AIOps: data-driven decision making for better IT service management

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AIOps – or Artificial Intelligence for IT Operations — is the application of machine learning (ML) and data science to IT operations problems. So, why is AIOps needed, and how can it best be applied to enhance IT service management and automation?

In the era of digital transformation, virtually every enterprise today faces the challenge of the rapidly growing volumes of data generated by IT infrastructure and applications that must be captured, analyzed and acted on in real time to prevent potential service disruptions, slow-downs or even outages. As a further complication, IT operations teams often work in silos, making it challenging to ensure that the most urgent incidents are addressed quickly.

AIOps essentially allows organizations to correlate data from diverse sources and visualize key performance indicators and issues in a dashboard, providing a holistic view of an enterprise’s current IT infrastructure. It can be applied to enhance a wide range of IT service management and cybersecurity tasks, including performance analysis, anomaly/threat detection, event correlation and analysis, capacity optimization and incident auto-remediation.

Business & Decision, an Orange Business Services company, recently gave a keynote presentation on “Maturing AIOps – noise reduction and beyond” at Cisco Live 2019. “The way I like to explain AIOps is that instead of having ten people chase down the same symptoms, you can have one person go to the root cause and take care of it,” explains Matt Stratton, Service Line Director, Infrastructure and Data Analytics at Business & Decision.

“That way your team is free to do things like automation or patching and higher-value tasks that you never get to because you are too busy chasing tickets. AIOps is about doing things better and more efficiently, so you have time to focus on other things,” adds Stratton.

Orange Business Services and Business & Decision present at Cisco Live US in San Diego on AI Ops and the data that’s behind that. Presented by Matt Stratton.

The emerging world of AIOps

In a bid to cut IT spending, improve enterprise IT agility and accelerate innovation, IDC predicts that 70% of CIOs will aggressively apply data and AI to operations tools and processes by 2021. Gartner suggests that although some forward-thinking organizations are using AIOps for predictive forecasting of critical cost drivers – like network utilization and storage consumption – and cloud usage, the vast majority are simply experimenting with the technology to learn more about its implementation and business use cases.

If they aren’t already, infrastructure and operations (I&O) heads should start deploying AIOps now, according to Gartner, to refine performance analysis and look to extend the technology to IT management and automation within the next two to five years. Current top business use cases include predictive event alerting and root cause analysis.

AIOps is central to the shift necessary to handle digital transformation in IT operations. “It is less a product and more a paradigm for transformation. It isn’t just about tools and technology, it is also about people,” explains Stratton.

AIOps doesn’t come without its challenges, however. Lack of AIOps skills, IT operations maturity and data quality are the three biggest hurdles for enterprises in ensuring quick “time to value” for deployments, according to Gartner. In addition, handing over control and adopting autonomous systems is a concern for some enterprises.

Enterprises also need to understand that it is imperative to have a well thought out strategy for the deployment of AIOps tools, or deployment can be very disruptive to workflows.

Exploring the AIOps landscape

As well as working with customers in the AIOps field, Orange Business Services is exploring tools to address its own internal needs, especially with more complex and agile services. This includes automatic categorization of incident tickets and routing them to the right operating center.

Orange is also innovating using AIOps in a number of key business areas in both enhancing and bringing new technologies to market – these include 5G, contact centers, multisourcing integration, SD-WAN and SDx (software-defined everything).

5G, for example, necessitates a new breed of platform capable of supporting a rich catalog of near real-time edge computing and IoT services. Orange is developing distributed architectures for 5G that combine the best of cloud and mobility. Software-defined infrastructures will extend from on-premises via the radio access network to the core network to support new business cases. AI is vital in harvesting network telemetry and other data insights and triggering action within intelligent automation and service orchestration systems to ensure consistent service levels across all these distributed environments.

Over time, in multisourcing service integration (MSI), AIOps will be able to provide end-to-end unified visibility on all infrastructure services that Orange and third parties deliver to the customer. This includes checking the performance of multiple Internet or cloud service providers.

The changing face of AIOps

Up until now AIOps has been used mainly to support IT operations processes to monitor and gain insight into IT infrastructures, applications and digital experience.

Gartner believes, however, that AIOps will develop into a more “bidirectional solution that not only ingests data for analysis, but also initiates actions based on its analysis.” These actions, often through integration with IT Service Management (ITSM) and IT Operations Management (ITOM) tools, are likely to include problem triage, run-book automation, application-release orchestration and so forth.

IT operations are being pulled in very different directions: on one side, CIOs are being asked to cut costs, and on the other, operations are becoming increasingly complex. AIOps might just be the answer.

Want to know more about AI and how it works? Read our blog series beginning with Everything you always wanted to know about AI (but were afraid to ask), and read our ebook Smarter data management for AI-enabled business success.

Jan Howells

Jan has been writing about technology for over 22 years for magazines and web sites, including ComputerActive, IQ magazine and Signum. She has been a business correspondent on ComputerWorld in Sydney and covered the channel for Ziff-Davis in New York.