Azure Cosmos DB Performance Tuning Tutorials

Welcome to our curated collection of tutorials focused on optimizing the performance of your Azure Cosmos DB solutions. This guide provides practical strategies, best practices, and in-depth explanations to help you achieve maximum efficiency and responsiveness.

Introduction to Azure Cosmos DB Performance

Understanding the core concepts of Azure Cosmos DB performance is crucial. This section covers:

  • Request Units (RUs) and throughput provisioning
  • Partitioning strategies and their impact
  • Latency and consistency models

Advanced Indexing Strategies

Efficient indexing can dramatically improve query performance. Learn how to:

  • Leverage composite indexes and included properties
  • Understand index transformations and their trade-offs
  • Implement custom indexing policies for specific workloads

For detailed examples, refer to the Azure Cosmos DB Indexing Deep Dive.

Optimizing Queries

Slow queries can be a bottleneck. This tutorial focuses on:

  • Writing efficient SQL, MongoDB, Cassandra, Gremlin, and Table API queries
  • Minimizing cross-partition queries
  • Effective use of projection and filtering

Example of an optimized query:

SELECT TOP 10 c.name, c.email
FROM c
WHERE c.city = "Seattle" AND c.is_active = true
ORDER BY c.registered_date DESC

Throughput Management and Cost Optimization

Balancing performance with cost is essential. This module explores:

  • Autoscale vs. manual throughput provisioning
  • Monitoring RU consumption and identifying bottlenecks
  • Strategies for reducing RU costs without sacrificing performance
  • Understanding reserved throughput

Best Practices for Application Development

Your application code plays a vital role in Cosmos DB performance. We'll cover:

  • Choosing the right SDK and version
  • Implementing effective retry policies
  • Connection pooling and singleton clients
  • Asynchronous operations for maximum throughput

Monitoring and Diagnostics

Proactive monitoring is key to identifying and resolving performance issues. Learn to use:

  • Azure Monitor and Azure Cosmos DB metrics
  • Diagnostic logging and tracing
  • Tools like Azure Cosmos DB Data Explorer for performance analysis

See our guide on Monitoring Azure Cosmos DB for more information.

Case Studies and Real-World Scenarios

Examine how other developers have tackled common performance challenges in Azure Cosmos DB through practical case studies.