azure-cosmosdb
Architectural best practices for Azure Cosmos DB scaling and configuration.
Install
mkdir -p .claude/skills/azure-cosmosdb && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/6107" && unzip -o skill.zip -d .claude/skills/azure-cosmosdb && rm skill.zipInstalls to .claude/skills/azure-cosmosdb
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Azure Cosmos DB partition keys, consistency levels, change feed, SDK patternsKey capabilities
- →Determines optimal partition keys for scalability
- →Configures consistency levels for read/write trade-offs
- →Designs efficient containers for NoSQL access patterns
- →Implements logic for Change Feed change tracking
- →Optimizes throughput via RU request unit management
How it works
It applies NoSQL design heuristics to evaluate partitioning strategies based on cardinality, distribution, and query performance requirements.
Inputs & outputs
When to use azure-cosmosdb
- →Designing partition keys for scaling
- →Choosing consistency levels for apps
- →Implementing Cosmos DB change feed
About this skill
Core Principle
Choose partition key wisely, design for your access patterns, understand consistency tradeoffs.
Cosmos DB distributes data across partitions. Your partition key choice determines scalability, performance, and cost. Design for even distribution and query efficiency.
Cosmos DB APIs
| API | Use Case |
|---|---|
| NoSQL (Core) | Document database, most flexible |
| MongoDB | MongoDB wire protocol compatible |
| PostgreSQL | Distributed PostgreSQL (Citus) |
| Apache Cassandra | Wide-column store |
| Apache Gremlin | Graph database |
| Table | Key-value (Azure Table Storage compatible) |
This skill focuses on NoSQL (Core) API - the most common choice.
Key Concepts
| Concept | Description |
|---|---|
| Container | Collection of items (like a table) |
| Item | Single document/record (JSON) |
| Partition Key | Determines data distribution |
| Logical Partition | Items with same partition key |
| Physical Partition | Storage unit (max 50GB, 10K RU/s) |
| RU (Request Unit) | Throughput currency |
Partition Key Design
Good Partition Keys
// High cardinality, even distribution, used in queries
// E-commerce: userId for user data
{ "id": "order-123", "userId": "user-456", ... } // PK: /userId
// Multi-tenant: tenantId
{ "id": "doc-1", "tenantId": "tenant-abc", ... } // PK: /tenantId
// IoT: deviceId for telemetry
{ "id": "reading-1", "deviceId": "device-789", ... } // PK: /deviceId
// Logs: synthetic key (date + category)
{ "id": "log-1", "partitionKey": "2024-01-15_errors", ... } // PK: /partitionKey
Hierarchical Partition Keys
// For multi-level distribution (e.g., tenant → user)
// Container created with: /tenantId, /userId
{
"id": "order-123",
"tenantId": "acme-corp",
"userId": "user-456",
"items": [...]
}
// Query within tenant and user efficiently
Bad Partition Keys
// Avoid:
// - Low cardinality (status, type, boolean)
// - Monotonically increasing (timestamp, auto-increment)
// - Frequently updated fields
// - Fields not used in queries
// Bad: Only 3 values → hot partitions
{ "status": "pending" | "completed" | "cancelled" }
// Bad: All writes go to latest partition
{ "timestamp": "2024-01-15T10:30:00Z" }
SDK Setup (TypeScript)
Install
npm install @azure/cosmos
Initialize Client
// lib/cosmosdb.ts
import { CosmosClient, Database, Container } from '@azure/cosmos';
const endpoint = process.env.COSMOS_ENDPOINT!;
const key = process.env.COSMOS_KEY!;
const databaseId = process.env.COSMOS_DATABASE!;
const client = new CosmosClient({ endpoint, key });
// Or with connection string
// const client = new CosmosClient(process.env.COSMOS_CONNECTION_STRING!);
export const database: Database = client.database(databaseId);
export function getContainer(containerId: string): Container {
return database.container(containerId);
}
Type Definitions
// types/cosmos.ts
export interface BaseItem {
id: string;
_ts?: number; // Auto-generated timestamp
_etag?: string; // For optimistic concurrency
}
export interface User extends BaseItem {
userId: string; // Partition key
email: string;
name: string;
createdAt: string;
updatedAt: string;
}
export interface Order extends BaseItem {
userId: string; // Partition key
orderId: string;
items: OrderItem[];
total: number;
status: 'pending' | 'paid' | 'shipped' | 'delivered';
createdAt: string;
}
export interface OrderItem {
productId: string;
name: string;
quantity: number;
price: number;
}
CRUD Operations
Create Item
import { getContainer } from './cosmosdb';
import { User } from './types';
const usersContainer = getContainer('users');
async function createUser(data: Omit<User, 'id' | 'createdAt' | 'updatedAt'>): Promise<User> {
const now = new Date().toISOString();
const user: User = {
id: crypto.randomUUID(),
...data,
createdAt: now,
updatedAt: now
};
const { resource } = await usersContainer.items.create(user);
return resource as User;
}
Read Item (Point Read)
// Most efficient read - requires id AND partition key
async function getUser(userId: string, id: string): Promise<User | null> {
try {
const { resource } = await usersContainer.item(id, userId).read<User>();
return resource || null;
} catch (error: any) {
if (error.code === 404) return null;
throw error;
}
}
// If id equals partition key value
async function getUserById(userId: string): Promise<User | null> {
try {
const { resource } = await usersContainer.item(userId, userId).read<User>();
