Elasticsearch Mastery (Senior → Principal)

Operate

• Start with query patterns, relevance requirements, data freshness, and retention.
• Treat mapping, analyzer, shard count, and indexing strategy as architectural choices.
• Optimize for predictable operations, not demo-search quality only.
• Distinguish logging/observability use-cases from user-facing search needs.

Default Standards

• Mappings should be explicit on important fields.
• Shards are not free; oversharding is an operational tax.
• Relevance tuning requires representative queries and evaluation, not intuition.
• Observe indexing throughput, search latency, heap pressure, GC, and shard health.

References

• Indexing and query design: references/indexing-and-query-design.md
• Operations and relevance: references/operations-and-relevance.md
• Mappings and analyzers: references/mappings-and-analyzers.md
• Query DSL and scoring: references/query-dsl-and-scoring.md
• Shards and cluster layout: references/shards-and-cluster-layout.md
• Indexing pipelines: references/indexing-pipelines.md
• Search relevance: references/search-relevance.md
• Aggregations and analytics: references/aggregations-and-analytics.md
• ILM and retention: references/ilm-and-retention.md
• Capacity planning: references/capacity-planning.md
• Security and multi-tenant: references/security-and-multi-tenant.md
• Backup, restore, and snapshots: references/backup-restore-and-snapshots.md
• Observability: references/observability.md
• Logging vs search clusters: references/logging-vs-search-clusters.md
• Incident runbooks: references/incident-runbooks.md