Full-text search in Cosmos DB

Security for Full-text search in Cosmos DB starts with queryable text paths, sensitive fields, account keys or Entra permissions, private endpoints, diagnostic logs, SDK access, data classification, and whether search exposes regulated content. Review who can create, update, delete, execute, read logs, approve dependencies, and manage credentials or identities. Prefer Microsoft Entra ID, managed identity, private networking, least privilege, and audited automation where the service supports them. Keep secrets out of code and avoid broad public exposure unless there is a documented exception. Capture role assignments, diagnostic settings, policy decisions, Activity Log entries, and owner approvals so access and data handling are intentional and reviewable.

Cost for Full-text search in Cosmos DB is driven by request units for text queries, indexing overhead, data size, cross-partition queries, diagnostics, provisioned throughput, serverless usage, failed experiments, and duplicate external search systems. The expensive mistake is not only Azure consumption; it can also be duplicate experiments, emergency support, overprovisioned capacity, unnecessary data transfer, or cleanup after weak design evidence. Review whether the workload truly needs the selected tier, retention, diagnostics, network path, scale rule, cache behavior, or automation pattern. Use tags, budgets, alerts, and cleanup reviews so teams can explain why the design exists and remove stale resources safely.

Reliability for Full-text search in Cosmos DB depends on index policy correctness, feature enablement, partition design, RU availability, SDK behavior, consistency expectations, query fallback, regional failover, and how policy changes affect production traffic. A resource can be present and still fail the business workflow if routing, identity, quota, storage, code, cache, scale, or downstream health is wrong. Test failure modes, retries, deployment behavior, disabled states, rollback steps, and maintenance windows before relying on the design. During incidents, compare platform metrics, logs, deployment history, and application traces from the same time window before changing production. The goal is a recoverable configuration support teams can verify quickly.

Performance for Full-text search in Cosmos DB depends on index selectivity, partition key design, query functions, text path count, RU budget, result size, continuation tokens, SDK options, regional latency, and whether hybrid search also uses vectors. Measure platform metrics and application-side completion times because a fast control-plane response does not prove users received the right result. Test with realistic regions, data sizes, concurrency, authentication paths, route choices, cache state, package size, and downstream limits. When performance regresses, compare configuration changes, resource limits, client logs, diagnostic data, and workload timing before adding capacity or blaming one service. Tune with evidence from the exact environment and traffic pattern.

Operations for Full-text search in Cosmos DB require policy review, query testing, RU monitoring, feature registration evidence, SDK version tracking, deployment approvals, search relevance checks, and rollback of container indexing changes. Before a change, capture read-only CLI output, portal evidence when useful, owner tags, expected behavior, and rollback steps. During incidents, avoid changing several settings at once; compare metrics, logs, deployment operations, identity evidence, network state, and downstream health first. Keep runbooks clear enough for support teams to verify current behavior quickly. Good operations make the term observable, reviewable, and recoverable during releases, audits, and incidents. Review owner, scope, evidence, dependencies, and rollback before production change.