Operations | Monitoring | ITSM | DevOps | Cloud

Today, Kosli and Adaptavist announce a strategic partnership to help regulated enterprises automate governance for AI driven software delivery - making it automated, continuous, and evidence-driven rather than a manual checkpoint that sits apart from DevOps and CI/CD. Adaptavist brings deep enterprise DevOps transformation expertise: assessment and strategy, DevSecOps integration, developer experience, and implementation across Atlassian, GitLab, and AWS.

If you’re evaluating compliance controls against your Kosli trail data today, there’s a good chance you’ve written some glue code to make it work. A script that pulls trail data from the API. Another that downloads attestations one by one. Something that mangles the JSON together into a shape that your chosen compliance engine can evaluate. And then that engine itself, whether it’s OPA, a custom Python script, or something else, installed and configured in your pipeline.

Can you create an audit trail for what your AI agent actually did, and enforce rules about what it was allowed to do? Here’s what I found after spending a session wiring the two tools together.

The modern world runs on mission-critical software. It moves our money, drives our cars, diagnoses our illnesses, and fundamentally improves our lives. But, organizations building this critical software face a paradox: they need to move fast to stay competitive, but they also need rigorous governance to manage risk. This has created a lot of tension in regulated industries.

We’re excited to announce support of physical environments in the Terraform Provider for Kosli! What’s Included Environment Management: Full lifecycle support for creating, updating, and managing physical environments types: K8S, ECS, S3, docker, server, and lambda. Manage legacy environments as IaC: Import your existing physical environments to have Terraform manage them.

We’re delighted to announce a strategic partnership between Kosli and TeamTopologies - a collaboration that brings together SDLC Governance automation with the world’s leading framework for organizing business and technology for fast flow of value.

For anyone shipping software in regulated industries, the word “control” gets thrown around all over. Compliance frameworks demand controls, auditors verify controls are used, engineering teams implement controls, and there are even Control Owners. But what exactly is a control? And more importantly, how do we design controls that actually serve their intended purpose while enabling rather than hindering delivery velocity?

ServiceNow is the system of record for change and approvals in most regulated enterprises. And yet, for many teams, it has become the place where delivery slows to a crawl. Not because ServiceNow is broken. But because the evidence model underneath it is. Developers ship fast through modern CI/CD pipelines, automated tests, and security scans, only to hit a wall when changes reach approval. Tickets bounce back. Evidence is questioned. Screenshots do not tell the full story. CABs hesitate. Releases wait.

In regulated environments, slow change is often blamed on process. Too many approvals. Too much governance. Too much red tape. But in reality, most delays are not caused by regulation itself. They are caused by missing, fragmented, or untrusted evidence. Screenshots pasted into tickets. Proof assembled weeks later. Approvals stalled because no one can confidently say whether a change actually meets policy. When evidence is an afterthought, compliance turns into chaos.

Imagine for a moment that agentic coding tools really do deliver on their promise. Code is written faster, tests are generated automatically, and refactors that once took days now take minutes. On paper, software delivery should accelerate dramatically. Now imagine you work in a regulated enterprise. The code is ready, but production is still days or weeks away.