return resource || null;
} catch (error: any) {
if (error.code === 404) return null;
throw error;
}
}
Query Items
// Query within partition (efficient)
async function getUserOrders(userId: string): Promise<Order[]> {
const ordersContainer = getContainer('orders');
const { resources } = await ordersContainer.items
.query<Order>({
query: 'SELECT * FROM c WHERE c.userId = @userId ORDER BY c.createdAt DESC',
parameters: [{ name: '@userId', value: userId }]
})
.fetchAll();
return resources;
}
// Cross-partition query (use sparingly)
async function getOrdersByStatus(status: string): Promise<Order[]> {
const ordersContainer = getContainer('orders');
const { resources } = await ordersContainer.items
.query<Order>({
query: 'SELECT * FROM c WHERE c.status = @status',
parameters: [{ name: '@status', value: status }]
})
.fetchAll();
return resources;
}
// Paginated query
async function getOrdersPaginated(
userId: string,
pageSize: number = 10,
continuationToken?: string
): Promise<{ items: Order[]; continuationToken?: string }> {
const ordersContainer = getContainer('orders');
const queryIterator = ordersContainer.items.query<Order>(
{
query: 'SELECT * FROM c WHERE c.userId = @userId ORDER BY c.createdAt DESC',
parameters: [{ name: '@userId', value: userId }]
},
{
maxItemCount: pageSize,
continuationToken
}
);
const { resources, continuationToken: nextToken } = await queryIterator.fetchNext();
return {
items: resources,
continuationToken: nextToken
};
}
Update Item
// Replace entire item
async function updateUser(userId: string, id: string, updates: Partial<User>): Promise<User> {
const existing = await getUser(userId, id);
if (!existing) throw new Error('User not found');
const updated: User = {
...existing,
...updates,
updatedAt: new Date().toISOString()
};
const { resource } = await usersContainer.item(id, userId).replace(updated);
return resource as User;
}
// Partial update (patch operations)
async function patchUser(userId: string, id: string, operations: any[]): Promise<User> {
const { resource } = await usersContainer.item(id, userId).patch(operations);
return resource as User;
}
// Usage:
await patchUser('user-123', 'user-123', [
{ op: 'set', path: '/name', value: 'New Name' },
{ op: 'set', path: '/updatedAt', value: new Date().toISOString() },
{ op: 'incr', path: '/loginCount', value: 1 }
]);
Delete Item
async function deleteUser(userId: string, id: string): Promise<void> {
await usersContainer.item(id, userId).delete();
}
Optimistic Concurrency (ETags)
async function updateUserWithETag(
userId: string,
id: string,
updates: Partial<User>,
etag: string
): Promise<User> {
const existing = await getUser(userId, id);
if (!existing) throw new Error('User not found');
const updated: User = {
...existing,
...updates,
updatedAt: new Date().toISOString()
};
try {
const { resource } = await usersContainer.item(id, userId).replace(updated, {
accessCondition: { type: 'IfMatch', condition: etag }
});
return resource as User;
} catch (error: any) {
if (error.code === 412) {
throw new Error('Document was modified by another process');
}
throw error;
}
}
Consistency Levels
| Level | Guarantees | Latency | Use Case |
|---|---|---|---|
| Strong | Linearizable reads | Highest | Financial, inventory |
| Bounded Staleness | Consistent within bounds | High | Leaderboards, counters |
| Session | Read your writes | Medium | User sessions (default) |
| Consistent Prefix | Ordered reads | Low | Social feeds |
| Eventual | No ordering guarantee | Lowest | Analytics, logs |
Set Consistency Per Request
// Override default consistency
const { resource } = await usersContainer.item(id, userId).read<User>({
consistencyLevel: 'Strong'
});
// For queries
const { resources } = await container.items.query(
{ query: 'SELECT * FROM c' },
{ consistencyLevel: 'BoundedStaleness' }
).fetchAll();
Batch Operations
Transactional Batch (Same Partition)
async function createOrderWithItems(userId: string, order: Order, items: any[]): Promise<void> {
const ordersContainer = getContainer('orders');
const operations = [
{ operationType: 'Create' as const, resourceBody: order },
...items.map(item => ({
operationType: 'Create' as const,
resourceBody: { ...item, userId, orderId: order.orderId }
}))
];
const { result } = await ordersContainer.items.batch(operations, userId);
// Check if any operation failed
if (result.some(r => r.statusCode >= 400)) {
throw new Error('Batch operation failed');
}
}
Bulk Operations
// For large-scale imports (not transactional)
async function bulkImportUsers(users: User[]): Promise<void> {
const operations = users.map(user => ({
operationType: 'Create' as const,
resourceBody: user,
---
*Content truncated.*
When not to use it
- →For relational data requiring strict ACID transactions
- →When storage needs are minimal and simple JSON storage suffices
Limitations
- →Incorrect partition key choice is difficult to reverse
- →Throughput settings directly impact monthly costs
How it compares
It focuses on the physical-to-logical partitioning mechanics unique to the Cosmos DB architecture.
Compared to similar skills
azure-cosmosdb side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| azure-cosmosdb (this skill) | 1 | 4mo | Review | Intermediate |
| postgresql-table-design | 30 | 4mo | No flags | Intermediate |
| agentdb-advanced-features | 7 | 9mo | Review | Advanced |
| event-store-design | 5 | 2mo | No flags | Advanced |
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