Retry Pattern - Microservice - How this helps on migration strategy
Retry Pattern
Several migration strategies were identified during the research, and this pattern stands out as an excellent approach.
Its Role in Migration
The Retry Pattern handles transient faults,
such as network failures or timeouts, during communication between services or
components. During migration, where parts of a monolith are replaced with
microservices, this pattern ensures resilience by automatically retrying failed
operations.
Migrating modules with high-availability
requirements like payments, order processing, or inventory updates. Scenarios
involving third-party APIs or network-dependent components.
- Retry Count: Limits retries to several
attempts (configurable).
- Exponential Backoff:
Increases the wait time between retries to avoid overwhelming the service.
- Fallback Mechanism:
Returns an appropriate message if retries fail.
Handles Temporary Failures:
During migration, new microservices or APIs may not
always be stable. Retrying helps handle intermittent failures gracefully.
Improves User Experience:
Users won't see errors immediately if retries resolve
temporary issues.
Supports Partial Migration:
Network or integration issues can be mitigated with
retries when the monolith and microservices coexist.
Advantages of Using the Retry Pattern During Migration
Reduces risk of downtime when integrating with
unstable or new microservices.
Ensures smooth user experience during the transitional
phase.
Simplifies error handling by abstracting retracting
into a reusable policy.
Use Case Example: Migrating Payment Processing
Imagine you’re migrating a Payment Processing
module from a monolithic application to a microservice. The monolith still
handles order creation, but the payment functionality has been moved to a
microservice.
Monolith Code Before Migration
public class PaymentService
{
public bool ProcessPayment(string orderId,
decimal amount)
{
// Simulate payment processing logic
return true;
}
}
Post-Migration: Monolith Calls the Payment
Microservice
The monolith makes HTTP calls to the payment
microservice in the new setup. To handle transient failures, implement the Retry
Pattern.
C# Example with Retry Pattern
Using Polly, a .NET library for resilience and
transient fault handling:
- Install Polly NuGet Package:
dotnet add package Polly
- Implement the Retry Logic:
using System;
using System.Net.Http;
using System.Threading.Tasks;
using Polly;
using Polly.Retry;
public class PaymentService
{
private readonly HttpClient _httpClient;
private readonly AsyncRetryPolicy<HttpResponseMessage>
_retryPolicy;
public PaymentService(HttpClient httpClient)
{
_httpClient = httpClient;
// Define the retry policy
_retryPolicy = Policy
.HandleResult<HttpResponseMessage>(r => !r.IsSuccessStatusCode)
.Or<HttpRequestException>()
.WaitAndRetryAsync(
retryCount:
3,
sleepDurationProvider:
attempt => TimeSpan.FromSeconds(Math.Pow(2,
attempt)),
onRetry:
(response, timespan,
retryCount, context)
=>
{
Console.WriteLine($"Retrying...
Attempt: {retryCount}");
});
}
public async Task<bool>
ProcessPayment(string orderId,
decimal amount)
{
var paymentRequest = new
{
OrderId = orderId,
Amount = amount
};
var httpRequest = new HttpRequestMessage(HttpMethod.Post,
"http://payment-service/api/payments")
{
Content = new StringContent(System.Text.Json.JsonSerializer.Serialize(paymentRequest),
System.Text.Encoding.UTF8,
"application/json")
};
// Execute with retry
var response = await _retryPolicy.ExecuteAsync(()
=> _httpClient.SendAsync(httpRequest));
if (response.IsSuccessStatusCode)
{
Console.WriteLine("Payment
processed successfully.");
return true;
}
Console.WriteLine("Payment
failed after retries.");
return false;
}
}
Steps in Migration with Retry Pattern
- Migrate Payment Logic to a Microservice:
The payment
service is deployed as a standalone microservice.
- Integrate Retry Logic in the Monolith:
Add retry
logic to handle network issues or temporary unavailability of the payment
microservice.
- Test in a Hybrid Environment:
Test the
monolith and microservice integration with scenarios like timeouts and service
restarts.
Comments
Post a Comment