Gain insights into Java Virtual Machine resource usage and IBM z/OSÂ Connect API request statistics across multiple z/OS domains
Overview
IBM Z® OMEGAMON® AI for JVM automatically discovers all online Java™ applications running on z/OS® operating systems, monitors resource consumption, and provides alerts when key performance metrics exceed established baselines.
You can monitor the performance of Java Virtual Machines (JVMs) in various z/OS environments, including CICS®, IMS, Db2® subsystems, and pure Java application servers like WebSphere® Application Server or WebSphere Liberty Profile. It allows you to analyze in-flight, completed, or erroneous IBM z/OS Connect API requests and automatically collect debug core dumps for faster diagnosis.
Additionally, you can integrate it with other products in the OMEGAMON family to provide seamless z/OS management capabilities.
Visualize and manage all JVM workloads, analyze garbage collection and heap usage to detect memory leaks, and avoid blind spots by viewing JVMs side-by-side, receiving alerts, and quickly isolating root causes of performance issues.
Automatically identify online JVMs, gain proactive insights into common operational issues, and set alert thresholds to address potential problems before they impact operations.
Understand CPU usage at the Java thread level, optimize zIIP offload efficiency, and monitor critical z/OS Connect API requests to support digital transformation.
Features
Automatically discovers all online JVMs and provides real-time and historical performance monitoring across various z/OS environments, including CICS, IMS, Db2, and Java application servers like WebSphere Application Server and WebSphere Liberty Profile. A single screen view allows you to understand the current Java workload and where it is running.
Leverages AI-driven analytics to detect and diagnose thread and locking issues, sub-optimal garbage collection, looping threads, and CPU performance challenges, including z/OS-specific resources like zIIP offload and native memory allocation. These insights help optimize system efficiency and prevent performance bottlenecks.
Provides detailed performance statistics for IBM z/OS Connect API transactions, both Requester and API Provider flows. This includes monitoring of all completed and in-flight transactions within a single tool, allowing for quick identification and resolution of issues.
Offers deep insights into native memory address space allocations, showing how memory is allocated and consumed across threads, class libraries, and heap. It also provides proactive monitoring of CPU usage, including zIIP offload and non-offloaded zIIP-eligible work, helping to manage MLC costs and optimize mainframe resources.
Utilizes machine learning and predefined key performance indicator (KPI) alerts to continuously monitor CPU performance, garbage collection, JVM health, and z/OS Connect API workloads. This enables early detection of potential issues, allowing for preemptive action to maintain optimal system performance.
Integrates seamlessly with the OMEGAMON monitoring suite, providing a unified view of the mainframe and subsystems. It also incorporates IBM Z OMEGAMON AI Insights for advanced diagnostic and forecasting capabilities, and the IBM Z OMEGAMON Data Provider for rapid problem detection and automated response, ensuring comprehensive z/OS management and enhanced operational efficiency.
Automatically discovers all online JVMs and provides real-time and historical performance monitoring across various z/OS environments, including CICS, IMS, Db2, and Java application servers like WebSphere Application Server and WebSphere Liberty Profile. A single screen view allows you to understand the current Java workload and where it is running.
Leverages AI-driven analytics to detect and diagnose thread and locking issues, sub-optimal garbage collection, looping threads, and CPU performance challenges, including z/OS-specific resources like zIIP offload and native memory allocation. These insights help optimize system efficiency and prevent performance bottlenecks.
Provides detailed performance statistics for IBM z/OS Connect API transactions, both Requester and API Provider flows. This includes monitoring of all completed and in-flight transactions within a single tool, allowing for quick identification and resolution of issues.
Offers deep insights into native memory address space allocations, showing how memory is allocated and consumed across threads, class libraries, and heap. It also provides proactive monitoring of CPU usage, including zIIP offload and non-offloaded zIIP-eligible work, helping to manage MLC costs and optimize mainframe resources.
Utilizes machine learning and predefined key performance indicator (KPI) alerts to continuously monitor CPU performance, garbage collection, JVM health, and z/OS Connect API workloads. This enables early detection of potential issues, allowing for preemptive action to maintain optimal system performance.
Integrates seamlessly with the OMEGAMON monitoring suite, providing a unified view of the mainframe and subsystems. It also incorporates IBM Z OMEGAMON AI Insights for advanced diagnostic and forecasting capabilities, and the IBM Z OMEGAMON Data Provider for rapid problem detection and automated response, ensuring comprehensive z/OS management and enhanced operational efficiency.