Handle transient errors and 429s

Azure Cosmos DB is a globally distributed, multi-model database service provided by Microsoft Azure. It offers high availability, horizontal scalability, and low latency access to your data. When building native applications using Azure Cosmos DB, it’s important to handle transient errors and 429s effectively to ensure a smooth user experience.

Transient errors are intermittent errors that occur due to temporary issues in the system, such as network glitches, high server load, or resource unavailability. These errors are typically short-lived and can be retried without any manual intervention. On the other hand, HTTP status code 429 indicates that the client has sent too many requests within a given time frame.

Implement Retry Logic

To handle transient errors and 429s, you can implement retry logic in your application. Azure Cosmos DB SDKs provide built-in retry policies that automatically handle transient errors. The SDKs use an exponential backoff algorithm to retry failed requests with increasing delays between retries. This helps to mitigate the impact of transient errors and enables automatic recovery.

Here’s an example of retry logic using the .NET SDK:

using Microsoft.Azure.Cosmos;

// Use the client to interact with Azure Cosmos DB
// ...

Implement Circuit Breaking

Circuit breaking is a pattern that allows you to prevent repeated failed requests by temporarily blocking access to the affected service. When a transient error or 429 occurs, you can dynamically adjust the circuit breaker state to open and prevent additional requests for a specific duration. This helps to reduce the load on the service and improves overall system stability.

Implement Exponential Backoff

Exponential backoff is a technique that allows you to pause between retry attempts in an increasing manner. Instead of retrying immediately, you can introduce a delay before each retry, with each subsequent retry having a longer delay than the previous one. This approach prevents overwhelming the service with repeated requests and gives it time to recover from transient errors.

Here’s an example of exponential backoff using JavaScript:

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

Monitor Request Units (RUs)

Azure Cosmos DB uses Request Units (RUs) to measure the throughput and resource consumption of database operations. When handling transient errors and 429s, it’s important to monitor and manage the RUs consumed by your application. You can use Azure Monitor to track the RU consumption and set alerts for any unexpected spikes or anomalies. By monitoring RUs, you can optimize your application’s performance, detect potential issues, and adjust the throughput provisioned for your database as needed.

In conclusion, handling transient errors and 429s is crucial when designing and implementing native applications using Azure Cosmos DB. By utilizing built-in retry logic, implementing circuit breaking, applying exponential backoff, and monitoring request units, you can ensure a robust and resilient application that provides a seamless user experience even during temporary disruptions.