azure-cosmosdb

Provides reference and implementation guidance for Azure Cosmos DB APIs and global distribution.

Updated Apr 27, 2026
One-click install
npx skills add https://github.com/tomz/agent-skills --skill azure-cosmosdb-tomz
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: azure-cosmosdb
Source: https://github.com/tomz/agent-skills/tree/main/azure-cosmosdb
Command: npx skills add https://github.com/tomz/agent-skills --skill azure-cosmosdb-tomz

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Consolidates authoritative guidance for architecting, configuring, and operating Cosmos DB across the API surface to help teams design scalable, globally distributed data systems.

Core Features & Use Cases

  • API coverage: SQL, MongoDB, Cassandra, Gremlin, Table, and PostgreSQL compatibility with practical patterns.
  • Key capabilities: throughput provisioning, autoscale, serverless, partitioning strategies, indexing policies, conflict resolution, change feed, TTL, RBAC, and IaC provisioning with Terraform/Bicep.
  • Use Case: Design a globally distributed catalog or analytics store with low-latency reads across regions and strong consistency choices.

Quick Start

Configure a global Cosmos DB account with multi-region locations, appropriate consistency, and a container with a suitable partition key to begin using Cosmos DB patterns.

Frequently Asked Questions about azure-cosmosdb

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I choose a partition key for Cosmos DB to avoid hot spots?

Cosmos DB partitioning strategies distribute data and throughput across logical partitions. Selecting a high-cardinality partition key balances request units and prevents hot spots, ensuring scalable multi-region deployments without throttling.

What's the best way to provision throughput on Cosmos DB for variable workloads?

Cosmos DB throughput provisioning supports autoscale and serverless modes for variable workloads. Autoscale adjusts provisioned RU/s automatically based on usage patterns, while serverless billing charges per request, optimizing costs for sporadic traffic.

Does Cosmos DB support multi-API data models like MongoDB and Cassandra?

Cosmos DB provides native compatibility with SQL, MongoDB, Cassandra, Gremlin, Table, and PostgreSQL APIs. This multi-model support allows teams to migrate existing applications without changing drivers, using familiar query languages.

How do I configure global distribution in Cosmos DB for low-latency reads?

Cosmos DB global distribution configures multi-region write and read locations using Bicep or Terraform. Setting appropriate consistency levels and multi-region locations ensures low-latency reads globally while maintaining data synchronization.

When should I use Cosmos DB change feed in my architecture?

Cosmos DB change feed captures row-level modifications in order, triggering downstream processing. Use it for event-driven architectures, real-time analytics, or replicating data to secondary stores, maintaining an auditable modification log.

What are the limitations of Cosmos DB conflict resolution policies?

Cosmos DB conflict resolution policies handle multi-region write collisions using last-write-wins or custom logic. Limitations include managing idempotency in custom procedures and potential data loss when overwriting concurrent multi-region updates.