Discover how Automation Intelligence (AAI) provides historical analysis of workflow runs, allowing users to review business flows from start to finish. You'll see how to visualize the critical path of jobs and compare run times against the average to understand what causes a missed Service Level Agreement (SLA). Learn how AAI can predict SLA failure at the start of a workflow, and then use that data to analyze trends, set expectations, and determine where to focus improvement efforts for optimization. This capability is available for the Broadcom suite as well as cloud schedulers like Airflow.
Users also need to review a business flow from start to finish. So here we have AAI, which provides a historical analysis of our runs. You can see here a monthly summary. I can then go into the monthly summary and, for example, look at a specific workflow in our case, the cloud data pipeline. I can see all the runs. When I show relative to SLA, you actually will notice.
I can visualize the critical path, the jobs on the critical path. I can compare them to their average run time, which is the green line, as well as the red line, which is the real run time which caused me to miss the SLA. This is available for the Broadcom suite, as well as cloud schedulers such as Airflow, as well as other scheduling products.
Once I see a run, I can then go ahead and grab a specific run. For example, here we can see that an alert was uttered right at the start of the workflow predicting that I would not make the SLA. Notice there is no second alert that I actually did not make the SLA. We also can use that to do optimization.
So, if I analyze the last 30 runs, I can see so what are the changes over time? What is the trending? What's the expectation? I can see this and then analyze where should I put my improvement time? Certainly with a job that is more on the critical path versus a job that maybe is not on the critical path.
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