Restructure the Elasticsearch search docs into a task-oriented IA

[kosabogi]

Summary

Restructure the Elasticsearch search documentation from a feature-organized reference into a task-oriented path.

Overall flow:

Get Started → Set Up → Ingest → Search → Monitor and Tune → Manage → Go to Production

Plus: Chat with Your Data, Advanced, Guides, Troubleshoot.

Each section is a sub-issue of this one.

Sections

• Get Started: quickstart and Elasticsearch basics, before any architecture decision
• Set Up: choose a deployment type and connect
• Ingest: get content in, including inference setup for semantic content
• Search: full-text, vector, semantic, hybrid, multimodal, querying, filtering, quality, aggregations
• Monitor and Tune: performance, relevance, ranking
• Manage: APIs, mapping, indices, vector storage, Agent Builder
• Go to Production: security, performance, capacity planning
• Chat with Your Data: RAG
• Advanced: manual embedding pipelines
• Guides: end-to-end scenarios
• Troubleshoot: symptom-first entries

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[kosabogi]

https://github.com/elastic/developer-docs-team/issues/282 keep this in mind while working on the new IA