/amazon-opensearch-service

Index Template Skeleton — Elasticsearch / OpenSearch source

Use this when the source is Elasticsearch or OpenSearch. Most ES/OS mappings carry over 1:1; this skeleton is the audit target for the handful of constructs that need action (see the ES field/mapping → OpenSearch table in source-elasticsearch.md). For Solr sources use solr-index-template-skeleton.md instead.

Migration Assistant for Amazon OpenSearch Service does this for you. Historical Data Migration's metadata-migration phase translates the source mappings + index templates into OpenSearch-compatible form (stripping _type, converting dense_vector→knn_vector, flattened→flat_object) and reindexes documents. This skeleton is for auditing Migration Assistant for Amazon OpenSearch Service's output and for the rare override — NOT a manual step in the migration plan.

{
  "index_patterns": ["<index-name>-*"],
  "template": {
    "settings": {
      "number_of_shards": "<from Step 5 sizing>",
      "number_of_replicas": 1,
      "refresh_interval": "30s",
      "analysis": {
        "analyzer": {
          "<custom_analyzer>": {
            "type": "custom",
            "tokenizer": "<tokenizer>",
            "filter": ["lowercase", "<filter>"]
          }
        }
      }
    },
    "mappings": {
      "properties": {
        "<keyword_field>": { "type": "keyword" },
        "<text_field>": {
          "type": "text",
          "fields": { "keyword": { "type": "keyword", "ignore_above": 256 } }
        },
        "<int_field>": { "type": "integer" },
        "<date_field>": { "type": "date", "format": "strict_date_optional_time||epoch_millis" },
        "<geo_field>": { "type": "geo_point" },
        "<vector_field>": {
          "type": "knn_vector",
          "dimension": "<dim>",
          "method": { "name": "hnsw", "engine": "faiss", "space_type": "l2" }
        }
      }
    }
  }
}

Fill-in checklist

• index_patterns matches the target index / alias name.
• number_of_shards / number_of_replicas come from Step 5 (Estimate Sizing); refresh_interval defaults to 30s for prod per sizing.md, not 1s.
• _type removed. Multi-type (ES 6.x) or _doc-placeholder (ES 7.x) mappings are flattened — types do not exist in OpenSearch (nugget #9).
• fielddata: true stripped from text fields and replaced with a .keyword subfield + doc_values (nugget #8) or the node OOMs on first aggregation.
• dense_vector → knn_vector with an explicit method/engine chosen per the k-NN engine table in vector-knn.md; recall validated against source. [verify] the current default engine for the target version.
• flattened → flat_object.
• Runtime fields are pre-computed at ingest (no runtime mapping equivalent); reindex required.
• _source: {enabled: false} indexes are migrated via Migration Assistant for Amazon OpenSearch Service Historical Data Migration only (nugget #22), and _source is re-enabled on the target.
• Field aliases (alias type) carry over unchanged.
• Painless scripts re-tested; inline scripts noted as a Serverless NextGen blocker if that target is in play.
• Custom analyzers replicated under analysis; filter order preserved (lowercase before synonym_graph/stop).
• Domain-level security verified before deployment: encryption at rest with a customer-managed KMS key (EncryptionAtRestOptions); node-to-node encryption (NodeToNodeEncryptionOptions); HTTPS enforced (EnforceHTTPS: true, TLSSecurityPolicy: Policy-Min-TLS-1-2-2019-07); fine-grained access control with IAM/SAML/OIDC; access policy scoped by principal and source ARN/account. You MUST NOT use 0.0.0.0/0.
• If using a custom domain endpoint, an ACM-managed certificate ARN is configured (CustomEndpoint.CertificateArn). You MUST NOT use a self-managed certificate.

What goes where in the final report

You MUST embed the filled-in template in section 2. Schema / Mapping of the report. You MUST cite the source _mapping field name for each non-trivial mapping decision in the table.