Diagnose bottlenecks in TiKV scale-out and scale-in operations for TiDB clusters.
npx skills add https://github.com/alex-quan-001/nutshell-skills --skill tikv-scale
Please help me install this Agent Skill. Skill: tikv-scale Source: https://github.com/alex-quan-001/nutshell-skills/tree/main/skills/diagnosis/tikv-scale Command: npx skills add https://github.com/alex-quan-001/nutshell-skills --skill tikv-scale
This Skill eliminates guesswork when troubleshooting slow or stuck TiKV scale-out and scale-in operations in TiDB clusters, helping you quickly identify whether the bottleneck lies in PD operator generation or TiKV data migration.
Use the tikv-scale skill to diagnose why your TiDB cluster's TiKV scale-in operation is stuck and identify the root cause bottleneck.
High-intent search queries and answers about installing and using this skill.
An empty TiKV node after scale-out indicates a bottleneck in PD operator creation or TiKV data migration. Diagnosing PD scheduling metrics and logs helps pinpoint if slow balance-region operators prevent snapshot migration from initiating.
To troubleshoot stuck TiKV scale-in operations, analyze PD logs for replace-rule-offline-* operator delays and inspect TiKV store state transitions. Identifying whether the bottleneck is in operator generation or data migration guides the exact resolution steps.
Slow PD operator creation during TiKV store migration stems from scheduling configuration issues or cluster constraints. Analyzing PD scheduling metrics isolates the bottleneck, enabling specific configuration knob recommendations to accelerate balance-region operations.
Diagnosing stuck add learner operations requires checking TiKV snapshot migration performance and store state transition logs. Applying workflow heuristics isolates the delay, providing configuration adjustments to resolve the scaling bottleneck.
Yes, you can diagnose TiKV snapshot migration performance issues by analyzing store state transition delays and PD operator logs. This approach provides workflow heuristics and configuration recommendations to resolve scaling bottlenecks.
Diagnosing TiKV scaling bottlenecks relies on accessing accurate PD scheduling logs and TiKV state metrics. Without proper log access, identifying slow operator creation or stuck add learner operations remains constrained by available diagnostic data.
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