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How generative AI facilitates ITOps modernization

4 min read
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by Joel McKelvey | May 7, 2024

IT teams need immediate and automatic access to machine data and institutional knowledge to move faster and make the right decisions. And they need context to identify incidents and understand how to resolve them. AIOps enables this by transforming noisy and fragmented operations data into actionable insights. This is the foundation of full-context operations.

Full-context operations combines observability and other machine-generated data with historical, expert, and institutional knowledge. With rapid access to complete incident data, ITOps teams can more effectively:

  • Maintain service availability
  • Automate manual processes
  • Resolve incidents faster

It takes thoughtful and effective deployment to achieve these outcomes. I joined Jon Brown, senior analyst at Enterprise Strategy Group, and Jason Walker, BigPanda chief innovation officer, in a recent webinar to talk about the value of full-context operations. We also discussed the future of generative AI for ITOps and how AI innovations power ITOps modernization.

AI benefits ITOps modernization

AI is rapidly transforming IT operations. According to Enterprise Strategy Group, 85% of organizations use or plan to deploy AI across many functional areas, including IT operations. ITOps professionals know the possibilities and have focused on integrating AI and automation into their operations. The results of these investments have been overwhelmingly positive.

“Organizations that have put in automation are very pleased with the outcomes,” said Brown. “Those using AI in production, many of whom are BigPanda customers, are thrilled with the results.”

These results are promising, but they aren’t magic. IT operations remain highly complex. However, industry professionals are optimistic: 92% report that generative AI will allow them to scale IT operations without adding headcount.

ESG reports the top three use cases for AI adoption in ITOps as:

  • IT change root-cause correlation: 29%
  • Knowledge-base generation: 25%
  • Root-cause analysis of active incidents: 24%

The top three use cases for AI adoption in IT operations.

Full-context is essential for ITOps modernization

Gathering siloed, disparate information when outages occur is still a complex process. We’ve made progress on instrumentation but remain a long way from IT operations management (ITOM) being considered easy.

“The actual tasks of IT operations management are still burdensome, complex, and manual,” said Brown. “Processes like collecting and correlating log data are hard, especially if you have to do them manually.”

According to ESG, one-third of ITOps professionals state that obtaining business context is the biggest challenge to effective incident response. Additionally, most companies report wasting up to 50% of total MTTR waiting for context.

Lack of context is costly and painful for ITOps teams working on incident response. According to a recent survey of more than 400 global IT leaders, one in three ITOps professionals say their most significant challenge is getting the necessary business context. That same survey found a majority of companies spend up to half the total mean time to resolution (MTTR) just looking for the information they need to do their jobs.

Full-context ops changes the game. Operators get the information and insights they need to uncover vital incident and root-cause details instantly. They can quickly understand the business impact of a given alert to respond or assign resources appropriately. This improves operational efficiency and service availability.

Generative AI can deliver vital context in innovative ways

GenAI can significantly and positively affect data accessibility. These systems offer the revolutionary capability of consistently correlating contextual data in real time. Advances in large language models make it possible to deliver these insights to operators in natural language.

One of the most exciting moments in the webinar was Jason’s prototype demo of the BigPanda AI-powered copilot. He showed the value of fast, natural-language access to an organization’s unified machine and human IT data. In this case, the copilot made data available through the BigPanda Unified Data Fabric. The BigPanda copilot delivers actionable insights to ITOps and ITSM teams investigating and responding to live incidents.

The BigPanda AIOps Copilot interface

The key to getting value from AI tools like these is ensuring they are knowledgeable in your specific domain. Only if the ITOps-centric AI consumes relevant information can it deliver answers specific to your environment and conditions.

AI will continue to transform ITOps modernization

It’s an exciting time in AIOps. Rapid advances in AI can help you improve service availability, resolve incidents faster, and operate far more efficiently. Learn more in the full webinar, “Knowledge is power: How AI delivers vital context to IT operations.”