aiopsre

aiopsre / rca-api

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🚀 An AI-native RCA platform for incident ingestion, evidence governance, runtime orchestration, and async diagnosis delivery. Built to help teams close the loop from alerts to diagnosis. 🚀 一款面向故障根因分析的 AI Native RCA 平台，覆盖告警接入、证据治理、运行时编排与异步诊断交付，帮助团队打通从告警到诊断的闭环。

11
1
89% credibility
Found Apr 07, 2026 at 11 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Go
AI Summary

API server for a root cause analysis platform that ingests alerts from monitoring systems, collects evidence from Kubernetes/Prometheus/Elasticsearch, runs multi-agent AI diagnosis jobs, and manages operator workflows with audit trails.

How It Works

1
🚨 Spot a problem alert

You get a notification that something's wrong with your app or service.

2
📤 Send alert to analyzer

Forward the alert to the smart analyzer which starts investigating automatically.

3
🔍 AI digs for clues

The system gathers clues like metrics and logs, then uses AI to find the root cause.

4
📋 Review findings

Check the AI's diagnosis, evidence, and suggested fixes in a clear dashboard.

5
Approve or rerun
✅
Approve fix

Greenlight the solution and watch it resolve the issue.

🔄
Rerun analysis

Request deeper checks with new time ranges or hints.

🎉 Problem solved

Your service is back to normal with full audit trail of what happened.

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Star Growth

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AI-Generated Review

What is rca-api?

rca-api is an ai-native RCA API built in Go for ingesting alerts, governing evidence from K8s/Prom/ES, orchestrating runtime workflows, and delivering async AI diagnosis. It closes the loop from alerts to root cause analysis via REST endpoints like /v1/ai/jobs for queuing, starting, and finalizing jobs. Developers get a docker-compose stack with MySQL, Redis pub/sub for queue wakeups, and an ai-orchestrator for tool calls.

Why is it gaining traction?

It handles real SRE pain with adaptive long-polling for ai jobs, Redis streams for notice delivery, and MCP policy for tool limits—async, resilient, no busy-waiting. Stands out from basic alert routers by baking in evidence governance and multi-agent diagnosis delivery, plus metrics/healthz for observability. Quick local setup beats stitching disparate AIOps tools.

Who should use this?

SREs and DevOps engineers automating incident RCA in microservices environments, especially those spiking on ai-native development github flows with alerts and evidence. Teams closing diagnosis loops via API integrations like salesforce rca api or custom alert ingestion, tired of manual evidence hunts.

Verdict

Grab it for prototyping ai-native RCA pipelines—docker-compose spins up apiserver, notice-worker, and orchestrator fast, with solid Makefile/tests. At 11 stars and 0.9% credibility, it's early but production-ready for small teams; scale cautiously until more adoption.

(198 words)

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