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JobScheduler Operations Center

The JobScheduler Operations Center (JOC) is used to monitor and control the jobs, job chains and orders.
You open JOC in a browser with the URL:

where scheduler_host and scheduler_port are the hostname and the TCP port number of the JobScheduler. 

Overview Communication Between JOC and JobScheduler Engine 

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Factors affects JOC Performance 

• Size of data packet

  • One of major factor affecting data packet sent back by JobScheduler depend upon number JobScheduler objects e.g. job chain, job, order, deployed in live folder.

• Number of running jobs/tasks

  • Number of running jobs/tasks also add addition run time information e.g. start time, end time, step text etc.

• Number of history entries per order/task

  • In JOC user can configure how many order/task histories he want to see. As number of order/task history is higher, JobScheduler engine needs more time to fetch that information from database. Also the data packet size will be bigger.

• Auto update frequency

  • By default auto update of JOC is disabled . But if user enable the Auto update

• Database performance

  • JobScheduler fetch history and status information from Database tables, as time progress  database tables become too big and usual database performance problems such as no indexing, unoptimized queries plans etc started affecting JOC performance.

• Network performance

  • The JOC communicate with JobScheeduler JobScheduler over LAN / local network.  Usually enterprise networks are very fast but added layer of security. packet firewalls, zoned network etc add bit of latency. which also can  affect the JOC performance. 

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The JOC will open a new tab to display the debug information. You will see debug information in new tab depending upon Log Level, Number of job, job chain etc. and JOC update frequency.

Disable Debugging

To disable the JOC debugging follow the same steps as for Enable Debugging and in step three set the Log Level to 0.

Analyze Data In Debug Log

115-05-04 14:02:18.684 [debug3]ELAPSED TIME FOR SCHEDULER REQUEST: 0.172s
115-05-04 14:02:18.703 [debug3]MODIFY DATETIME ATTRIBUTES:
115-05-04 14:02:18.725 [debug3]ELAPSED TIME FOR MODIFY DATETIME ATTRIBUTES: 0.022s
115-05-04 14:02:18.743 [debug3]ELAPSED TIME FOR SCHEDULER TREE REQUEST: 0.521s
115-05-04 14:02:18.762 [debug3]START MODIFY RESPONSE left_frame
115-05-04 14:02:18.782 [debug3]ELAPSED TIME FOR MODIFY RESPONSE: 0.02s
115-05-04 14:02:18.801 [debug3]WRITE HTML
115-05-04 14:02:18.820 [debug3]START TRANSFORM RESPONSE frameset
115-05-04 14:02:18.937 [debug3]ELAPSED TIME FOR TRANSFORM RESPONSE frameset: 0.117s
115-05-04 14:02:18.957 [debug3]ELAPSED TIME FOR WRITE HTML: 0.156s
115-05-04 14:02:18.975 [debug1]ELAPSED TIME FOR UPDATE left_frame: 0.79s
115-05-04 14:02:18.995 [debug3]HTTP REQUEST STATUS onComplete 200
115-05-04 14:02:23.286 [debug2]EXEC update_periodically_checkbox__onclick("[object HTMLInputElement]") in top_frame
115-05-04 14:02:23.305 [debug4]DELAYED EXEC (0.001s): parent.left_frame.repeat_update( parent._scheduler._update_periodically, parent._scheduler._update_periodically ); called by update_periodically_checkbox__onclick in top_frame
115-05-04 14:02:23.324 [debug2]ELAPSED TIME FOR EXEC update_periodically_checkbox__onclick("[object HTMLInputElement]") in top_frame: 0.038s

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1. Organizing JobScheduler objects e.g. job, job chain under directories and sub directories.
2. In case of higher number of JobScheduler objects JOC's tree view render faster compare to list view.
3. Using JobScheduler with Jetty Web server rather then JobScheduler's inbuilt Web Server also has visible performance improvement.
4. By increasing auto refresh / Update time to 30-45 seconds also reduce load on the JobScheduler engine.
5. Also check your JobScheduler database for old indexes and other usual database related performance problems 

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