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    May 23, 2023

    What Is Workload Automation Observability?

    Jennifer Chisik, Automation Analytics & Intelligence (AAI) Product Manager at Broadcom, reveals how gaining unified automation observability for your workload automation can transform complex environments and re-imagine business service delivery.

    As workload automation environments become more complex and job volumes increase, the need for true observability is becoming an increasingly essential and critical component for optimized automated business process delivery.

    Most organizations run several automation engines from different vendors in both distributed and mainframe environments, and in the cloud. Sometimes these automation engines operate in a silo, sometimes they have dependencies with each other. In all cases, they produce vast amounts of operational data detailing the events that occur every minute.

    These are mission-critical workloads and business services that the organization depends on. A financial trading floor, for example, will need to reconcile trades overnight. Potentially tens of thousands of jobs need to run before the trading floor opens the next day. Any interruption to that business service can mean millions of dollars of lost revenues and fines.

    The challenge

    Right now, all of that automation data is sitting disconnected and unused, or at best underutilized. 
    Despite the plethora of workload automation engines in the market – some mature, some modern, cloud-based platforms – they all have one thing in common: they produce a vast amount of valuable data as they automate critical business processes. However, not all automation engines provide the end-to-end visibility – unified automation observability – required to successfully deliver business services.

    The solution: Automation Analytics & Intelligence

    This is where Automation Analytics & Intelligence (AAI) comes in. AAI gathers all this data across various scheduling solutions and platforms, then normalizes it into a single vast repository. This data warehouse, with historical and real-time definitional data, is used as the basis for producing advanced analytics and allows you to successfully manage complex workloads at the business service level. Broadcom’s AAI provides unified automation observability across multiple vendors and solutions spanning mainframe, distributed, and cloud environments.

    AAI is an advanced analytics solution for workload automation that provides predictive SLA management, critical-path insight, and unified enterprise-wide observability for business-critical applications. This way, your critical workload data can be a source of business insights used to drive IT Ops efficiency and support your digital transformation journey and business success.

    What can you do with AAI?

    1. Predictive SLA management

    I recently met with a multinational financial institution. Their team had calculated the cost of a missed SLA. If the trading system was down for just one minute, the business cost would be approximately $750,000. That excludes the damage to the customer experience and brand reputation.

    The fact is that SLA management matters – and AAI can have a transformative impact on adherence to those SLAs. Not only can AAI do historical analysis, to visualize the number of times an SLA has been missed and pinpoint problematic business processes, but it also offers predictive analytics. You can use AAI in real-time to better predict when an automation process will complete.

    If there is a delay in the process due to high data volumes or operational slowdowns, AAI will respond immediately, letting you know that you are in jeopardy of missing your SLAs. This will give you valuable time (often hours) to proactively respond before you miss your SLA and incur costs. And, with smart alerting, you can be notified of these slowdowns only when they are sufficiently severe so as to jeopardize your ability to meet your SLA. By not alerting at a job level, and only when an SLA is in jeopardy of being missed, you can drastically reduce your alarm noise and be assured that if you do receive an alarm it is significant.

    You also have the flexibility to push analytics to users: a dashboard widget, for example, can show business process owners and application owners the status of their automated business processes and the likelihood of missed SLAs.

    2. Critical path analysis

    In project management methodology, the critical path is the best sequence of independent steps to complete a project most efficiently, time-wise, and resource-wise. For workload automation, lack of insight into the critical path means missed SLAs, fines, or worse – lost customers.

    One of AAI’s most powerful features is just that - critical path analysis. Because AAI is organized for business processes and not single executions you get business process visibility and accountability.

    Based upon the entry of a critical job (typically a job with a hard and fast SLA on it), AAI will automatically identify all of the jobs that are upstream of that critical job and group them together into a “jobstream”. Then, it identifies the critical path to business process completion and the jobs in that path that are most likely to cause future issues. Plus, due to the ever-changing nature of workloads, it does this dynamically, capturing changes as they happen, creating true observability and predictability of your automation landscape.

    These capabilities came in handy with another multinational financial institution I met with recently. They were suffering from a major latency problem. The team was continually in “war rooms”, attempting to understand the critical path of SLAs that were being missed and fielding calls from frustrated business users. By adopting AAI, the team immediately had visibility into the different platforms and vendors, understood the cause of latency delay problems in their business processes, and increased throughput.

    3. Workload optimization

    Another important capability is workload optimization. AAI enables your organization to see over the horizon and optimize your workload before you experience problems. Through trend analysis, based on historical data, you can proactively find common jobs that have problems, see which jobs are running longer over time, and reveal the critical processes they are associated with. Moreover, you can identify trends across job streams – by looking at thousands of jobs that run together to fulfill a business service.

    An example of this is a global financial services organization running more than one million processes (jobs) per day, with complicated dependencies and scheduling criteria. The definitions, as well as, the start time, end time, and status of these jobs, are captured and become a valuable datastore. This datastore is foundational for discovering trends, predicting workloads and ultimately leading to insights that allow this customer to keep their workload optimized and deliver automated business services more efficiently.

    These capabilities not only help workload teams operate more efficiently, but they can also help DevOps and System Maintenance teams. By providing them insight into machine and resource utilization, for example, they can improve load balancing and optimize capacity planning.

    4. Change modeling

    With AAI, you can also simulate potential changes against defined SLAs before moving to production. This helps limit SLA breaches and allows you to optimize complex automated processing across vendors and platforms.
    The experience of one of our customers before they implemented AAI demonstrates the value of this. A large financial services organization was undertaking a complex, wide-ranging accounting system upgrade, adding hundreds of new jobs to the workload automation engine. As a result of undiscovered problems with the business processing, it was a disaster – resulting in service downtime, significant cost overruns, dramatic manual intervention, and damage to the brand.

    This could all have been prevented using AAI because it could have anticipated the breached SLAs prior to the new jobs being moved into production.

    Transforming workload automation

    AAI transforms workload automation with business process visibility and predictive SLA management. AAI can help you reimagine workload automation by:

    • Improving service delivery – With a business process-based view instead of an object-based view, you deliver workload earlier to the business to drive real business benefits and reduce the risk of SLA breaches.
    • Create efficiency and reduce costs – Reduce the time spent by the workload team monitoring jobs and addressing alerts and freeing up time to spend on other more innovative projects.

    To discover how AAI can help your organization transform the efficiency of your complex workload automation environments, and reimagine service delivery, find more automation observability and intelligence resources on Broadcom’s Software Academy.

    Jennifer Chisik

    Jennifer Chisik is currently the Head of Product for Automation Analytics & Intelligence (AAI) at Broadcom, Inc. AAI is an analytics platform providing organizations with cross-vendor, cross-platform visibility into their complex automation environments. She came to Broadcom via their acquisition of Terma Software,...

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