troubleshoot-zookeeper

What problem does it solve?

It helps diagnose Apache ZooKeeper failures by mapping common incident archetypes (quorum loss, write stalls, GC pause cascades, session storms, heap/OOM, and snapshot stalls) to the exact Netdata signals you need, using MCP queries for structured triage and remediation recommendations.

Core Features & Use Cases

• Operator-playbook diagnostic tree: Routes a coding agent through ZooKeeper health domains (availability, latency, throughput, connections/sessions, replication/sync, data tree/memory, errors/integrity, JVM/resources, security) to narrow root cause.
• MCP-based signal verification: Performs discovery and verification via list_metrics, query_metrics, and anomaly ranking via find_anomalous_metrics against the relevant zookeeper.* contexts.
• Remediation confirmation loop: Re-runs the same MCP verification queries after applying remediation to confirm signals return to expected ranges.

Quick Start

Ask an AI agent to troubleshoot your Apache ZooKeeper with Netdata using MCP by querying the ZooKeeper zookeeper.* contexts for the last 15 to 30 minutes, selecting the correct failure archetype, then applying the remediation and verifying the signals recover.