env0 this week added at the KubeCon + CloudNativeCon Europe 2025 conference an artificial intelligence (AI) agent to its platform for automating the management of infrastructure-as-code (IaC) workflows using open source Terraform tools.
Company VP of marketing, Chris Graham, said Cloud Analyst via a natural language interface enables DevOps teams to surface insights into performance issues and other inefficiencies that are adversely impacting deployments by harmonizing diverse data from IT environments. It can, for example, identify metrics such as the number of drifts detected over the past month, quarter, or year and via a dashboard, track deployment times and actual success rates.
DevOps teams can also easily create custom charts, visualizations and filters for specific teams or projects without having to first collect and normalize the data required themselves.
The overall goal is to make it possible for DevOps teams to continuously monitor infrastructure configurations created using IaC or provisioned manually, said Graham.
That’s critical because while many IT teams today routinely use IaC tools to provision cloud infrastructure, there are still many cloud instances that were manually configured, noted Graham.
The env0 platform currently supports cloud instances running on Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP) and Oracle Cloud Infrastructure (OCI) to enable DevOps teams to manage and govern IaC workflows across a heterogeneous IT environment. In the future, env0 plans to also provide a bring-your-own-cloud option, added Graham.
It’s not clear how aggressively DevOps teams will adopt AI agents to manage IT environments, but a recent Futurum Research survey finds 41% of respondents expect generative AI tools and platforms will be used to generate, review and test code, while 39% plan to make use of AI models based on machine learning algorithms. More than a third (35%) also plan to apply AI and other forms of automation to IT operations, the survey finds.
Given the relative immaturity of AI agents, many IT teams are going to be hesitant to rely on large language models to actually provision IT environments. However, AI agents such as Cloud Analyst will make it simpler to analyze configurations in a way that should reduce mistakes and improve cybersecurity posture management.
Over time, those AI agents will also make it simpler to incorporate FinOps data that will enable DevOps teams to also better optimize cloud computing environments, noted Graham. The challenge is bringing together all the data required to enable AI agents to provide IT teams with a full 360-degree view of increasingly complex cloud computing environments, he added.
Regardless of the approach to agentic AI, roles and responsibilities on DevOps teams will be changing as many of the manual processes that conspire to make managing IT environments tedious are automated. AI agents won’t replace the need for DevOps engineers any time soon, but the ability to manage highly dynamic application environments at levels of scale that might have once seemed unimaginable will soon become fairly commonplace. The challenge and the opportunity now is determining how best to manage all the AI agents that are being incorporated into the DevOps workflow.
