Key Performance Areas for an Agile Batch Environment
Learn how you can identify, validate and measure the key performance areas for a Optimized JCL Environment.
z/IRIS® enables IBM Z performance data to integrate with enterprise-wide continuous monitoring and observability solutions.
z/IRIS streams z/OS System Management Facility (SMF) metrics into a near real-time modern and scalable data feed framework. Its SMF data feeds are compatible with and can be integrated into widespread application performance monitoring (APM), DevOps, and big data tools.
z/IRIS provides the following benefits for integrating z/OS performance data into your enterprise monitoring apps:
z/IRIS mainframe inclusivity allows DevOps personnel to detect and analyze critical z/OS performance issues without involving a mainframe subject matter expert.
Some of the common use cases where z/IRIS-generated traces and metrics can be used to monitor, analyze, and perform root cause analysis for application and performance issues include:
Db2 for z/OS performance issues during JDBC access: Enterprise monitoring interfaces can issue alerts when z/OS applications are impacted by Db2 database deadlocks, detecting which applications are blocking database resources.
Mainframe batch jobs observability: With z/IRIS work traces, DevO
ps can monitor mainframe batch job activity using their in-house APM software. Users can be alerted when jobs or job steps report errors. DevOps can also baseline z/OS metrics and alert users when anomalies occur.
Persistent storage and visualization: z/IRIS stores normalized SMF data
in a time-series database for usability and high-speed data retrieval and visualization objectives. The product comes with a preconfigured InfluxDB database with a ready-to-use loading process.
z/IRIS can instrument, collect, capture and distribute z/OS traces and metrics for all leading APM tools, including:
z/IRIS also supports the OpenTelemetry standard open-source framework. It can be used to integrate mainframe performance data with any observability and monitoring package that supports these new data exporting standards.
z/IRIS’s modern architecture uses client, server, and front-end instrumentation layers to integrate the collected metrics.
Front-end software and services can instrument z/IRIS-generated metrics and traces, enabling end-to-end monitoring and root cause analysis for z/OS applications.
Using a scalable, elastic and open transport architecture, NRT processing delivers z/OS performance data where and when you need it.
z/OS applications can run on zIIP processors, freeing up z/OS processors to service business application workloads and reducing the cost of running z/IRIS clients on your mainframe.
To increase the business value of your SMF data, the Apache Kafka category/feed used by z/IRIS is open to subscription by 3rd party Apache Kafka consumer tools. This reduces complexity and resources required to process z/OS performance data outside the mainframe. Users can implement their own Apache Kafka consumer that accesses SMF data for in-house processing. Mainframe customers can access their SMF data on-the-fly and integrate SMF data into most modern tools, applications and in-house processes.