Tag Archives: batch processing
With the focus on compliance, most companies have SLAs for online work, but many don’t have SLAs for batch. We all know only too well that users have expectations as stringent as SLAs. Everyone’s tracking how well you manage batch, but because the batch SLAs aren’t documented, they are what the users think they should be. How can you possibly manage that!?
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 initially set up your workload manager (WLM) policies, it was a LOT of work—something you’re likely not eager to go through again. As long as performance seems to be okay, it’s easy to forget about it—shifting your focus to the myriad other challenges on your plate. But while it’s tempting to ignore your WLM policies, there are plenty of reasons why you shouldn’t—particularly during hardware upgrades.
When you upgrade hardware, you’re adding capacity—if not speed—which can translate into better performance initially. However, over time, as increased demand sucks up the cycles you’ve added, performance may degrade. That’s why it’s essential to revisit your WLM policies upon every hardware upgrade. Ideally, you want to provide at or just below agreed-upon service levels and set realistic goals.
It’s 7 a.m. You sit down at your desk and, despite managing your email account until late last night, you open an inbox so full that you can’t send out anything until you bring your storage down a few MB. Messages start popping up—previously-configured alerts designed to notify you of looming application issues—indicating that simply working through the backlog is going to take up a significant portion of your day. And after a quick glance at your calendar, it’s evident that you’ll have at least five hours of meetings rounding out the rest of it.
Once again, lunch and a planned run to the gym are out. Your manager stops by to tell you that the scheduler is having some issues with batch—the recent merger dumped a huge load of new accounts. In the weeks before the increase in demand, you were having trouble making the SLAs. Even without asking, you know that batch isn’t priority one, but you can’t ignore it.
We mainframers have a love/hate relationship with automation. Our careers rest on it—business applications are nothing more than formerly manual labor, after all—and we love it when automation takes on chores for us that we’d rather not do, such as routine problem detection and remediation (automating JCL creation was a personal favorite).
We’ve seen automation tools pitched in our workplace that our managers hope will allow them to avoid the need to have high-priced experts manage complex technical challenges. Our constant battle, then, is to promote that middle ground—IT solutions that help us do our increasingly-complex jobs better, while simultaneously saving our companies money.
Advertisers constantly stress the value of more. More data, more minutes, more channels, more choices—it makes it easy to believe that more is truly better. For some situations, it probably is, but as John Baker recently discussed in our CMG webinar, What’s in your nest? More than ever – Less is More!, for performance experts this can seem counter-intuitive.
Don’t get us wrong—we would all love more processor capacity and more memory. But while over-configured datacenters were common in the past, today that’s no longer the case. With more mainframers finding themselves challenged to reduce costs, we rarely get more—except more workloads, more challenges and more demand.
A guest post by Denise P. Kalm – “Robots will replace us!” The rallying protest cry echoed throughout the ‘50’s and the ‘60’s as sci-fi movies predicted a future of smart machines. As much as people feared losing their jobs then, now IT workers too often fear automation capabilities as career destroyers.
People were wrong about robots and they’re wrong about software automation too. In fact, professionals in all fields increasingly need automation to successfully execute their jobs. The tools they have increase their productivity and accuracy, translating to greater job satisfaction.