|Since the introduction of the early mainframe systems, Job Schedulers have formed a fundamental part of the IT infrastructure. IBM introduced its first z/OS scheduler in the 1970’s, and nearly 40 years, multiple name changes and technology advancements later, IBM Workload Automation technology is still working away in the background of a vast number of well-known organisations across the planet.
In more recent history came a move from traditional, multi-platform, and resource intense batch scheduling environments towards highly efficient and centralised Workload Automation solutions. Workload Automation may now be a mature technology, however as the foundation for process and technology integration, it must continually evolve to keep pace with digital transformation.
Over the last few years, Cloud has been the major driving force behind many advancements in Workload Automation technologies. Whilst full Cloud adoption has been significantly less than envisioned, Hybrid solutions have become the norm with most IT departments consuming technology “as-a-service” to at least some degree. WLA has had to adapt accordingly, and as a result, over the last few years we’ve seen the introduction of support for Public Clouds (including SaaS, PaaS and IaaS), the new ability to automate and monitor workloads across Hybrid environments from a single point of control, and the choice to consume WLA as-a-service from a few leading vendors, including IBM via Service Engage.
Aside from new Cloud related features, recent advancements in WLA solutions have included critical path monitoring and predictive analytics, options for open integration (e.g. via RESTful API’s), increased out-of-the-box integration with other business applications, and more complex event-based scheduling and triggers.
But what’s next? What advances can we expect to see in the WLA arena in the next few years? What is driving these changes, and how will they affect you?
Digital transformation - the changes associated with the application of digital technology in all aspects of human society – is having a massive impact on all IT services, including WLA, and will continue to do so. As user demand grows for the ability to consume services on the move and in any way they choose (from PC’s to Smart Phones) organisations must change the way they conduct business and engage with their customers. Since this includes making services available to clients quickly, in real-time and from a number of sources, the implication for WLA is increasingly shorter windows of time to process larger and larger files
Rapid Rate of Change
The pace at which we require change, in terms of the delivery of new services and applications and the frequency of updates to existing ones, is accelerating. As a result dedicated DevOps and Continuous Delivery Teams have become standard within most organisations, and it is down to the WLA service to deliver self-service, exposed APIs, “what-if” modelling and scheduling capabilities built directly into applications to assist them with delivering changes at the rate now demanded.
Both digital transformation and rapid rate of change are the drivers behind many of the improvements and advancements expected in WLA solutions, including:
All businesses will take a different approach to adopting this new functionality as and when it is released. Some will be key in driving the developments in the first place, and some will introduce the different features gradually as and when they are required. What’s clear however is that Workload Automation forms the backbone of every organisations IT infrastructure, and it is a fundamental requirement for all businesses to embrace it if they wish to keep pace with their competition.
- Embedded Scheduling within applications will increase to assist with continuous delivery
- Better self-service functionality and more dashboards, mobile apps etc. to allow increased involvement and understanding from LoB stakeholders
- Improvements to the change management of agents must continue to accommodate increases in Hybrid Cloud usage
- Increased support for Big Data in relation to awareness, control and manipulation
- Increased collaboration through user communities to allow users to share their innovations and customisations
- Automation, monitoring and control of the application release process