High memory usage of CA OM Web Viewer Tomcat task
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High memory usage of CA OM Web Viewer Tomcat task

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Article ID: 132621

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Updated On:

Products

CIS COMMON SERVICES FOR Z/OS 90S SERVICES DATABASE MANAGEMENT SOLUTIONS FOR DB2 FOR Z/OS COMMON PRODUCT SERVICES COMPONENT Common Services Datacom/AD CA ECOMETER SERVER COMPONENT FOC Easytrieve Report Generator for Common Services INFOCAI MAINTENANCE IPC UNICENTER JCLCHECK COMMON COMPONENT Mainframe VM Product Manager CHORUS SOFTWARE MANAGER CA ON DEMAND PORTAL CA Service Desk Manager - Unified Self Service PAM CLIENT FOR LINUX ON MAINFRAME MAINFRAME CONNECTOR FOR LINUX ON MAINFRAME GRAPHICAL MANAGEMENT INTERFACE WEB ADMINISTRATOR FOR TOP SECRET Xpertware Compress Data Compression for MVS Compress Data Compression for Fujitsu

Issue/Introduction

The customer's performance team found that the CA OM Web Viewer Tomcat task was experiencing high memory usage.  The peak memory usage was more than 63000 MB.  

Environment

  • z/OS 2.2 
  • Common Services 14.1 - Tomcat 8.5.32
  • CA OM Web Viewer 12.1 

Cause

Concern over high memory usage of the CA OM Web Viewer Tomcat task.

Resolution

Common Services Level 2 reviewed the Tomcat log after LOGLVL='+T' was added and from the CCS perspective the Tomcat environment appeared to be OK.

The Web Viewer group advised that one way to determine if Web Viewer is causing the memory concern is to set up and run Tomcat Manager and 'undeploy' the Web Viewer application along with CA Styles. Knowledge Base article KB000012737 provides instructions on how to do this. When this was done a decrease in the CPU activity was noted. Web Viewer Level 2 suggested additional tracing steps and a console dump of the Tomcat STC at a point where the customer sees CPU activity occurring. Review of the dump showed that the main thing taking storage and resources was the JVM associated with the Tomcat task.

The OM Web Viewer group suggested an upgrade to Java 1.8.  In his next update, the customer advised that the Java upgrade provided a significant decrease in memory usage.