Tag Archives: WLM
Even knowledgeable performance experts make the mistake of throwing more resources at work. If 10 buffers are good, 15 would be even better, right? If we have more batch work, throw initiators at it; it will get things moving faster. But it turns out that overinitiation is very similar to putting up more toll collectors on a bridge. Immediately after the toll is paid, the lanes have to shrink to the number that fits on the bridge. If you have too many toll takers, the merge following the toll gets crazy, accidents can happen and no one is moving fast.
We systems programmers love metrics – and we have a lot of them. Leveraging its Batch Service Metric, ThruPut Manager can help you set and achieve SLAs that are achievable and desirable. Give it a try and see how better communication between IT and the business can lead to career opportunities and advancement.
Once upon a time, we had the luxury of throwing resources at performance problems. But even back then, we knew that didn’t always work and that there were diminishing returns, especially for batch workloads. A perfect example is buffering. For OLTP work, you could throw a lot of buffers at it and generally see some benefit, though the gains tended to diminish. However, with batch, you not only found that at some point, you got no further benefit, but that having to scan all those buffers could slow the system down. Often, the ‘right’ number was a good deal lower than what you thought.
When you hear the term dynamic initiators, you probably think of an initiator that simply starts and stops automatically. The thing is, when these initiators become part of a complete automation solution for z/OS batch processing, like ThruPut Manager, they’re capable of much, much more. ThruPut Manager’s automation algorithms optimize resource utilization and throughput of the workload as a whole by deciding to add or remove initiators based on current system load and datacenter policies.
Strict caps, as we’ve mentioned in previous posts, can be harmful to application performance. On the flip side, raising a cap to meet the needs of workload conditions can increase the Rolling 4-Hour Average (R4HA) and, as a result, cancel out the benefits of soft capping. So what is an organization to do?
Well, believe it or not, it is possible to take advantage of the financial benefits of soft capping and meet the needs of your organization at the same time. One technique is to lower the multi-programming level (MPL) of a system by controlling the available batch initiators.