cosmosdb-best-practices

name	cosmosdb-best-practices
description	╔═══════════════════════════════════════════════════════════════════════════════╗ ║ ║ ║ █████╗ ███████╗██╗ ██╗██████╗ ███████╗ ║ ║ ██╔══██╗╚══███╔╝██║ ██║██╔══██╗██╔════╝ ║ ║ ███████║ ███╔╝ ██║ ██║██████╔╝█████╗ ║ ║ ██╔══██║ ███╔╝ ██║ ██║██╔══██╗██╔══╝ ║ ║ ██║ ██║███████╗╚██████╔╝██║ ██║███████╗ ║ ║ ╚═╝ ╚═╝╚══════╝ ╚═════╝ ╚═╝ ╚═╝╚══════╝ ║ ║ ║ ║ ██████╗ ██████╗ ███████╗███╗ ███╗ ██████╗ ███████╗ ██████╗ ██████╗ ║ ║ ██╔════╝██╔═══██╗██╔════╝████╗ ████║██╔═══██╗██╔════╝ ██╔══██╗██╔══██╗ ║ ║ ██║ ██║ ██║███████╗██╔████╔██║██║ ██║███████╗ ██║ ██║██████╔╝ ║ ║ ██║ ██║ ██║╚════██║██║╚██╔╝██║██║ ██║╚════██║ ██║ ██║██╔══██╗ ║ ║ ╚██████╗╚██████╔╝███████║██║ ╚═╝ ██║╚██████╔╝███████║ ██████╔╝██████╔╝ ║ ║ ╚═════╝ ╚═════╝ ╚══════╝╚═╝ ╚═╝ ╚═════╝ ╚══════╝ ╚═════╝ ╚═════╝ ║ ║ ║ ║ ╔═══════════════════════════╗ ║ ║ ║ 🚀 AGENT KIT 🚀 ║ ║ ║ ╚═══════════════════════════╝ ║ ║ ║ ╚═══════════════════════════════════════════════════════════════════════════════╝ Azure Cosmos DB performance optimization and best practices guidelines for NoSQL, partitioning, queries, and SDK usage. Use when writing, reviewing, or refactoring code that interacts with Azure Cosmos DB, designing data models, optimizing queries, or implementing high-performance database operations.
license	MIT
metadata	{"author":"cosmosdb-agent-kit","version":"1.0.0"}

Azure Cosmos DB Best Practices

Comprehensive performance optimization guide for Azure Cosmos DB applications, containing 45+ rules across 8 categories, prioritized by impact to guide automated refactoring and code generation.

When to Apply

Reference these guidelines when:

• Designing data models for Cosmos DB
• Choosing partition keys
• Writing or optimizing queries
• Implementing SDK patterns
• Reviewing code for performance issues
• Configuring throughput and scaling
• Building globally distributed applications

Rule Categories by Priority

Priority	Category	Impact	Prefix
1	Data Modeling	CRITICAL	model-
2	Partition Key Design	CRITICAL	partition-
3	Query Optimization	HIGH	query-
4	SDK Best Practices	HIGH	sdk-
5	Indexing Strategies	MEDIUM-HIGH	index-
6	Throughput & Scaling	MEDIUM	throughput-
7	Global Distribution	MEDIUM	global-
8	Monitoring & Diagnostics	LOW-MEDIUM	monitoring-

Quick Reference

1. Data Modeling (CRITICAL)

• model-embed-related - Embed related data retrieved together
• model-reference-large - Reference data when items get too large
• model-avoid-2mb-limit - Keep items well under 2MB limit
• model-denormalize-reads - Denormalize for read-heavy workloads
• model-schema-versioning - Version your document schemas
• model-type-discriminator - Use type discriminators for polymorphic data

2. Partition Key Design (CRITICAL)