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- We did some tests with tasks running in parallel on one of our systems. We started off by running 500 shell jobs in parallel. Our test system had no problem with up to 1500 jobs in parallel. But if we started more than 1500 then the JOC (JS Operations Center) started to slow down.
- A customer in the USA has approx. 1500 jobs defined, each of them with a schedule. These jobs are running more or less around the clock on a RedHat Linux with an Oracle 11 database. Each task that is started for a job runs in a separate process and therefore uses any available CPU independently from other tasks. The JobScheduler main process that launches the jobs runs in one tasks task and will therfore therefore use one CPU.
- A third example: a customer drives a series of Indesign servers with JS. More than 1000 orders are started and run for a short time – typically a few seconds, The orders use the same task sequentially without creating a setup time for each order. Here, JS is running on a Windows server and the workload it generates is relatively small.
One further point which has an impact on the performance of JS is the size of the history-database and the performance of the database server. We recommend that the database is compacted from time to time, e.g. once a week or perhaps once a day, depending on the number of job runs.
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