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What microservices are
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Why .NET 10 is a strong choice
- Core principles for high performance
- How to build fast and efficient microservices
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Common mistakes to avoid
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How Sparkle Web approaches microservices development
What Are Microservices?
Key Features of Microservices
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Independent – each service runs separately
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Deployable on its own – you can update one service without affecting others
- Loosely connected – services talk to each other through APIs or messages
- Scalable – each service can scale based on its own needs
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Flexible – teams can work on different services at the same time
Example
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Users
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Products
- Orders
- Payments
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Notifications
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User Service
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Product Catalog Service
- Order Service
- Payment Service
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Notification Service
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Has its own logic
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Can be updated independently
- Can scale based on traffic
Why Choose .NET 10 for Microservices?
Key Benefits of .NET 10
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High speed and fast response times
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Low memory usage
- Strong support for async programming
- Simple APIs for lightweight services
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Built-in tools for dependency handling
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Excellent support for containers and cloud platforms
Core Principles of High-Performance Microservices
1. One Responsibility per Service
- One service handling users, payments, and notifications
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User Service handles user data
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Payment Service handles payments
- The Notification Service sends messages
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Keeps code simple
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Makes testing easier
- Improves performance and stability
2. Stateless Services
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Services can scale easily
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Any request can go to any server
- No special session handling is needed
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Databases
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Redis or distributed cache
- External storage systems
3. Database per Microservice
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Creates tight connections between services
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Slows down performance
- Makes changes risky
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Changes are safer
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Performance improves
- Scaling is easier
Building a High-Performance Microservice with .NET 10
Step 1: Use Minimal APIs
var builder = WebApplication.CreateBuilder(args);
var app = builder.Build();
app.MapGet("/health", () => Results.Ok("Service is running"));
app.Run();
Benefits:
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Faster startup
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Lower memory use
- Clean and simple code
- Ideal for microservices
Step 2: Use Async Code Everywhere
var data = repository.GetData();
var data = await repository.GetDataAsync();
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Uses fewer threads
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Handles more requests at once
- Improves response times
High-Performance Data Access
Use Lightweight Data Tools
var products = await connection.QueryAsync<Product>(
"SELECT * FROM Products WHERE IsActive = 1");
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Faster queries
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Less memory usage
- Better control over SQL
Optimize Database Usage
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Adding proper indexes
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Avoiding too many database calls
- Caching frequently used data
- Keeping queries simple
Caching for Better Performance
Use Redis or Distributed Cache
var cached = await redis.GetStringAsync("product_123");
if (cached != null)
return JsonSerializer.Deserialize<Product>(cached);
// Fetch from DB and save to cache
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Faster responses
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Lower database usage
- Better performance under high traffic
Communication Between Microservices
Prefer Asynchronous Messaging
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RabbitMQ
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Azure Service Bus
- Kafka
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Reduces delays
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Avoids tight connections
- Prevents failures from spreading
Resilience and Stability
Handle Failures Gracefully
services.AddHttpClient("order-service")
.AddTransientHttpErrorPolicy(policy =>
policy.WaitAndRetryAsync(3, retry => TimeSpan.FromMilliseconds(200)));
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Improves reliability
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Keeps systems stable during issues
Security Without Slowing Things Down
Use JWT Authentication
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Fast
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Stateless
- Easy to scale
services.AddAuthentication("Bearer")
.AddJwtBearer();
Secure Internal Communication
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API gateways
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Private networks
- Secure certificates
Containerization and Deployment
Use Docker for Each Service
FROM mcr.microsoft.com/dotnet/aspnet:10.0
WORKDIR /app
COPY . .
ENTRYPOINT ["dotnet", "ProductService.dll"]
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Same environment everywhere
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Faster deployments
- Easy scaling
Monitoring and Observability
Logging
Log.Information("Order created with ID {OrderId}", orderId);
Metrics and Tracing
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OpenTelemetry
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Prometheus
- Grafana
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Detect slow endpoints
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Track memory usage
- Monitor traffic patterns
Performance Testing
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Run load tests
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Measure response times
- Find slow areas early
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k6
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JMeter
Common Performance Mistakes to Avoid
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Too many service-to-service calls
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Large data responses
- Blocking async code
- Shared databases
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No caching
How We Build High-Performance .NET Microservices
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Strong service design
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Performance-focused coding
- Cloud-ready deployment
- Secure and stable systems
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Ongoing monitoring and improvement
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Reduce infrastructure costs
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Handle high traffic smoothly
- Release features faster
- Scale without rebuilding everything
Conclusion
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Smart design
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Clean code
- Efficient data handling
- Continuous improvement
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Excellent performance
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Cloud-ready tools
- High developer productivity
- Strong security

Dipak Pakhale
A skilled .Net Full Stack Developer with 8+ years of experience. Proficient in Asp.Net, MVC, .Net Core, Blazor, C#, SQL, Angular, Reactjs, and NodeJs. Dedicated to simplifying complex projects with expertise and innovation.
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