Claude Code Plugins

Community-maintained marketplace

Feedback

elasticsearch

@muzhicaomingwang/ai-ideas
1
0

Elasticsearch DBA skill for index/mapping design, query tuning, cluster sizing and operations, shard/replica strategy, ILM, monitoring, troubleshooting (hot nodes, GC, rejected requests), and safe reindexing/upgrades. Use for tasks like designing search schemas, diagnosing performance issues, and operating ES in production.

Install Skill

1Download skill
2Enable skills in Claude

Open claude.ai/settings/capabilities and find the "Skills" section

3Upload to Claude

Click "Upload skill" and select the downloaded ZIP file

Note: Please verify skill by going through its instructions before using it.

SKILL.md

name elasticsearch
description Elasticsearch DBA skill for index/mapping design, query tuning, cluster sizing and operations, shard/replica strategy, ILM, monitoring, troubleshooting (hot nodes, GC, rejected requests), and safe reindexing/upgrades. Use for tasks like designing search schemas, diagnosing performance issues, and operating ES in production.

elasticsearch

Use this skill for Elasticsearch（ES）相关设计、性能与运维（DBA/中间件）任务。

Defaults / assumptions to confirm

  • ES version and deployment (self-hosted / managed)
  • Cluster topology (nodes, roles, storage type)
  • Data volume and retention requirements
  • Query patterns (search vs analytics) and latency SLO

Workflow

  1. Understand use-cases and query patterns
  • Primary user journeys: keyword search, filtering, aggregations, sorting.
  • Write patterns: append-only logs vs frequent updates.
  • Required consistency and freshness (near real-time delay tolerance).
  1. Index & mapping design
  • Define index naming convention and templates.
  • Choose correct field types (keyword vs text, date, long, scaled_float).
  • Analyze/analyzer strategy for language (e.g., Chinese tokenizer) if needed.
  • Avoid mapping explosion; control dynamic mappings.
  • Plan _source and stored fields usage; consider doc values.
  1. Shards and replicas
  • Pick shard count with future growth and reindex cost in mind.
  • Avoid too many small shards; target shard size range (e.g., 10–50GB) depending on workload.
  • Set replicas for availability and read scaling.
  1. Query tuning
  • Use profile and slow logs to find bottlenecks.
  • Reduce heavy aggregations; precompute when possible.
  • Use filters with keyword fields; cache-friendly queries.
  • Pagination: prefer search_after for deep pages; avoid large from+size.
  1. Lifecycle management
  • Use ILM (hot-warm-cold-delete) for time-series data.
  • Rollover policies by size/time; manage retention.
  1. Cluster operations & stability
  • Monitor heap, GC, CPU, disk watermarks, thread pool rejections.
  • Detect hot keys/indices; rebalance shards carefully.
  • Snapshot/restore; restore drills; retention policy.
  1. Safe changes
  • Mapping changes often require reindex; plan alias-based migrations.
  • Use index aliases for zero-downtime cutover.
  • Upgrade runbook: compatibility, rolling upgrade, backout plan.

Outputs

  • Mapping/index template proposal + rationale.
  • Shard/replica sizing plan + expected capacity.
  • Performance diagnosis report (evidence → root cause → fixes).
  • Migration plan (reindex + alias cutover + verification).