Igniters AutoFix

Inspiration

Modern software development heavily relies on CI/CD pipelines, yet one of the most common frustrations developers face is pipeline failure due to small, repetitive issues such as missing dependencies or configuration errors. These failures interrupt workflow and waste valuable debugging time.

We wanted to reduce this friction by creating an intelligent system that not only detects failures but actively helps resolve them. The idea was simple: instead of developers fixing CI issues manually, let an autonomous agent handle it.

What it does

Igniters AutoFix is an autonomous GitLab agent that monitors CI/CD pipelines, detects failures, analyzes error logs, and generates actionable fixes automatically.

When a pipeline fails, the agent:

Reads the failure logs
Identifies common error patterns
Suggests a fix (e.g., missing dependency)
Outputs a ready-to-apply solution

This transforms CI from a passive system into an active assistant.

How we built it

We built the project using Python and GitLab CI pipelines.

A failing CI job is intentionally triggered
A secondary job runs on failure using GitLab’s when: on_failure
The agent parses error logs and applies rule-based analysis
Fix suggestions are generated and saved as artifacts

The system is lightweight, fast, and designed to integrate directly into existing GitLab workflows.

Challenges we ran into

One of the key challenges was designing a system that works reliably within the constraints of a CI environment. Since pipelines are ephemeral, capturing and analyzing logs in a meaningful way required careful structuring.

Another challenge was balancing simplicity and usefulness. Instead of building an overly complex AI system, we focused on creating a deterministic and explainable solution that works consistently.