nudgebee/nudgebee
Unified CloudOps platform with AI-SRE, AI-FinOps, AI-K8sOps, and the Agentic Automation Builder without fragmented tools, context switching, or model lock-in.
What it solves
Nudgebee is an open-source SRE copilot designed to simplify observability, incident response, and cloud cost management (FinOps) across Kubernetes and major cloud providers (AWS, Azure, GCP). It helps operators move from raw signals to actionable findings and guided remediation.
How it works
Nudgebee uses a distributed architecture of Go, Python, and TypeScript services to monitor infrastructure. It ingests data via cloud-provider scans and Kubernetes collectors, then processes this information through several specialized servers:
- LLM & RAG Servers: Use agentic planners and retrieval-augmented generation to root-cause incidents and propose fixes.
- Runbook Server: Orchestrates recurring fixes using Temporal workflows.
- ML Server: Employs Python-based ML pipelines to recommend right-sizing for Kubernetes workloads.
- Collector & Relay Servers: Bridge in-cluster agents to a central control plane.
- ChatOps: Integrates with Slack and Teams to allow SREs to query state and run runbooks directly from chat.
Who it’s for
It is built for Site Reliability Engineers (SREs) and platform operators who manage complex Kubernetes environments and multi-cloud deployments.
Highlights
- LLM-powered triage: Agentic planners that can reproduce and root-cause incidents.
- FinOps optimization: Identifies idle workloads, oversized pods, and stale snapshots to reduce cloud spend.
- Runbook automation: Codifies recurring fixes into reusable, triggerable workflows.
- Bidirectional ticketing sync: Integrates with Jira, ServiceNow, PagerDuty, and Zenduty.
- Multi-cloud support: Native observability and scanning for AWS, Azure, and GCP.