A transient fault is an intermittent, temporary failure that if retried may be resolved. In distributed systems like Azure Cosmos DB, transient faults can happen due to network latency, system resources overuse, etc.
To handle these scenarios, Azure Cosmos DB provides built-in retry policies. These are pre-configured sets of standards that dictate how a system will handle different types of transient faults. Most SDKs for Azure Cosmos DB have a default retry policy that includes an exponential backoff retry model. This means that the system will attempt to retry the operation after a delay. If the attempt fails, then the delay is increased exponentially and another retry is attempted.
Here is a simple example of a built-in retry policy using the Java SDK for Azure Cosmos DB:
java
ConnectionPolicy policy = new ConnectionPolicy();
policy.getRetryOptions().setMaxRetryAttemptsOnThrottledRequests(9);
policy.getRetryOptions().setMaxRetryWaitTimeInSeconds(30);
In the above example, the policy is set to make a maximum of 9 retry attempts on throttled requests, with a maximum wait time of 30 seconds between retries.
Understanding and Handling 429s – Too Many Requests
When working with Azure Cosmos DB, you might encounter HTTP 429 response status code. It means the request rate is large than the RU/s (Request Units per second) allotted for your database or container. In other words, your application is being throttled because it is exceeding its provisioned throughput capacity.
Again, retry policies come into play here. Azure Cosmos DB SDKs have a built-in mechanism to handle request rate too large exceptions. If your application receives a 429 – “Too many requests” response code, the SDK will handle it by implementing a retry after the period suggested by the `x-ms-retry-after-ms` header in the response.
Here’s a simple example using the .NET SDK:
csharp
CosmosClientOptions clientOptions = new CosmosClientOptions()
{
MaxRetryAttemptsOnRateLimitedRequests = 9,
MaxRetryWaitTimeOnRateLimitedRequests = TimeSpan.FromSeconds(30)
};
In this example, we’ve set the maximum number of retries on rate-limited requests to 9 and the maximum wait time between those retries to 30 seconds.
While handling 429s and transient errors, one should aim to balance between maintaining up time, avoiding data loss, and managing the cost associated with increased request units (RU).
Comparing Retry Policies
| Retry Policy Parameter | Description | Ideal Value |
|---|---|---|
| MaxRetryAttemptsOnRateLimitedRequests | The max number of retries for rate-limited requests | Should be set based on business needs and cost considerations |
| MaxRetryWaitTimeOnRateLimitedRequests | The max wait time between retries for rate-limited requests | Should be set high enough to allow for transient errors to pass |
Remember, configuring the correct retry policies and handling transient failures and 429s effectively is crucial when designing and implementing native applications using Microsoft Azure Cosmos DB for optimal performance, reliability and data consistency. Make sure to test different configurations to find the optimal settings for your specific use case.
Practice Test
True or False: Transient errors are temporary errors that may self-correct if the operation is repeated.
Answer: True
Explanation: Transient errors are not permanent and are often resolved if the operation is tried again after a short period of time.
What does status code 429 represent in HTTP requests?
- A) Not Found
- B) Server Error
- C) Too Many Requests
- D) Unauthorized
Answer: C) Too Many Requests
Explanation: HTTP status code 429 indicates that the user has sent too many requests in a given amount of time.
True or False: Retry policies can be implemented to handle transient errors in Azure Cosmos DB.
Answer: True
Explanation: Implementing retry policies is a common strategy used to combat transient errors in Azure Cosmos DB.
Which of the following can be a reason for a 429 error in Azure Cosmos DB?
- A) Network congestion
- B) Exceeded provisioned throughput
- C) Authorization issue
- D) Disk Failure
Answer: B) Exceeded provisioned throughput
Explanation: A 429 error occurs when the request rate is large and exceeds the provisioned throughput limit.
True or False: Increasing the provisioned throughput can resolve 429 errors in Azure Cosmos DB.
Answer: True
Explanation: If the request rate exceeds the provisioned throughput, increasing the provisioned throughput can prevent 429 errors.
Which of the following should be considered while designing retry policy for transient errors?
- A) Time between retries
- B) Max number of retries
- C) Both A and B
- D) Neither A nor B
Answer: C) Both A and B
Explanation: Both the time between retries and the maximum number of retries are important considerations while designing a retry policy.
True or False: Transient errors can often be resolved without any action from the user or application.
Answer: False
Explanation: Although transient errors are temporary, they typically require some form of action such as a retry mechanism or a request delay to be resolved.
