Azure Functions: Cosmos DB Triggers

Leveraging NoSQL data with serverless compute

Introduction to Cosmos DB Triggers in Azure Functions

Azure Functions provides powerful integration with Azure Cosmos DB, enabling you to trigger function execution based on changes in your Cosmos DB data. This is invaluable for real-time processing, data synchronization, event-driven architectures, and more.

There are two primary types of Cosmos DB triggers:

Cosmos DB Trigger Binding

The Cosmos DB trigger binding allows your Azure Function to react to new or updated documents in a Cosmos DB container. It uses the Cosmos DB change feed to monitor for these changes.

Key Concepts:

Configuration:

To configure a Cosmos DB trigger, you typically define it in your function.json file (for Node.js, Python, etc.) or use attributes/decorators (for .NET).

Example: function.json for a Node.js Function

{
  "bindings": [
    {
      "name": "documents",
      "type": "cosmosDBTrigger",
      "direction": "in",
      "databaseName": "MyDatabase",
      "collectionName": "MyCollection",
      "connectionStringSetting": "CosmosDBConnection",
      "createLeaseCollectionIfNotExists": true,
      "leasesCollectionName": "leases"
    }
  ]
}

Example: C# Attribute

using Microsoft.Azure.WebJobs;

public static class CosmosTriggerFunction
{
    [FunctionName("CosmosDbProcessor")]
    public static void Run(
        [CosmosDBTrigger(
            databaseName: "MyDatabase",
            collectionName: "MyCollection",
            ConnectionStringSetting = "CosmosDBConnection",
            CreateLeaseCollectionIfNotExists = true,
            LeaseCollectionName = "leases")]IReadOnlyList<MyDocumentType> documents,
        ILogger log)
    {
        log.LogInformation($"Processing {documents.Count} documents...");
        foreach (var document in documents)
        {
            log.LogInformation($"Processed document Id: {document.Id}");
            // Your processing logic here
        }
    }
}

public class MyDocumentType
{
    public string Id { get; set; }
    // Other properties
}

Important Settings:

Handling Multiple Documents

The trigger typically passes a collection of changed documents to your function, allowing for efficient batch processing. This reduces the overhead of invoking your function for every single change.

You can control the batch size and concurrency settings to optimize performance.

Best Practices and Considerations

Lease Container Management:

Ensure the lease container is correctly configured and has sufficient throughput. It's crucial for the trigger's reliability.

Idempotency:

Design your functions to be idempotent. Since the trigger might deliver the same document changes more than once under certain failure conditions, your logic should handle duplicates gracefully.

Error Handling:

Implement robust error handling within your function. Unhandled exceptions can cause the trigger to stop processing or behave unexpectedly.

Monitoring:

Utilize Azure Monitor and Application Insights to track your function's execution, performance, and any errors related to the Cosmos DB trigger.

Throughput:

Ensure both your primary data container and your lease container have adequate Request Units (RUs) to handle the expected load and change feed processing.

Further Reading