlled
using a Spring security filter
■ Each data source has specific POJO
implementation or private flow
■ Choice is based on payload using a
Groovy evaluator
8. ■ Only minor Java code required
■ Web service interface and types
■ Custom transformers
■ Choice uses CXF operation header
■ XSLT to transform XML/RPC to
JAXB XML structure
Overview and examples of Mule use cases
8
9. ■ Web service interface and types defined as
POJI and POJOs with JAX-WS annotations
■ The service component only performs
validation and preprocessing of request
Overview and examples of Mule use cases
9
■ The actual sending using an SMTP
connector is performed asynchronous
■ Custom transformer uses Velocity to
convert request object to email body
10. 1. Business context and problems faced
2. The idea of a service-oriented online architecture
3. How and why we selected Mule
4. Overview and examples of Mule use cases
5. Best practices and learnings
10
11. ■ Mule provides several built-in components
to test Mule XML and flow definitions
■ The MuleFunctionalTest allowed us to test
our flows within the IDE
■ No deployment to a standalone instance
required, thus reducing turn-around times
■ The MuleClient is not really intuitive to use
■ Smart combination of SoapUI test cases
together with mock services allowed 100%
local and off-site development
■ Learning: develop as much as possible as
POJOs and use „traditional“ unit testing
■ Learning: take the time to write a good
mock for the service you are integrating
Best practices and learnings
11
12. ■ „The Leanest, Meanest ESB: Mule ESB is the world's most efficient Enterprise
Service Bus” (http://www.mulesoft.com/mule-esb-small-footprint)
■ We went well below the mentioned figures by building a custom Mule distribution
tuned and optimized for our specific use cases
■ Based on the default distribution assembly XML found in the Mule community
sources, we
1. got rid of everything not required in production, mainly docs and examples, but also not
required Tanuki EXE wrapper binaries, etc.pp.;
2. selected only the required Mule modules and transports our uses cases really required, this
reduced the amount of 3rd party libs significantly;
3. used Maven dependency management to have full control of all used 3rd party libraries,
used more recent versions where possible (e.g. Spring, CXF, Saxon)
4. added our Mule apps and their dependencies, then repackaged
■ Thorough load tests lead to optimized JVM parameters and high performance:
-Xmx=128m -Xms=128m -XX:MaxPermSize=64m -XX:NewRatio=2 -XX:SurvivorRatio=12 -XX:+UseParallelGC
-XX:+UseParallelOldGC
Best practices and learnings
12
96 MB
30 MB
37 MB
13. ■ A migration of the whole infrastructure in one go would
have been impossible; the system needs to be
available around the clock
■ Instead a staged migration of the infrastructure
components and applications has been used:
■ Phase 1: Migration of all online servers, application by
application, introduction of the primary ESB with first
required services
■ Phase 2: Integration of a new online portal, operated in
parallel to the old portal infrastructure
■ Phase 3: Migration of all „legacy“ portals to access the new
online infrastructure components
■ After each phase the behavior of the new components
was monitored closely to detect any problems in
production
■ The services and backend systems integrated by the
primary ESB instance constantly grew (I might still be
growing in next phases)
Best practices and learnings
13