I'm curious about how people are incorporating AI agents into their everyday DevOps tasks beyond just code generation. For instance, while I've heard of RooCode's capabilities for generating Infrastructure as Code, I'm looking for more diverse examples. Has anyone had any interesting experiences or implementations they could share?
5 Answers
Lately, we've been using AugmentCode, and it's great! Its auto agent feature is super fast—I was able to whip up scripts much quicker than I could manually, so it's definitely a time-saver.
We've been exploring AI agents for tasks like PR reviews, tagging, and refactoring. GitLab is diving deep into AI and is reportedly integrating it into their failure pipelines. I'm excited to see what that brings when we get a chance to try it out!
I recently launched an AI-powered GitHub app called Zumbro. It auto-generates pre-commit configurations with your choice of Python linters and formats, and also creates pull requests for any necessary corrections it finds. I'm looking for feedback on how well it works and any additional features people want!
I'm building an orchestrator with integrated MCP where agents create scripts from instructions and test them in a safe environment. It can even analyze failures and apply fixes automatically before alerting the team. It should streamline a lot of processes once it’s fully functional!
That sounds awesome! Do you have any resources on MCP? I’d love to learn more about it.
Elastic is offering some cool solutions that analyze error behavior based on your logs, which could be really useful in a production setting.
That sounds interesting! How does it compare to other tools you've tried?