I built a small Java CLI that uses Groq’s LLM API to turn noisy server logs into structured incident summaries: root cause, severity, affected components, and suggested fixes. Introduction Server logs are useful, but during an incident they can also become overwhelming. A single failure can produce hundreds or thousands of lines in a few minutes. You search for ERROR , skim stack traces, follow timestamps, jump between services, and slowly piece together what actually happened. The problem is not that logs are useless. The problem is that logs are raw events, not explanations. I built ai-log-analyzer to explore a simple idea: Can a Java CLI turn noisy server logs into a short, structured incident summary using an LLM? This is not meant to replace observability platforms, incident response workflows, or proper monitoring. It is a small developer tool that shows how LLMs can help summarize unstructured operational data.…