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OpenSearch · Search and Analytics

Shard sizing, cluster yellow states, and the query that melts a node.

Outcome

    • Explain the three access layers: domain policy → IAM policy → FGAC role mapping
    • Explain why all three 403 failures look identical and the debugging order
    • Map an IAM role to an OpenSearch FGAC role via _plugins/_security/api/rolesmapping
    • Explain when to use VPC vs public endpoint
    • Define an index with explicit mappings: text, keyword, float, date, geo_point, boolean
    • Use multi-field mapping for fields needing both full-text search and aggregation
    • Explain why mapping type changes on existing fields are forbidden
    • Create an index alias and explain the zero-downtime reindex swap pattern
    • Explain what "index": false does and when to use it
    • Bulk index documents using NDJSON format
    • Explain why Bulk API returns HTTP 200 even when individual documents fail
    • Check .errors and .items[*].index.error in bulk responses
    • Explain near-real-time indexing (1-second default refresh)
    • Use match for text fields and term for keyword fields
    • Build a bool query with must, filter, should clauses
    • Explain why structured conditions belong in filter not must
    • Write a geo_distance filter and sort results by distance
    • Use multi_match with field boosting and fuzziness: AUTO
    • Build a faceted search returning results + sidebar counts in one request
    • Use terms, range, histogram, and stats aggregations
    • Nest sub-aggregations to compute per-bucket metrics
    • Explain why terms returns 10 buckets by default and set explicit size
    • Explain why aggregations on text fields fail
    • Build DynamoDB → Streams → Lambda → OpenSearch sync pipeline
    • Handle INSERT, MODIFY, and REMOVE events correctly
    • Explain why forgetting REMOVE creates ghost documents
    • Explain why bulk index is idempotent and makes Lambda retries safe
    • Verify end-to-end: DynamoDB write → searchable in OpenSearch within seconds

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