Cosmosdb

Azure Cosmos DB indexing strategy best practices: excluding unused paths, composite indexes for ORDER BY, spatial indexes, index types, path syntax, and indexing modes (consistent vs lazy). USE FOR: Cosmos DB indexing policy, exclude paths, composite index, spatial index, index path syntax /? /* /[], range vs hash index, lazy vs consistent indexing, index direction, write overhead reduction. DO NOT USE FOR: query optimization (use cosmosdb-query-optimization), full-text search indexes (use cosmosdb-full-text-search), vector indexes (use cosmosdb-vector-search).

Azure Cosmos DB security best practices: disabling local authentication (keys), managed identity with DefaultAzureCredential, network access restrictions, RBAC least privilege, and continuous backup for point-in-time restore. USE FOR: Cosmos DB security, disable local auth, disable keys, managed identity, DefaultAzureCredential, Entra ID, network restrictions, IP firewall, private endpoints, RBAC roles, least privilege, data plane roles, continuous backup, point-in-time restore, PITR, zero-trust. DO NOT USE FOR: client-side encryption (pending), SDK authentication code (use cosmosdb-sdk).

Azure Cosmos DB monitoring and diagnostics best practices: RU consumption tracking, P99 latency monitoring, throttling alerts, Azure Monitor integration, and diagnostic logging. USE FOR: Cosmos DB monitoring, RU consumption, request units tracking, P99 latency, throttling alerts, 429 monitoring, Azure Monitor, diagnostic logs, metrics, alerts, performance monitoring, troubleshooting, observability. DO NOT USE FOR: SDK diagnostics logging (use cosmosdb-sdk), throughput right-sizing (use cosmosdb-throughput).

Azure Cosmos DB throughput and scaling best practices: autoscale for variable workloads, right-sizing provisioned throughput, serverless for dev/test, burst capacity, and container vs database throughput allocation. USE FOR: Cosmos DB autoscale, provisioned throughput, serverless, burst capacity, RU/s sizing, container throughput, database throughput, cost optimization, over-provisioning, under-provisioning, throttling prevention. DO NOT USE FOR: RU consumption monitoring (use cosmosdb-monitoring), partition key design (use cosmosdb-partition-key).

Azure Cosmos DB data modeling best practices: embedding vs referencing, document size limits, schema versioning, type discriminators, JSON serialization, denormalization, and relationship patterns. USE FOR: Cosmos DB document design, embedding related data, referencing large data, 2MB item limit, nesting depth, numeric precision, denormalize reads, schema versions, type discriminator, polymorphic containers, JSON serialization, relationship references. DO NOT USE FOR: partition key design (use cosmosdb-partition-key), query optimization (use cosmosdb-query-optimization), SDK client code (use cosmosdb-sdk).

Azure Cosmos DB partition key design best practices: high cardinality, hotspot avoidance, hierarchical partition keys, synthetic keys, query pattern alignment, immutability, and logical partition size limits. USE FOR: Cosmos DB partition key choice, high cardinality, avoid hot partitions, hierarchical partition keys, synthetic partition keys, query pattern alignment, partition key length, immutable partition key, 20GB logical partition limit. DO NOT USE FOR: data modeling (use cosmosdb-data-modeling), query optimization (use cosmosdb-query-optimization), throughput (use cosmosdb-throughput).

Azure Cosmos DB vector search best practices: enabling the feature, defining embedding policies, configuring vector indexes (flat, quantizedFlat, diskANN), normalizing embeddings, VectorDistance queries, and repository patterns for RAG. USE FOR: Cosmos DB vector search, vector embedding policy, vector index, flat index, quantizedFlat, diskANN, VectorDistance, cosine similarity, embedding normalization, RAG, retrieval augmented generation, semantic search, vector repository pattern, AI search. DO NOT USE FOR: full-text search (use cosmosdb-full-text-search), LangChain integration (use cosmosdb-sdk or cosmosdb-design-patterns).

Azure Cosmos DB design patterns: change feed materialized views, efficient ranking, service layer relationship hydration, LangGraph multi-agent orchestration, human-in-the-loop interrupts, checkpoint resumption, agent routing, FastAPI startup, chat history separation, background task writes, async Cosmos DB routing, and agent name attribution. USE FOR: Cosmos DB change feed, materialized views, CQRS, event sourcing, ranking patterns, service layer, relationship hydration, LangGraph, multi-agent, human-in-the-loop, interrupt, checkpoint, agent routing, FastAPI startup, chat history, background tasks, async routing, agent attribution, AI grounding. DO NOT USE FOR: SDK configuration (use cosmosdb-sdk), data modeling (use cosmosdb-data-modeling).

Azure Cosmos DB full-text search best practices: enabling the capability flag, defining fullTextPolicy, configuring fullTextIndexes, keyword matching with FullTextContains functions, BM25 relevance ranking, and hybrid queries. USE FOR: Cosmos DB full-text search, FTS, EnableNoSQLFullTextSearch, fullTextPolicy, fullTextIndexes, FullTextContains, FullTextContainsAll, FullTextContainsAny, FullTextScore, BM25 ranking, RANK, hybrid queries, keyword search, inverted index, language-aware tokenization. DO NOT USE FOR: vector search (use cosmosdb-vector-search), regular query optimization (use cosmosdb-query-optimization).

Azure Cosmos DB query optimization best practices: point reads, projections, pagination with continuation tokens, parameterized queries, filter ordering, cross-partition query avoidance, and analytical query detection. USE FOR: Cosmos DB queries, point reads vs queries, SELECT projections, continuation tokens, parameterized queries, avoid cross-partition, avoid scans, filter selectivity, TOP literal, ORDER BY, latest by timestamp, OLAP detection, aggregate queries, DISTINCT keyword. DO NOT USE FOR: indexing (use cosmosdb-indexing), data modeling (use cosmosdb-data-modeling), SDK client code (use cosmosdb-sdk).

Azure Cosmos DB global distribution best practices: multi-region writes, consistency levels, conflict resolution, automatic failover, read regions, and zone redundancy for high availability. USE FOR: Cosmos DB multi-region, consistency levels, strong consistency, bounded staleness, session consistency, eventual consistency, conflict resolution, automatic failover, read regions, zone redundancy, global replication, disaster recovery, geo-redundancy, multi-master. DO NOT USE FOR: SDK preferred regions (use cosmosdb-sdk), monitoring (use cosmosdb-monitoring).

Step-by-step guide for designing Azure Cosmos DB NoSQL data models. Captures application requirements, access patterns, volumetrics, and concurrency details into a cosmosdb_requirements.md file, then produces an optimized Cosmos DB NoSQL data model design using best practices and common patterns, saved to a cosmosdb_data_model.md file. Use when the user wants to design, model, or plan a Cosmos DB NoSQL database schema, partition strategy, or container layout, or when they need help with NoSQL data modeling for Azure Cosmos DB.