AgentSkillsCN

elasticsearch

精通Elasticsearch DBA技能，擅长索引与映射设计、查询调优、集群规模与运维管理、分片与副本策略、生命周期管理（ILM）、监控与故障排查（如热节点、GC、拒绝请求），以及安全的重新索引与升级操作。适用于设计搜索架构、诊断性能问题，以及在生产环境中高效运维Elasticsearch集群等任务。

SKILL.md
--- frontmatter
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).