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Fix Azure Cosmos DB Throttling (429 Too Many Requests)

Resolve Cosmos DB 429 throttling errors by increasing RU/s, optimizing queries, and implementing retry logic.

Published: Apr 2, 20266 min readBy FixWikiHub Editorial Team

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Introduction

Azure Cosmos DB uses Request Units (RU/s) to manage throughput. When your workload exceeds provisioned RU/s, Cosmos DB returns 429 (Too Many Requests) errors, rejecting operations until capacity becomes available.

Symptoms

429 Throttling error:

json

{
  "code": 429,
  "message": "The request rate is too large. Please retry after 1000 milliseconds.",
  "activityId": "abc123-def456"
}

SDK retry exhaustion:

csharp

// In application logs:
Microsoft.Azure.Documents.DocumentClientException: Message: {"Errors":["Request rate is large"]}
ResourceType: DocumentCollection, Method: GET

Monitoring showing throttling:

```bash $ az monitor metrics list \ --resource /subscriptions/SUB/resourceGroups/my-rg/providers/Microsoft.DocumentDB/databaseAccounts/my-cosmos \ --metric "TotalRequestUnits" "ThrottledRequests"

# High throttled request count ```

Common Causes

1.Provisioned RU/s too low - Workload exceeds capacity
2.Hot partition - All traffic to single partition
3.Inefficient queries - Queries consuming too many RUs
4.Burst traffic - Sudden spike exceeding throughput
5.Autoscale not configured - Manual provisioning can't scale fast
6.Large documents - Big documents consume more RUs
7.Missing retry logic - Application doesn't handle 429

Step-by-Step Fix

1.Check logs for specific error messages
2.Verify configuration settings
3.Test network connectivity
4.Review recent changes
5.Apply corrective action
6.Verify the fix

Step 1: Check Current RU/s Provisioning

bash

# Get throughput settings
az cosmosdb sql container show \
  --account-name my-cosmos \
  --resource-group my-rg \
  --database-name my-db \
  --name my-container \
  --query '{Throughput:resource.throughput,AutoscaleSettings:resource.autoscaleSettings}'

Step 2: Monitor RU Consumption

```bash # Check RU consumption metrics az monitor metrics list \ --resource /subscriptions/SUB/resourceGroups/my-rg/providers/Microsoft.DocumentDB/databaseAccounts/my-cosmos \ --metric "TotalRequestUnits" \ --interval PT1H \ --query 'value[0].timeseries[0].data'

# Get per-container RU consumption az monitor metrics list \ --resource /subscriptions/SUB/resourceGroups/my-rg/providers/Microsoft.DocumentDB/databaseAccounts/my-cosmos \ --metric "TotalRequestUnits" \ --aggregation total \ --interval PT1H ```

Step 3: Increase Provisioned RU/s

```bash # Increase manual throughput az cosmosdb sql container throughput update \ --account-name my-cosmos \ --resource-group my-rg \ --database-name my-db \ --name my-container \ --throughput 2000

# Switch to autoscale az cosmosdb sql container throughput update \ --account-name my-cosmos \ --resource-group my-rg \ --database-name my-db \ --name my-container \ --max-throughput 4000

# Autoscale automatically scales from 400-4000 RU/s ```

Step 4: Analyze Query RU Cost

```sql -- Run query with RU cost SELECT c.id, c.name FROM c

-- Check request charge in response headers -- x-ms-request-charge: 5.0 RUs

-- Optimize expensive queries: -- Add indexes on filter properties -- Use partition key in WHERE clause -- Limit returned properties ```

Step 5: Add Indexing Policy

json

{
  "indexingPolicy": {
    "automatic": true,
    "indexingMode": "consistent",
    "includedPaths": [
      {
        "path": "/name/?"
      },
      {
        "path": "/status/?"
      }
    ],
    "excludedPaths": [
      {
        "path": "/largeJsonField/*"
      }
    ]
  }
}

Apply via CLI:

bash

az cosmosdb sql container update \
  --account-name my-cosmos \
  --resource-group my-rg \
  --database-name my-db \
  --name my-container \
  --idx @indexing-policy.json

Step 6: Implement Retry Logic

```csharp // C# SDK with retry logic var cosmosClientOptions = new CosmosClientOptions { MaxRetryAttemptsOnRateLimitedRequests = 9, MaxRetryWaitTimeOnRateLimitedRequests = TimeSpan.FromSeconds(30) };

var client = new CosmosClient(connectionString, cosmosClientOptions);

// SDK automatically retries on 429 with exponential backoff ```

