In this second of three Industry Insights on workload automation, I examine the role of the central manager, who orchestrates workloads across multiple platforms and can provide dependencies between jobs in different applications, ensuring those workloads run in the correct sequence and that they run as soon as any dependant tasks or events have successfully completed.
Because everything is now managed centrally, the business can now easily run or schedule reports that display the success or failure of jobs across the entire enterprise.
It is important to understand that this series of articles is not intended to take a granular look at workload automation – it’s not possible to do that and it would require a work closer to the size of Tolstoy’s masterpiece, “War and Peace”.
My goal is to unwrap the mystery or perceived complexity of the subject and highlight just some of the potentially beneficial outcomes.
At a glance – future technologies such as Hadoop, for example, which may not yet be on your radar but as soon as you are ready to take advantage of these technologies, you can rest assured that advanced integration, inherited dependencies, load balancing (allowing work to run on a number of nominated servers) and job scheduling will all be available.
Moreover, monitoring is performed using the same graphical interface used to define the workloads. As the single unified graphical interface, this can provide visibility of all work running across the entire enterprise, no matter what operating system platform the work is running on. Multiple windows of information can be defined to display exactly only what each user needs to see – for example, jobs in trouble which can then be managed by exception.
The demands of data management are said to have out-paced the capabilities of most organisations.
Effective unified automation also helps to eliminate the need for new day processing, thus improving agility by removing the unnecessary management server overhead task of building and distributing daily schedules.
Operational tasks are easily performed using the graphical user interface, allowing operations staff to manage the workload automation environment and the running of workloads efficiently.
It also relegates diagnostics and problem resolution from the realm of nightmare into a few clicks of a mouse that help you to explore errors from the graphical interface.
I think I have extolled the virtues of workload automation quite enough to acquire the interest of any CIO trying to improve efficiencies and reduce costs.
The next question is: What are the analysts and the market saying about automation?
The market advocates automation. According to IDC’s Enterprise Cloud and DevOps Management Survey, 46% of organisations agree that “increased use of automation” is among the most important drivers and requirements shaping their company’s overall IT strategy from today through 2020.
Gartner has much to say on the subject of automation, with predictions that 2020 will see more than 50% of current manual operational tasks in infrastructure managed services being replaced by intelligent automation services. 2021 is forecast as the year that intelligent automation will generate an additional 20% in savings over what is achievable today in application testing services for end-users.
Moreover, by 2022, organisations utilising active metadata to dynamically connect, optimise and automate data integration processes will reduce time to data delivery by 30%.
The demands of data management are said to have out-paced the capabilities of most organisations. Because of this, it is noted that IT leaders will rapidly innovate by leveraging important new technologies and trends.
In order to deliver effective data management solutions, it is predicted that organisations will apply automation to data management, allowing expert personnel to complete other valuable projects.
Forrester highlights what it calls the automation paradox, predicting that after years of falling, mean-time-to-resolution (the time it takes to resolve an IT failure, for example) will increase. This is said to be a result of automating the ‘low-hanging fruit’ ‒ described as repetitive tasks and incidents ‒ leaving the more complex and time-consuming problems for humans to fix.
Forrester estimates that most organisations have automated at least 20% of commodity tasks, with others automating a staggering 80%. However, it is noted there is still a lot of low-hanging fruit waiting to be automated in enterprises. For example, the worldwide market for robotic process automation (RPA) services is predicted to reach $7.7 billion in 2021 and anticipated to grow to $12 billion by 2023. According to Forrester, this is being propelled by a need to establish governance and operating models around RPA platforms.
So, all the research gurus appear to be in agreement on the projected growth of automation technologies but one crucial component must be present if organisations are to succeed with automating workloads and that is the need for agility.
Although enterprise resource planning software is often integral to core business processes, it can be slow and inefficient, requiring unreliable manual input that holds back the rest of the organisation. A modern workload automation solution should be able to bring agility to the entire enterprise, aligning this software with cutting-edge front-end tech. This helps to reconcile the multi-generational structures outlined by Gartner as an integral step for the modern enterprise.
Companies will have to manage older systems and at the same time connect them to modern digital programs, because multigenerational IT involves different layers of technology, all of which need to be automated from the bottom-up.
In my final Industry Insight in this series, I will elaborate further on the need for agility; plus the all-important need for security and outside of the forecast statistics, what the future of workload automation will look like.
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