Explore how Terramate can uplift your IaC projects with a free trial or personalized demo.
However, while working with customers, we learned that many IaC practitioners are non-expert users and thus often struggle to understand those changes. With AI Mate, you can now summarize and explain the changes among all affected stacks to provide a comprehensive explanation to non-expert users in natural language.
As you can see in the screenshot above, using AI Mate transforms a complex overview of changes in multiple stacks into an easy to understand summary, allowing developers to make sense of the impact of a pull request without having to understand all technical details which allows them to move faster and with confidence.
Similar to the capability of explaining changes in pull requests, AI Mate helps developers to summarize and explain deployments.
This is especially handy in case of failed deployments, where a developer just wants to understand the reason for the failure quickly without having to scroll through and decipher endless logs. AI Mate provides precise explanations of why a deployment has failed and includes potential resolution paths as well, allowing developers to quickly fix broken stacks.
Drift is an often misunderstood concept in Terraform, OpenTofu, and other IaC technologies. Many practitioners struggle to understand what drift is and why it even exists in the first place. Terramate Cloud is already helping thousands of organizations detect and remediate drift with scheduled and post-deployment drift detection and alerts. But to deeply understand the root causes of drift, a developer often has to rely on a thorough command of the affected cloud resource complexities and interactions.
AI Mate again understands and explains the drift in detail without users having to dig deep into the details. It’s an enormous time saver and allows non-expert users to quickly remediate drift with confidence.
How does AI Mate work?
AI Mate is now available in Terramate Cloud for all plans, including our free Community tier.
It relies on data synced via Terramate CLI, which in turn looks at plan files and CI/CD logs, sanitizes the data for any sensitive values, and syncs it to Terramate Cloud. Note that this sync is done in a push model, i.e. DevOps/platform engineers retain full control over which data is synced and which isn’t. Terramate Cloud then leverages a host of different LLM models to generate what we feel are pretty accurate AI summaries.
While the summaries work well in a lot of cases, with the current underlying LLM technology, we cannot guarantee 100% accuracy. What we do find is that the smaller the size of a stack is, the better the accuracy. A smaller context window is yet another good reason to split your state.
If you want to explore how AI Mate can help you move faster, create a free account with Terramate Cloud or book a demo call with one of our experts.
Explore how Terramate can uplift your IaC projects with a free trial or personalized demo.