In what situation might you use exponential backoff when handling 429s?
Answer: When your request volume exceeds the limit, and immediate retries are not succeeding
Explanation: Exponential backoff is a method that gradually increases the delay between retries to reduce the load on the system and increase the chances of a successful retry.
Which status code is related to transient errors in Azure Cosmos DB?
- A) 400
- B) 429
- C) 404
- D) 500
Answer: B) 429
Explanation: 429 status code is related to transient errors as it means “Too many requests”(i.e., exceeding the provisioned throughput).
True or False: Properly handling transient errors can prevent application from crashing.
Answer: True
Explanation: Proper handling of transient errors, such as implementing retry logic and properly managing request rate in relation to provisioned throughput, can help maintain application uptime and prevent crashes.
Interview Questions
What is a transient error in Azure Cosmos DB?
A transient error in Azure Cosmos DB is a temporary error that may resolve itself when the operation is retried. These can be caused by a variety of factors such as network interruptions, timeouts, throttling, or a busy resource, among others.
What type of transient errors does the Azure Cosmos DB SDK handle?
Azure Cosmos DB SDK automatically handles some types of transient errors, such as request timeouts and rate limiting (HTTP status code 429).
How does Azure Cosmos DB handle too many requests?
Azure Cosmos DB throttles requests and returns HTTP status code 429 (Too Many Requests) when a client makes too many requests within a certain period. This is to prevent denial of service attacks and also to maintain overall system performance.
What is the best practice to handle a 429 (Too Many Requests) error in Azure Cosmos DB?
Best practice for handling 429 errors is to incorporate a retry policy in application code. This policy will retry the operation after a specified delay when a 429 error is encountered.
What information does the x-ms-retry-after-ms header provide?
The x-ms-retry-after-ms header provides the recommended wait time (in milliseconds) to retry the operation after receiving a 429 (Too Many Requests) error.
Is the retry count limit for a transient error in Azure Cosmos DB customizable?
Yes, the retry count can be customized using CosmosClientOptions.MaxRetryAttemptsOnRateLimitedRequests on the SDK.
How can you increase the throughput provisioned for a container to avoid 429 errors in Azure Cosmos DB?
To increase the throughput of a container, you can call the ReplaceThroughputAsync method on the Container object, providing it with a new ThroughputProperties object with the desired throughput.
How does the Azure Cosmos DB handle transient errors by default?
By default, Azure Cosmos DB SDK retries nine times for read operations and retries once for write operations when a transient error is encountered.
Can the throttle behavior of Azure Cosmos DB be simulated during testing?
Yes, you can simulate the throttle behavior by using the Request unit charge header (“x-ms-request-charge”). If a client exceeds the provisioned throughput for a container or database, Azure Cosmos DB will throttle that client and return HTTP status code 429 (Too Many Requests).
What is the role of the MaxRetryWaitTimeOnRateLimitedRequests in a RetryOptions object linked to CosmosClientOptions?
The MaxRetryWaitTimeOnRateLimitedRequests defines the maximum wait time in seconds for which the SDK will retry on rate-limited requests (429) before throwing an exception.
Why are transient errors significant in Azure Cosmos DB operations?
Transient errors are important because they represent temporary and often self-resolving issues. Appropriate handling of these errors can increase the robustness of applications using Azure Cosmos DB by ensuring that operations are successful even under unstable network conditions, or during periods of high request volumes.
Why might enabling the Direct connectivity mode result in increased 429 status codes?
Switching to Direct mode might increase 429 status codes as this mode uses many more concurrent connections. This can lead to higher rates of request and therefore higher likelihood of exceeding rate limits.
How can the exponential back-off strategy assist in handling transient errors effectively?
The exponential back-off strategy ensures that clients retry requests less frequently as the number of attempts increase. This helps to reduce contention and allows the service to recover, effectively handling transient errors.
How is automated failover affected by transient errors in Azure Cosmos DB?
A transient error may trigger an automatic failover in Azure Cosmos DB. However, failovers are no substitute for implementing a robust retry policy in the application code, as some network or service errors may not trigger a failover.
Why is it important to set MaxRetryAttemptsOnRateLimitedRequests and MaxRetryWaitTimeOnRateLimitedRequests when setting up a Cosmos client?
It is important to set these parameters as they control the client’s behavior in terms of retrying operations that have been rate limited (429 errors). Setting these appropriately can help to prevent requests from failing due to exceeding the provisioned throughput.
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