Azure Cosmos DB Best Practices

This document outlines recommended practices for building efficient, scalable, and cost-effective applications with Azure Cosmos DB.

Partitioning Strategies

Effective partitioning is crucial for scaling your Azure Cosmos DB workloads. Choosing the right partition key can significantly impact performance and cost.

Choosing a Good Partition Key

• High Cardinality: Select a property that has a large number of distinct values.
• Even Distribution: Ensure data is distributed evenly across partitions to avoid "hot" partitions.
• Query Patterns: A partition key that is frequently used in query filters will improve query performance.

Common Pitfalls

• Low Cardinality Keys: Can lead to a few very large partitions.
• Keys with Skewed Data: Results in uneven load distribution.

Indexing Best Practices

Azure Cosmos DB automatically indexes all data, but you can optimize this by configuring indexing policies.

Include/Exclude Paths

• Exclude paths that are not queried frequently to reduce index storage and throughput consumption.
• Include paths that are frequently used in filters and sorts.

Index Kinds

• Use the appropriate index kind (e.g., range, spatial, composite) based on your query patterns.

Request Unit (RU) Optimization

Understanding and optimizing Request Units (RUs) is key to managing costs and performance.

Efficient Queries

• Filter data as early as possible in your queries.
• Avoid `SELECT *` and only retrieve the fields you need.
• Use stored procedures or UDFs for complex server-side logic to reduce round trips.

Batching Operations

• Use bulk operations or batching for large inserts, updates, or deletes.

Consistency Levels

Azure Cosmos DB offers multiple consistency levels, each with different trade-offs between latency, throughput, and availability.

• Strong: Highest consistency, but highest latency.
• Bounded Staleness: Guarantees that reads are no more than a specified version or time behind the writes.
• Session: Default and usually a good balance. Guarantees consistency within a client session.
• Consistent Prefix: Guarantees that reads will return a prefix of all writes.
• Eventual: Lowest consistency, lowest latency. Reads might lag behind writes.

Choose the consistency level that best matches your application's requirements. For many applications, Session or Bounded Staleness are excellent choices.

Connection Management

Efficiently managing connections to Azure Cosmos DB can significantly improve application performance.

• Use SDKs: Leverage the official Azure Cosmos DB SDKs, which handle connection pooling and retries automatically.
• Single Client Instance: Instantiate a single DocumentClient (or equivalent for newer SDKs) per application instance. Avoid creating new clients for each request.
• TCP Mode: Prefer the TCP transport mode offered by the SDKs for lower latency and higher throughput compared to the HTTP mode.

Monitoring and Alerting

Proactive monitoring helps identify and resolve issues before they impact users.

• Azure Monitor: Use Azure Monitor to track key metrics like Request Units, latency, storage, and availability.
• Alerts: Set up alerts for critical metrics (e.g., high RU consumption, increased latency, throttling) to be notified of potential problems.

Geo-Replication

For high availability and disaster recovery, configure geo-replication for your Azure Cosmos DB account.

• Multi-Region Writes: Enable multi-region writes for applications requiring low-latency writes in multiple regions.
• Failover: Understand and test your failover strategy.