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AI / DevOps / Operations

Three Use-Cases for Generative AI in ITOps

It’s worth looking at workflows that ITOps teams are already augmenting with GenAI: status update automation, incident postmortems and process automation.
Jan 5th, 2024 7:55am by
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Organizations are under more demand than ever to deliver a great digital experience. This means an ever-growing pressure on IT operations (ITOps) teams to manage digital incidents at a breakneck pace to ensure service stability. For many teams that are looking to meet these intense demands, generative AI (GenAI) is the most exciting technology in a generation.

GenAI has the potential to enhance ITOps productivity by helping teams to better prioritize high-impact and urgent work, and automate repetitive and manual tasks. But GenAI is not a panacea, and pragmatism is needed. Thought needs to be given to the best use cases for GenAI that give ITOps a means to reduce the pressure.

How GenAI Is Being Put to Work

In practice, how will GenAI deliver these benefits to ITOps? To answer this question, it’s worth looking at some of the workflows that ITOps teams are already augmenting with GenAI: status update automation, incident postmortems and process automation.

1. Status Update Automation

When incidents and interruptions strike, it’s critical for ITOps teams to communicate the situation clearly and regularly. Along with coordinating among themselves during incidents, ITOps teams need to provide updates to organizational leadership and external stakeholders. However, status updates of live, complex situations are often stressful and demand a high cognitive load — all during times when ITOps teams may be at capacity.

Thankfully for many teams, writing and sharing status updates are processes that are a perfect fit for GenAI support. By trawling raw incident data, large language models (LLMs) can help generate comprehensive summaries quickly. But don’t expect your IT team members to try to perfect their ChatGPT prompts in the heat of an incident. Instead, look for prebuilt summarization features that understand the context of an incident status update.

Along with eliminating the need for ITOps teams to divert resources to interpret incident data, GenAI can also adapt status updates for different personas — whether it be managers, executives or customers. As a result, GenAI doesn’t just promise to save time on status updates and allow teams to focus on the real work of resolution, but also ensures that every stakeholder’s update is best suited to meet their needs.

2. Incident Postmortems

After the dust settles on incidents, ITOps teams often need to develop comprehensive postmortem reports. Incident postmortems are critical in flagging technical and cultural learnings that require action and for holding ITOps teams accountable to the rest of an organization. Unfortunately, postmortems can be time-consuming and challenging to create, since teams need to manually collect all relevant data points, review them as a group and summarize their findings.

GenAI offers a chance to dramatically streamline the postmortem process. By collecting logs, metrics and instant messages, GenAI can quickly assemble the data needed for an incident review, and then generate key sections such as key findings, root causes, areas of improvements and timelines. GenAI-powered postmortems are dramatically faster to create than their manual equivalents, which in turn encourages teams to commission postmortems more often, driving a culture of continuous improvement and futureproofing.

Along with saving time, GenAI can also provide an “objective” authority for the postmortem process, which can help reduce friction. The result is a more constructive, collaborative and stress-free approach to fixing the root causes of incidents.

3. Process Automation

Today’s IT teams are asked to do significantly more with the same or fewer resources. This will require teams to create a host of new automated runbooks for all kinds of repetitive jobs. These could be restarting and resetting remote office infrastructure, provisioning new systems, nightly “chron jobs” to copy data between systems or fetching troubleshooting diagnostics when system performance starts to degrade. But as we know, ITOps teams are notoriously time poor, so they don’t have heaps of time available to them to develop all the runbooks they could be using.

This kind of heavy lifting is something GenAI can help to transform. With a co-author for process automation, ITOps teams can get low-code capabilities for what used to be a high-code experience, but without loss of flexibility. GenAI copilots can help teams create process automation runbooks in seconds, with predefined steps within more complex processes. Users need to simply match the requirements of their own automation to generate.

The benefits of a GenAI-powered process automation go beyond saving time for ITOps teams. Backlogs for expert team members can serve as a major bottleneck. By turning workflow creation from a high-code to a low-code experience, GenAI can democratize expertise among ITOps teams by allowing non-experts to generate draft runbooks and processes to be checked by other people on the team.

In a way, GenAI is almost like having an extra junior developer on a team who can autonomously research and execute instructions. The result is that GenAI can dramatically reduce ITOps workload and improve productivity in and around incidents.

Giving ITOps the Extra Support They Need

GenAI has the potential to push the productivity of ITOps teams to new heights. As more examples emerge for how GenAI can free up time, we’re likely to see the technology increasingly become a  “must have” for ITOps teams across all industries.

Thankfully, GenAI offers some incredibly tantalizing possibilities for ITOps with use cases like status updates, incident postmortems and process automation being just the first of many. As we see GenAI mature, we’ll doubtlessly see more ways that it will accelerate learning, increase productivity and turbocharge innovation among ITOps teams.

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