How do you handle mainframe performance issues during peak periods and emergencies?

We can use tools like IBM's RMF (Resource Measurement Facility) or SMF (System Management Facility) to collect detailed performance and utilization data. These tools can provide information on CPU usage, memory utilization, I/O activity, and other critical metrics. We need to assess the volume and speed of I/O operations. High I/O wait times can indicate bottlenecks.

Saber entender problemas de desempenho no mainframe durante picos de utiliza??o é crucial para manter a estabilidade e a eficiência do sistema. Aqui est?o algumas estratégias podemos considerar: - Monitoramento Contínuo - Implemente ferramentas de monitoramento para rastrear o desempenho do sistema em tempo real. - Analise métricas como uso de CPU, memória, E/S e taxa de transa??es. - Saber identificar gargalos e anomalias rapidamente. - Verificar e ajustar os parametros do sistema, como tamanho de pool, buffers e filas, para otimizar o desempenho.

In emergencies, prioritizing mainframe workloads by business impact is essential to maintaining critical operations. WLM allows systems to dynamically allocate resources based on the importance of each workload, ensuring that high-priority tasks (e.g. customer transactions, essential banking services) receive the resources they need. Sometimes this means stealing resources from less urgent workloads (e.g. batch processing, internal reports) where a delay is less impactful. By using WLM to triage workloads, teams can minimize the risk of service disruptions, meet service-level agreements (SLAs), and quickly stabilize systems when resource contention is high. This approach supports overall business continuity and customer satisfaction.

If you believe you are experiencing performance problems, the first thing you should do is ensure you are running the latest available bundle. This will guarantee that you have the newest fixes on your system. If the problem still persists, then you need to check you have enough resources defined to the partition in which the issue is observed. This includes processors and memory, but also the I/O required to access your storage and network.

Managing mainframe performance during peak periods and emergencies is crucial for seamless operations. When issues arise, swiftly assess root causes using real-time monitoring tools. Prioritize essential tasks, communicate transparently about potential disruptions, and collaborate with cross-functional teams for targeted solutions. Optimize resource allocation and resolve bottlenecks through performance tuning measures. Conduct post-incident reviews for valuable insights. A proactive, collaborative, and data-driven approach ensures resilience during peaks and quick recovery in emergencies, safeguarding mainframe system stability. #MainframePerformance #ITOperations #EmergencyResponse

Using data such as SMF or RMF records will help you better understand where your resources are being consumed. Here you can view your CPU activity along with your I/O channel utilization to help diagnose any possible resource conflicts.

Know your worload in detail. Have a clear, documented vision of work importance, priorities and workload that can be held back during 'hard times'. Assure that your SLA's refelect the above. Has always worked and still does - but it takes some courage from operations management.

Being able to have a baseline for comparison is critical. Not only will it allow your organization to identify anomalous events, but it will also enable you to determine if there are other external factors contributing to the issue. Other external issues may include peak workload time, network outages, SAN events such as congestion, and maintenance windows. These may help the team root cause the source of the performance problems.

Even though applications may stay the same, the behavior of your end users might change over time. This factor needs to be considered as part of the resource planning or code optimization activities to ensure the overall health and performance of your applications running on the mainframe.

In my experience, performance issues with batch processing typically occur during peak times like month-end or quarter-end processing. If these issues lead to backlogs and missed SLAs, application teams should investigate job dependencies for the scheduled tasks. Often, when a new job is scheduled by an application programmer, they only consider the jobs within their own application and overlook the overall load on the Mainframe from other applications.

There is a major difference between a mainframe's handling of peak performance and that of other systems. The mainframe architecture is designed to operate at utilization levels up to and including 100% without collapsing. The queues may back up but the system keeps running. On other systems the probable outcome of a similar scenario is that the system will overload and shut down. This will likely cause a cascading effect, bringing down other systems, which could take hours to bring back on line.

Talk to the people that monitor and work the system at various times of the day/week/month. A prior job had a situation where after several years of good performance the scheduling software crashed due to too many jobs running during end of month. It turned out one of the night-shift managers had set up a custom prioritization of jobs during month-end so the fast-running jobs were run first. This manager had been changing it manually every end of month for several years and this month they had gone on vacation. Their custom modification was put into one job that would make those changes before end of month started and a second job that would restore normal settings afterwards. We never had that problem again.

It is also necessary to look at the work load schedule. This doesn’t seem to be mentioned above. There are occasions when heavy CPU or I/O processes are run concurrently but unnecessarily so. Traditionally, mainframes have been sized using the heaviest processing periods, year end processing for example. By looking at the daily processing schedule it is possible to identify options to reschedule less urgent, heavy usage processes to a time where the is more capacity available.