🚀 Over the past two years, one field that has profoundly impacted everyone's lives is Large Language Models (LLMs). They have seamlessly integrated into our daily lives and continue to evolve rapidly . However, DevOps remains in the exploratory phase when it comes to effectively utilizing the power of LLMs.

🛠️Today, I'm thrilled to share a project I've been working on for quite some time: DevOps GPT . As we often say, the best way to debug an issue is to dive into the logs. But what if we could take this a step further? With DevOps GPT, we leverage the power of LLMs to analyze logs, provide recommendations, and suggest solutions to complex problems.

💡 What Makes DevOps GPT Different? 
1️⃣ Pre-Built SRE Logic: It includes a substantial amount of Site Reliability Engineering (SRE) logic, reducing the need to query the LLM for every error. This makes it faster and more efficient.
2️⃣ Caching Layer: DevOps GPT comes with a built-in caching mechanism, ensuring that similar queries retrieve cached results, significantly improving performance.

✅ Current Features: 
1️⃣ LLM Support: Supports both OpenAI and LLAMA, with OpenAI set as the default.
2️⃣ Platform Compatibility: Currently, the RPM is compiled for RedHat 🐧, with plans to support additional platforms soon.
3️⃣ Slack Integration: Alerts are integrated with Slack, so you never miss critical updates.

🔮 What's Next? 
I plan to integrate DevOps GPT with other LLMs in the future and expand its capabilities to cater to a wider range of use cases.

📝 I'd love for you to give it a try and share your feedback . Your insights will help me improve and make DevOps GPT even better. Let's shape the future of DevOps together! 

⬇️ Project link: https://github.com/thedevops-gpt/devops-gpt