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Key Takeaways
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A scheduler migration can be tricky to navigate. There is the risk of performance degradation and SLA breaches during the migration itself, and it can be challenging to ensure the migration project gets completed on time and within budget.
What if you could eliminate migration surprises and reduce risk? Automation Analytics & Intelligence (AAI) provides the cross-scheduler insights you need to maintain full visibility of your existing workload automation platform and of your entire environment as you migrate to a new solution.
AAI can support a scheduler migration in a few important ways. Read on to learn how.
A "big bang" approach to migration, that is, migrating an entire instance from one automation engine to another, is a daunting undertaking. It is often more desirable to migrate one application at a time. Using AAI, you can reliably discover dependencies between applications, helping you to plan which applications to migrate independently and which to migrate together.
During migrations, unrecognized job dependencies can lead to workflow “chains” becoming broken. This results in orphaned jobs that may no longer run on time or at all. With AAI, these dependencies can be identified before migration. With the solution, you can adjust migration plans or implement a bridge to ensure these workflows are unaffected.
As an application is migrated, AAI can compare the production (pre-migration) jobstream and the newly migrated jobstream, which may exist in a test instance of the new scheduler. The pre- and post-migration streams can be monitored side by side to verify that the newly migrated stream behaves similarly to the original jobstream and that no SLAs are breached.
As applications are migrated to production, AAI can monitor, predict, and report on both the old and the new together. For example, if one payroll application exists in the pre-migration scheduler and another in the post-migration scheduler, both can be combined into a single "business area" within AAI and this area can be monitored as a single unit.
As an application is migrated, it may be necessary to break a complex application into multiple parts and have handoff jobs in which a job from one engine will start a job from the other engine. This allows for more incremental migration. In this process, AAI provides better visibility across schedulers or even instances of the same scheduler, identifying logical places to build bridges or transition jobs and ensure successful hand-offs.
It may be the case that an SLA that consists of 10 tasks in the source scheduler might become more (or fewer) tasks in the target scheduler. AAI enables you to visualize the processes side by side and ensure that the deadline is met, regardless of the similarities or differences between the workflows.
If "handoff" jobs are created between scheduling instances, as mentioned in #5 above, AAI can model the logical dependencies between the jobs, even if they’re running on different schedulers. The solution can monitor the application as a single jobstream across both scheduling instances. Predictions, critical path, reporting, and all other analytics will be available. AAI increases business user access and validation visibility—during pre- and post-migration efforts. Post cutover, AAI also significantly reduces team workload by ensuring jobs are on track in the new environment.
With AAI, you use a single interface to view and organize workflows from multiple schedulers. This gives users centralized visibility for making comparisons and exerting control. With the solution, you can monitor job status, machine status, forecasts, job groupings, SLAs, and more. By harnessing a single view, you can more effectively ensure migration consistency. The solution simplifies the tracking of variations between source and target environments and it reduces service level impact during cutover events.
To learn more about AAI, visit AAI on Broadcom Software Academy.