siclaw and awesome-ai-sre

An operational platform with automated diagnostics and investigation capabilities complements a curated collection of specialized AI-SRE tools, where the former provides unified incident response infrastructure while the latter catalogs point solutions for RCA, cost optimization, and DevOps automation.

siclaw
55
Established
awesome-ai-sre
46
Emerging
Maintenance 13/25
Adoption 14/25
Maturity 20/25
Community 8/25
Maintenance 13/25
Adoption 7/25
Maturity 9/25
Community 17/25
Stars: 69
Forks: 4
Downloads: 550
Commits (30d): 0
Language: TypeScript
License: Apache-2.0
Stars: 25
Forks: 8
Downloads:
Commits (30d): 0
Language: JavaScript
License: MIT
No risk flags
No Package No Dependents

About siclaw

scitix/siclaw

AI-powered SRE platform — read-only infrastructure diagnostics with deep investigation, security governance, and team collaboration

Implements a four-phase investigation workflow (evidence gathering, hypothesis testing, root-cause analysis) with investigation memory that learns from past incidents to improve diagnostics. Supports three deployment modes—TUI for single users, local server with SQLite for team use, and Kubernetes with isolated AgentBox pods—all extensible via Model Context Protocol (MCP) for connecting external tools and data sources. Built on Node.js with TypeScript, uses pi-coding-agent or Claude Agent SDK for reasoning, and integrates with Kubernetes, Slack, Lark, Discord, and Telegram for multi-channel access.

About awesome-ai-sre

pavangudiwada/awesome-ai-sre

AI SRE tools for RCA, Incident Response, Cost-Saving, Infra management, DevOps and more

A curated catalog of 100+ AI SRE tools organized by function (incident response, observability, AIOps, IaC, security, deployment), with both open-source and commercial solutions. The repository auto-generates its tool index using CI workflows, tracking recent additions and providing direct links to GitHub repos, websites, and vendor channels for each integration. Targets cloud-native and enterprise DevOps teams evaluating agentic AI platforms for production reliability workflows.

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