sre-extension

Note: Given the recent deprecation of Gemini CLI, this Extension is also fully functional as a Plugin for agy CLI, Claude Code, and Codex.

About

The SRE Gemini CLI Extension is a dedicated toolkit comprising specialized Skills designed to augment Site Reliability Engineers (SREs). By integrating deeply with the Gemini CLI, this extension empowers SREs to investigate outages, configure MCP servers, formulate mitigations, and detect anomalies more rapidly.

See also:

• Reference PostMortems we've created with this tool.
• SRE Testing Suite to test your setups (currently a work in progress).

Installation

For detailed installation and configuration instructions across all CLI environments, please refer to the Installation Guide (INSTALL.md).

If you have just (a modern make clone) installed, you can quickly set up the extension. If you don't have just yet, you can quickly install it via brew install just / sudo apt-get install just (or see casey/just for more options).

Once installed:

# Google Antigravity CLI (agy)
just install-agy
# Google Gemini CLI (deprecated)
just install-gemini
# Claude Code
just install-claude

Available Skills

🛠️ Core SRE Skills

• investigation-entrypoint: Primary entrypoint for investigating production outages, orchestrating SRE response, and mitigating incidents. Start here when an incident occurs!
• gcp-playbooks: Follows established SRE playbooks for GCP/GKE investigations, including infrastructure discovery and common mitigation steps.
• gcp-mcp-setup: Automates enabling services, Google Managed MCP (OneMCP) servers, generating API keys, and configuring ~/.gemini/settings.json.
• gcp-slo-management: Discover Monitoring Services, list existing SLOs, or create new SLOs (Availability/Latency) via the REST API.
• postmortem-generator: Creates a generated PostMortem given enough context about a resolved incident/outage.

☁️ Cloud Capabilities

• cloud-build-investigation: Expert-level SRE skill for Google Cloud Build (GCB) and Cloud Run investigations. Correlates git commits with build failures and analyzes logs.
• cloud-logging: Skill for interacting with and analyzing Google Cloud Logging and Error Reporting. Processes large JSON logs or converts them to Apache format.
• cloud-monitoring: Interacts with Google Cloud Monitoring via APIs to avoid large context bloat. Exports time-series data and helps setup SLOs.

📊 Detection, Graphs & Mitigations

• generic-mitigations: Generic Mitigations high-level classification logic and actuation plan.
• monitoring-graphs: Generates high-quality, annotated incident graphs for post-mortems using Python to visualize outages and error rates (nice graphs visible here).
• anomaly-detection: Detects anomalies in time-series data from various sources (Isolation Forest, KNN, Z-score).
• data-ingestion: Fetches and parses time-series data from various sources for downstream analysis.

Compatibility & Harness Support