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 centre of every enterprise’s strategic agenda," says Dr Christopher Marshall, associate vice president for Analytics, Big Data and Artificial Intelligence at IDC Asia/Pacific.
Other highlights:
- Demand for AIOps stem 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 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.
