gemini-cli-extensions

gemini-cli-extensions / sre

Public

SRE Extension to provide Site Reliability Engineering tools for Gemini CLI investigations on Google Cloud et al.

14
1
100% credibility
Found Apr 17, 2026 at 14 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

A collection of specialized skills for an AI assistant that helps site reliability engineers investigate outages, detect anomalies, analyze cloud logs and metrics, and generate postmortems.

How It Works

1
📚 Discover the SRE Toolkit

You hear about a helpful collection of tools that supercharges your AI assistant for handling system outages and reliability issues.

2
🔧 Add the Toolkit

With one simple command in your AI assistant, you bring in these specialized reliability skills to make your work faster.

3
🌐 Link Your Cloud Workspace

You tell your assistant about your cloud project once, and it sets everything up securely for smooth investigations.

4
🚨 Report an Outage

When trouble hits, like a cluster going down, you describe the problem to your assistant in plain words.

5
🔍 Let It Investigate

Your assistant pulls in logs, spots weird patterns in data, draws helpful charts, and suggests smart fixes.

🎉 Get Resolutions and Reports

You receive clear mitigations, pretty graphs, and even a ready-to-use summary report to wrap up the incident quickly.

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AI-Generated Review

What is sre?

This Python-based extension packs SRE tools into Gemini CLI for faster Google Cloud investigations. It automates outage triage via playbooks, anomaly detection on time-series data using methods like isolation forests and Z-scores, log exports to Apache format, Monitoring metrics to CSV, and annotated graphs for postmortems. Install once with `gemini extensions install https://github.com/gemini-cli-extensions/sre`, then invoke skills like `investigation-entrypoint` during incidents to fetch metrics, correlate errors, and suggest mitigations.

Why is it gaining traction?

Unlike scattered gcloud scripts or manual API calls, it chains Gemini's AI with Google MCP servers for guided workflows, spitting out SLO setups, revision error reports, and incident visuals without context bloat. As an awesome SRE GitHub repo and Google SRE GitHub counterpart, it hooks devs prepping SRE interviews via GitHub SRE roadmap with ready playbooks and anomaly detectors that output screenshots-ready graphs. Low barrier: one command setups MCP for Logging, Monitoring, GKE.

Who should use this?

GCP SREs triaging GKE or Cloud Run outages, needing quick anomaly hunts or postmortem generators. On-call engineers scripting investigations, or SRE GitHub interview prep folks practicing with real Google SRE GitHub tools like SLO discovery and error correlation. Teams following SRE extensions for standardized response playbooks.

Verdict

Grab it if you're deep in GCP SRE—solid docs and Apache license make it a practical SRE GitHub repo starter, despite 14 stars and 1.0% credibility signaling early maturity. Test in a demo project first; lacks broad validation but accelerates routine probes.

(198 words)

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