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elasticsearch

Diagnose unassigned shards and optimize Elasticsearch cluster performance.

Updated Feb 26, 2026
Search Tags:#analytics#search#elasticsearch#cluster management#ilm#mappings#query dsl
One-click install
npx skills add https://github.com/gagan114662/exp --skill elasticsearch-gagan114662
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: elasticsearch
Source: https://github.com/gagan114662/exp/tree/main/crates/openfang-skills/bundled/elasticsearch
Command: npx skills add https://github.com/gagan114662/exp --skill elasticsearch-gagan114662

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides expert guidance for managing and optimizing Elasticsearch clusters, enabling efficient search, log analytics, and time-series data platforms.

Core Features & Use Cases

  • Querying and Mapping: Design explicit mappings and construct complex queries (bool, match, term).
  • Index Management: Utilize index aliases and ILM policies for zero-downtime operations and data retention.
  • Performance Tuning: Optimize search performance and diagnose cluster allocation issues.
  • Use Case: Troubleshoot an Elasticsearch cluster showing a yellow status by diagnosing unassigned shards and applying corrective measures.

Quick Start

Use the elasticsearch skill to explain why shards are unassigned in the current cluster.

Frequently Asked Questions about elasticsearch

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
Why does my Elasticsearch cluster show a yellow status and how do I fix unassigned shards?▼

An Elasticsearch cluster shows yellow status when replica shards are unassigned. You can diagnose this by checking cluster allocation issues and applying corrective measures to restore shard distribution.

How do I design explicit mappings and build complex queries in Elasticsearch?▼

Designing explicit mappings in Elasticsearch involves defining field data types upfront. You then construct complex queries using bool, match, and term clauses within the query DSL for efficient search operations.

What is the best way to manage index aliases and apply ILM policies for data retention?▼

Managing index aliases involves using them for zero-downtime reindexing operations. You apply Index Lifecycle Management (ILM) policies to automate data retention and manage the time-series data lifecycle.

How do I optimize Elasticsearch search performance for log analytics pipelines?▼

Optimizing Elasticsearch search performance requires tuning cluster configurations and query structures. This ensures efficient processing for log analytics pipelines and time-series data platforms.

When do I need explicit mapping design for my Elasticsearch indices?▼

Explicit mapping design is needed when you require precise control over field data types and search behavior. It prevents dynamic mapping errors and ensures efficient querying with bool and match clauses.

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