```python # Python SDK with retry logic from azure.cosmos import CosmosClient from azure.cosmos.exceptions import CosmosHttpResponseError

client = CosmosClient(url, credential=key) database = client.get_database_client('my-db') container = database.get_container_client('my-container')

max_retries = 5 retry_delay = 1

for attempt in range(max_retries): try: result = container.read_item(item_id, partition_key) break except CosmosHttpResponseError as e: if e.status_code == 429: time.sleep(e.retry_after_ms / 1000) else: raise ```

Step 7: Check for Hot Partitions

```bash # Check partition key distribution az cosmosdb sql container show \ --account-name my-cosmos \ --resource-group my-rg \ --database-name my-db \ --name my-container \ --query 'resource.partitionKey'

# If all requests go to one partition, redesign partition key # Good partition key: High cardinality, even distribution # Bad partition key: Low cardinality (e.g., status field) ```

Step 8: Use Bulk Execution

```csharp // For high-throughput writes, use bulk mode var bulkOptions = new CosmosClientOptions { AllowBulkExecution = true };

var client = new CosmosClient(connectionString, bulkOptions);

// Concurrent tasks var tasks = items.Select(item => container.CreateItemAsync(item, new PartitionKey(item.Id)));

await Task.WhenAll(tasks); ```

Step 9: Optimize Document Size

```bash # Larger documents consume more RUs # Rule of thumb: 1 KB ≈ 1 RU for read, 5-10 RUs for write

# Reduce document size: # - Remove unused fields # - Store large blobs in Blob Storage, keep reference in Cosmos # - Use short property names

# Check document size az cosmosdb sql container show \ --account-name my-cosmos \ --resource-group my-rg \ --database-name my-db \ --name my-container \ --query 'resource.documentSizeDistribution' ```

Step 10: Monitor Throttling Metrics

```bash # Set up alert for throttling az monitor metrics alert create \ --name cosmos-throttling-alert \ --resource-group my-rg \ --scopes /subscriptions/SUB/resourceGroups/my-rg/providers/Microsoft.DocumentDB/databaseAccounts/my-cosmos \ --condition "avg TotalRequestUnits > 80" \ --window-size 5m \ --evaluation-frequency 1m

# Check current throttling rate az monitor metrics list \ --resource /subscriptions/SUB/resourceGroups/my-rg/providers/Microsoft.DocumentDB/databaseAccounts/my-cosmos \ --metric "ThrottledRequests" ```

Cosmos DB RU Estimates

Operation	Approximate RU Cost
Read 1 KB item	1 RU
Write 1 KB item	5 RUs
Query (indexed)	1-10 RUs
Query (scan)	10-100+ RUs
Stored procedure	Variable

Verification

```bash # After increasing RU/s, monitor throttling az monitor metrics list \ --resource /subscriptions/SUB/resourceGroups/my-rg/providers/Microsoft.DocumentDB/databaseAccounts/my-cosmos \ --metric "ThrottledRequests" \ --interval PT1H

# Should show zero or minimal throttled requests

# Test application load # Should handle requests without 429 errors ```

[Fix Azure Cosmos DB Partition Hotspot](/articles/fix-azure-cosmos-db-partition-hotspot)
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Last updated: Apr 2, 2026

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Fix Azure Cosmos DB Throttling (429 Too Many Requests)

Introduction

Symptoms

Common Causes

Step-by-Step Fix

Step 1: Check Current RU/s Provisioning

Step 2: Monitor RU Consumption

Step 3: Increase Provisioned RU/s

Step 4: Analyze Query RU Cost

Step 5: Add Indexing Policy

Step 6: Implement Retry Logic

Step 7: Check for Hot Partitions

Step 8: Use Bulk Execution

Step 9: Optimize Document Size

Step 10: Monitor Throttling Metrics

Cosmos DB RU Estimates

Verification

People also search for

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Fix Azure Cosmos DB Throttling (429 Too Many Requests)

Introduction

Symptoms

Common Causes

Step-by-Step Fix

Step 1: Check Current RU/s Provisioning

Step 2: Monitor RU Consumption

Step 3: Increase Provisioned RU/s

Step 4: Analyze Query RU Cost

Step 5: Add Indexing Policy

Step 6: Implement Retry Logic

Step 7: Check for Hot Partitions

Step 8: Use Bulk Execution

Step 9: Optimize Document Size

Step 10: Monitor Throttling Metrics

Cosmos DB RU Estimates

Verification

Related Issues

Related Articles

People also search for

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