Gartner defines IT operations as the people and management processes associated with IT service management to deliver the right set of services at the right quality and at competitive costs for customers.
Depending on who you talk to there is an associated cost with keeping the lights on as some in the IT industry would call it.
According to a Ventana Research benchmark on IT Performance Management revealed that 57% of IT organizations (57%) find financial constraints as the most important factor influencing how well IT manages operations and resources.
“This situation requires IT to use its budget wisely, of course, but business conditions also force IT to constantly seek ways to minimize expenditures while delivering at least the same business value, and ideally more, from the IT infrastructure,” said the analyst.
KLTO: It’s mostly about money
Even before the pandemic, finance (aka budgets) has conspired to dictate the technology direction of many companies. These days when revenue is unpredictable, there is even more pressure on organisations to justify what they spend on – even on something as basic as keeping the lights on (KTLO).
KLTP is the cost of maintaining the application, including operations, resources and the supporting software and hardware. Ventana puts it at US$2,000 per individual per year, or an annual cost of US$4 million or US$333,000 per month.
In a period when hiring and retaining skilled resources to do routine maintenance work is less and less attractive to management, new innovations in technology and practices may help “keep the lights on” while redirecting the IT team to do higher value work.
Two technologies, artificial intelligence and automation, that may be conspiring to solve the puzzle of how to KTLO and still have time, budget and resources to focus on innovation. In particular, AI and its impact on IT operations or AIOps as it is being referred to.
IDC defines AIOps as tools that use big data and analytics (BDA) and AI technologies to support, automate, and enhance IT operations (ITOps). AIOps platforms leverage big data by collecting a variety of data from various ITOps tools and devices to spot and react automatically to issues in real time.
AIOps systems automate mundane software maintenance activities and orchestrate the many layers of IT systems – enabling them to become increasingly autonomous and self-regulating.
"IT automation, agility, and resilience — these operational IT priorities have been there for years, but COVID-19 has placed them in the front and center of every enterprise’s strategic agenda," says Dr Christopher Marshall, associate vice president for Analytics, Big Data and Artificial Intelligence at IDC Asia/Pacific.
Kolathu says IT operations, like any discipline, has its own rather specialized lexicon of terms, processes, relationships, machines and tools, objectives, metrics -- and, inevitably, challenges, bottlenecks, opacities, limitations.
"What AIOps does, is to ingest all available data, in whatever form, including unstructured text, to bring visibility, develop insights how the elements of the environment are working together, what patterns are emerging in a predictable manner, and which of these patterns are heading towards criticality," he explains.
Click on the podchat below and listen to Kolathu share his views on AIOps and how organisations can benefit advances in AIOps.
- What is AIOps? What problems does it answer/solve?
- What is the value proposition to the company (viewed from business and IT operations)?
- Are there any limitations that are not covered today by AIOps?
- How does a business evaluate if AIOps will deliver the economic benefits that it promises to them?
- Is AIOps unique to IBM and limited to IBM tech only?
- What is your advice to any organisation considering AIOps?
Trends by IDC
- Demand for AIOps stems from the increased running workload on infrastructure, the proliferation of middle layers, and the increased demand for agility and innovation.
- AIOps can be hindered by a lack of ITOps maturity and skills, but hybrid cloud may drive AIOps demand in the short-term whilst AIOps may become more commonplace as the digital transformation progresses to newer stages.
- Companies looking to adopt AIOps should be observant of signals to embark on or scale AIOps, be specific and make progress in five steps, begin with the outcome in mind, and be forward-looking and address their capacity to learn.