Transient Error Handling: The Importance of a Commonly Overlooked Practice in Distributed Systems
Transient error handling in distributed systems is among the usual activities that need to be addressed to maintain consistency and reliability. However, most of the developers and software engineers do not take it seriously, and because of its negligence, disastrous consequences may occur on application stability and security.
What are transient errors?
Transient errors are temporary issues that happen in a distributed system and are usually caused by network problems, congestion at servers, timeouts, or situations that are temporary in nature and might get resolved after some time. Unlike permanent errors, which depict failure needing direct intervention, transient errors can be managed proactively with the help of retry mechanisms, timeout handling, and other resilience strategies.
Impact of the transient error on data consistency
In a distributed context, where data and processes are scattered amongst nodes and networks, transient error handling becomes of key importance in maintaining consistency. A network error or network timeout can interfere with a transaction or an operation of writing data in a distributed database, resulting in a system incoherent. Consider, for example, that some transient error in a payment system causes an application to have money deducted from a client’s account but fails to record it in the recipient’s account. Lack of handling these errors reaps corruption of data, loss of information, and other anomalies that may hurt the experience of users and overall system reliability. Transient errors may merely manifest themselves in the form of some network timeout; their ignorance may cause severe issues related to message duplication, data loss, and consistency problems in databases.
Why is Transient Error Handling Often Ignored?
Despite its importance, transient error handling is often ignored due to a number of reasons:
- Underestimation of risk: Transient errors are considered very rare, negligible events by most developers. This may lead to a lack of implementation for error handling or retry logic in the system, which are most important for resilience.
- False Assumption of Network Reliability: Many assume that the network is always reliable, and the different components in the distributed system will have no issues communicating with each other. In real-world systems, network failures are inevitable, and proper handling of such failures is an absolute necessity.
- Lack of Awareness: Not all developers are aware of the different strategies in error handling, which include exponential backoff retries, circuit breakers, or temporary result caching. Most common reasons for these are a lack of awareness that will eventually translate into an implementation not robust enough.
Best Practices for Handling Transient Errors
In order to guarantee consistency in data and in system resilience within a distributed system, some best practices have to be put in place:
- Exponential Backoff Retries: In case of a transient error, if the failed operation was retried after an exponentially growing time gap, then the extra pressure on the system is less and maximizes the probability of success if it was a temporary fault.
- Use Circuit Breakers: It monitors errors coming from the calls to external services and blocks requests temporarily when a number of failures are detected, hence protecting the system from overload and long timeouts.
- Handle Timeouts Properly: Setting up proper timeouts in network operations makes it critical. Resources do not have to wait for ever for a response that may never come.
- Implement transient fault-based caching strategies: Storing the results of operations that might be affected by transient errors can reduce the number of redundant calls and improve overall performance.
- Monitoring and logging: It is essential to constantly monitor the system and log all errors, including transient ones, to analyze and handle them more efficiently in the future.
Solutions in .NET for Handling Transient Errors
- Polly - Resilience Library for .NET
- Automatic Retries and Transactions with Entity Framework Core
- Error Handling in HTTP Calls with HttpClientFactory
- Circuit Breaker and Retry Patterns with Microsoft.Extensions
- Using Azure SDK and Resilience Tools
1. Polly - Resilience Library for .NET
Polly is a popular library for resilience and fault handling in .NET. It supports various resilience patterns such as Retry, Circuit Breaker, Fallback, Timeout, and more. Here’s how you can use Polly to handle transient errors:
-
Retry Policy: Retries a failed operation a specified number of times with an optional delay between attempts.
var retryPolicy = Policy .Handle<SqlException>() // Handle specific exceptions .WaitAndRetry( retryCount: 3, // Number of retries sleepDurationProvider: retryAttempt => TimeSpan.FromSeconds(Math.Pow(2, retryAttempt)), // Exponential backoff onRetry: (exception, timespan, retryCount, context) => { // Log the retry attempt }); -
Circuit Breaker Policy: Prevents further attempts when a series of faults occur, allowing time for recovery.
var circuitBreakerPolicy = Policy .Handle<Exception>() .CircuitBreaker( exceptionsAllowedBeforeBreaking: 3, // Number of exceptions before breaking durationOfBreak: TimeSpan.FromMinutes(1) // Time before retrying ); -
Combining Policies: You can combine multiple policies, such as retry and circuit breaker, to create a more robust error-handling strategy.
var combinedPolicy = Policy.Wrap(retryPolicy, circuitBreakerPolicy);
2. Automatic Retries and Transactions with Entity Framework Core
Entity Framework Core provides built-in support for handling transient errors with SQL Server and other databases. The EnableRetryOnFailure method can be configured when setting up the DbContext to automatically retry database operations that fail due to transient issues.
public class ApplicationDbContext : DbContext
{
protected override void OnConfiguring(DbContextOptionsBuilder optionsBuilder)
{
optionsBuilder.UseSqlServer(
"YourConnectionString",
sqlServerOptions => sqlServerOptions.EnableRetryOnFailure(
maxRetryCount: 5, // Number of retry attempts
maxRetryDelay: TimeSpan.FromSeconds(10), // Max delay between retries
errorNumbersToAdd: null // Specific SQL error numbers to consider transient
));
}
}
3. Error Handling in HTTP Calls with HttpClientFactory
.NET Core provides HttpClientFactory, which integrates well with Polly to handle transient HTTP errors when calling external APIs. This is useful for handling common HTTP errors like timeouts, 500 errors, and more.
services.AddHttpClient("MyHttpClient", client =>
{
client.BaseAddress = new Uri("https://example.com/");
})
.AddTransientHttpErrorPolicy(policyBuilder =>
policyBuilder.WaitAndRetryAsync(3, retryAttempt => TimeSpan.FromSeconds(retryAttempt)));
With HttpClientFactory, you can set up a retry policy, a circuit breaker, or any other Polly policies directly within the HTTP client configuration.
4. Circuit Breaker and Retry Patterns with Microsoft.Extensions
.NET offers built-in support for resilience patterns through Microsoft.Extensions.Http and Microsoft.Extensions.DependencyInjection. You can use these extensions to configure a HttpClient with retry and circuit breaker policies using Polly.
5. Using Azure SDK and Resilience Tools
If you’re working with Azure services, the Azure SDKs provide built-in resilience capabilities. For instance:
- Azure Cosmos DB: Automatically retries on transient errors with exponential backoff.
- Azure Service Bus: Supports retry policies that can be configured to handle transient connectivity issues.
Azure SDKs are designed with resilience in mind, providing a range of configuration options to handle transient failures effectively.
Conclusion
Handling transient failures is not only a best practice but an essential requirement to build robust and resilient distributed systems. Neglect of this best practice would severely deteriorate data consistency and the stability of the entire system. Therefore, it must be ensured that all software professionals are aware of the importance of properly handling these kinds of errors and that sufficient strategies to mitigate the risks concerned are implemented. Only then are we able to work out systems capable of successfully facing all the complexity and challenges of today’s distributed environments.