Advanced tuning includes configuring tracing and monitoring,
and other tuning considerations for large objects, maximum concurrency,
messaging, clustered topologies, databases, and Business Process Management
products.
Tracing and monitoring considerations
The ability to configure tracing and monitoring at different
levels for a variety of system components can be extremely valuable
during periods of system analysis or debugging.
Tuning for large objects
The Java™ heap size
and concurrent processing within the JVM are factors to consider when
configuring tuning for large objects.
Tuning for maximum concurrency
For most high-volume deployments on server-class hardware,
many operations take place simultaneously. Tuning for maximum concurrency
ensures that the server accepts enough load to saturate its processors.
Messaging tuning
Use the following information to tune the WebSphere® Application Server for z/OS® messaging
engines.
Web Services tuning
If the target of the Web Services import binding is hosted
locally in the same application server, the performance can be further
improved by exploiting the optimized communication path provided by
the Web container.
HTTP binding connection pool tuning
Monitor and view the connection pool to determine whether
you can improve performance by adjusting settings.
Business Process Choreographer tuning
The following considerations apply for tuning Business
Process Choreographer: tuning the navigation mode, task list and process
list queries, and API calls.
Business Space tuning
A set of configuration options are relevant for tuning
Business Space.
Tuning the REST interface for federated BPM resources
The federated REST API can become a bottleneck if your
federation domains contain more than two systems and you have many
clients that interact concurrently with the federated BPM REST API.
A common cause of this problem is that the thread pool does not have
enough threads to handle the service requests from the clients.
Clustered topology tuning: Apply a data-driven scaling methodology
In general, there are two primary reasons to consider when
evaluating moving to a clustered topology from a single-server configuration:
scalability or load balancing to improve overall performance and throughput,
and high availability or failover to prevent loss of service due to
hardware or software failures.
Process search optimization
You can optimize the number of retrieved results entries
of your saved searches, and you can optimize your process searches
by using the saved search acceleration tools.
Advanced Java heap tuning
Because the Business Process Management product set is
written in Java, the performance
of the Java Virtual Machine
(JVM) has a significant impact on the performance delivered by these
products. JVMs externalize multiple tuning parameters that can be
used to improve both tooling and runtime performance. The most important
of these are related to garbage collection and setting the Java heap size.