How to handle azure cosmos db bulk insert speed limit error message

When performing bulk inserts in Azure Cosmos DB, there are certain limitations and considerations to keep in mind. One potential error message you might encounter related to bulk insert speed limits is:

"Request rate is large. More Request Units may be needed, so no further request is being sent. Please retry after some time, or adjust the RUs per second on your collection or database to allow for higher request rates."

This error message indicates that the request rate for your bulk inserts is exceeding the provisioned Request Units (RUs) per second for your Cosmos DB collection or database. Azure Cosmos DB uses Request Units as a measure of throughput, representing the cost of a request in terms of CPU, memory, and I/O resources.

1. Increase the provisioned RUs per second for your collection or database: By scaling up the RUs, you allocate more throughput capacity to handle higher request rates. You can adjust the RUs through the Azure portal, Azure CLI, or Azure PowerShell.

2. Split the bulk insert operation into multiple smaller batches: Instead of inserting all the data in a single bulk operation, divide it into smaller batches and perform the inserts over time. This approach helps distribute the request rate more evenly, preventing the error.

3. Implement client-side throttling: If you are using a custom application to perform the bulk inserts, you can introduce client-side throttling logic to control the request rate and avoid exceeding the provisioned RUs.

By following these steps, you should be able to mitigate the error related to bulk insert speed limits in Azure Cosmos DB.

Building a Serverless Web App with Azure Functions and Azure Cosmos DB

 Server less computing has revolutionized the way we build and deploy web applications. With server less, you can focus on writing code without worrying about managing infrastructure, and pay only for the compute resources you use. In this tutorial, we'll show you how to build a server less web app with Azure Functions and Azure Cosmos DB that provides scalable and cost-effective data storage and processing.

Prerequisites

Before we get started, you'll need to have the following:

1. An Azure account
2. Visual Studio Code
3. Azure Functions extension for Visual Studio Code
4. Azure Cosmos DB extension for Visual Studio Code

Creating the Azure Functions App

The first step is to create an Azure Functions app. In Visual Studio Code, select the Azure Functions extension and choose "Create New Project". Follow the prompts to choose your programming language and runtime.

Once your project is created, you can create a new function by selecting the "Create Function" button in the Azure Functions Explorer. Choose the HTTP trigger template to create a function that responds to HTTP requests.

In this example, we'll create a function that retrieves data from Azure Cosmos DB. We'll use the Cosmos DB extension for Visual Studio Code to connect to our database and retrieve data.

Creating the Azure Cosmos DB Account

Next, we'll create an Azure Cosmos DB account to store our data. In the Azure portal, select "Create a resource" and search for "Cosmos DB". Choose "Azure Cosmos DB" and follow the prompts to create a new account.

Once your account is created, select "Add Collection" to create a new container for your data. Choose a partition key and throughput level, and select "Create". You can now add data to your container through the Azure portal or through your Azure Functions app.

Connecting the Azure Functions App to Azure Cosmos DB

To connect your Azure Functions app to Azure Cosmos DB, you'll need to add the Cosmos DB extension to your project. In Visual Studio Code, select the Extensions icon and search for "Azure Cosmos DB". Install the extension and reload Visual Studio Code.

Next, open your function code and add the following code to your function:

const { CosmosClient } = require("@azure/cosmos");

module.exports = async function (context, req) {
    const endpoint = process.env["CosmosDBEndpoint"];
    const key = process.env["CosmosDBKey"];
    const client = new CosmosClient({ endpoint, key });
    
    const database = client.database("mydatabase");
    const container = database.container("mycontainer");
    
    const querySpec = {
        query: "SELECT * FROM c"
    };
    
    const { resources } = await container.items.query(querySpec).fetchAll();
    
    context.res = {
        body: resources
    };
}

This code connects to your Azure Cosmos DB account and retrieves all data from the specified container. Replace "mydatabase" and "mycontainer" with your database and container names.

Finally, add your Azure Cosmos DB account endpoint and key to your function's Application Settings. In the Azure Functions Explorer, select your function and choose "Application Settings". Add the following settings:

CosmosDBEndpoint: Your Azure Cosmos DB account endpoint
CosmosDBKey: Your Azure Cosmos DB account key

Conclusion

we learned how to build a serverless web app with Azure Functions and Azure Cosmos DB. We created an Azure Functions app and a new function that retrieves data from Azure Cosmos DB using the Cosmos DB extension for Visual Studio Code.

We also created an Azure Cosmos DB account and added a new container to store our data. Finally, we connected our Azure Functions app to Azure Cosmos DB by adding the necessary code and application settings. By using Azure Functions and Azure Cosmos DB together, you can build scalable and cost-effective web applications that handle data storage and processing without managing infrastructure.

You can extend this example to include more complex queries, data manipulation, and other functions that respond to HTTP requests or other triggers. 

 If you're new to serverless computing or Azure Functions, be sure to check out the documentation and resources available from Microsoft. With the right tools and knowledge, you can quickly build and deploy serverless web applications that are flexible, scalable, and cost-effective.