Over the next few years, we’ll see a seismic shift in how devops organizations, agile development teams, site reliability engineers, and IT Ops will achieve an increasingly complex mission.

How can IT improve reliability, performance, and security while deploying more innovations at increasing release frequency and with fewer incidents and defects?

Over the last ten years, solutions have included migrating to the cloud, centralizing observability data, automating operations, leveraging machine learning, and deploying other AIOps capabilities.

And for the next several years (One? Three? Five? What’s your estimate?), we’ll see new generative AI platforms emerge, and existing platforms add LLM capabilities that will transform how IT teams operate.

“In platforms targeting DevOps, IT Ops, and ITSM, the remarkable capabilities of GPT and LLM are transforming operations,” says Vijay Iyer, president of Americas at Mastek. “With advanced problem-solving abilities, GPT and LLM platforms empower organizations to efficiently address complex issues, optimize efficiency, and drive innovation in the IT landscape.”

What can IT, DevOps, SREs, and developers do today with gen AI and LLM capabilities to improve IT operations? Here’s a list:

1. Generate service level objectives

Kit Merker, chief growth officer of Nobl9, has an optimistic viewpoint on generative AI’s impact on DevOps, SRE, and IT Ops. “I don’t believe that GPT technologies will put developers or DevOps folks out of a job soon — to the contrary, it will create more jobs! — a lot of mundane and repetitive code-adjacent tasks can be further automated using specialty LLMs,” he says.

Merker shares a great example of how generative AIs can capture reliability data, and help site reliability engineers create service-level objectives. “SLOgpt.ai is an example of this, which uses Google Vertex AI and PaLM2, and is trained to understand reliability engineering concepts and can even answer questions about a Service Level Objective (SLO) generated from a user-uploaded screenshot of an observability metric,” he says. “You can ask SLOgpt.ai to create an OpenSLO yaml or to write a song about your SLO; the choice is yours.”

2. Propose incident root cause

Marko Anastasov, co-founder of Semaphore CI/CD, says that instead of gathering in war rooms and organizing bridge calls to review mounds of operational data, IT Ops can use LLMs to identify the root cause of incidents. “In this field, GPT and LLM can be used to automate incident response by providing real-time insights into the root cause of an incident and suggesting remediation steps,” he says. “This reduces the time to solve incidents, improves customer satisfaction, and makes the lives of support staff much easier.”

3. Grind out troubleshooting, creating documentation, and managing policies

Working in IT has many bright spots to showcase innovations, automate processes, and improve system reliability, but some responsibilities are time-consuming drudgeries. Tony Johnson, CI/CD Engineer III at Rise8, says Gen AI can be a powerful assistant. “With the evolution of GPT and LLMs, DevOps, IT Ops, and ITSM platforms now house predictive troubleshooting, automated documentation, and real-time policy enforcement capabilities, unleashing new heights in operational efficiency and resilience,” he says.

Read more from Rise8 on achieving impactful software and user joy, spearheading digital transformation with action and ambition, and shipping with continuous delivery.

4. Query log files to find anomalies

One user generates expensive queries undermining performance for all active users – how do you find the needle in the haystack? Emily Arnott, content marketing manager at Blameless, suggests using an LLM to query log files to find the answers. “A capability on the close horizon for LLMs is parsing huge log files that typical regex searching can’t make sense of,” she says. “Operations people often end up with a huge surplus of data and want to find any patterns or anomalies that can be detected in them. LLMs make this easy: even if you don’t know exactly what you’re looking for, they’re sophisticated enough to highlight things worth seeing.”

5. Migrate scripts and automations across platforms

When you need to change platforms, do you have to rewrite all the scripts and automations or hire someone to do all the work to port code across platforms? Not so, says Andrew Amann, CEO of NineTwoThree Studio. “We’ve recently leveraged ChatGPT’s innate ability to translate from one language to another to convert Terraform scripts to CloudFormation,” he says. “ChatGPT reduced 90% of the effort, requiring minimal edits and freeing time to test ported scripts thoroughly. We also did the opposite (CloudFormation to Terraform) for another client to become cloud agnostic.”