How to Perform Load Testing on .NET Applications
Load testing helps you understand how your .NET app behaves under expected and peak traffic. The process is broadly the same for ASP.NET Core, MVC, Web APIs, gRPC, or Blazor apps.
1. Define Goals Before Running Any Test
Ask these questions first:
✔ What are you testing?
API endpoints
MVC controller actions
SignalR hubs
Database-heavy operations
Authentication flows
✔ What are your performance targets?
Examples:
Response time: < 300 ms for 95th percentile
Throughput: 2,000 requests/sec
Max concurrent users: 5,000
Error rate: < 1%
✔ Test types:
Load test – expected traffic
Stress test – beyond capacity
Soak test – long-duration stability
Spike test – sudden load increase
2. Choose a Load-Testing Tool
⭐ Most Common Tools for .NET Apps
Tool Best For Notes
k6 APIs, microservices Scriptable in JS, cloud/distributed
JMeter Broad protocol support GUI + CLI
Azure Load Testing Cloud, scale, monitoring Native Azure integration
Visual Studio Load Testing (legacy) .NET devs Deprecated but still used
Locust Python-based scenarios Distributed load
Gatling High RPS APIs Scala-based
Recommended modern choice: k6 or Azure Load Testing.
3. Instrument Your .NET App for Observability
To understand bottlenecks, enable:
✔ Application Insights (Azure)
✔ OpenTelemetry (vendor neutral)
✔ ASP.NET Core built-in metrics
✔ Logging (Serilog, NLog, etc.)
Collect:
CPU, memory
GC pauses
Thread pool starvation
Database query timings
Request latency percentiles
Dependency call failures
4. Prepare a Load Testing Environment
Never load-test your production environment unless intentionally doing chaos experiments.
Options:
Staging environment (matching production hardware)
Isolated performance test cluster
Containerized microservices with scale-out capability
Ensure:
Same DB schema & sample data
Same API gateway/routing
Same caching mechanisms
Similar network topology
5. Create Load Test Scripts
Example: k6 script for .NET Web API
import http from 'k6/http';
import { sleep, check } from 'k6';
export let options = {
vus: 100, // virtual users
duration: '60s', // 1-minute load test
};
export default function () {
let res = http.get('https://yourapi.com/api/products');
check(res, {
'status is 200': (r) => r.status === 200,
'response time < 300ms': (r) => r.timings.duration < 300,
});
sleep(1);
}
Run it:
k6 run test.js
6. Execute Distributed or Cloud Load Tests
Azure Load Testing (best for .NET apps in Azure)
Capabilities:
Auto scaling thousands of concurrent users
Integration with App Insights
Stress, load, and spike tests
VNet/private endpoint support
Example Azure CLI:
az load test-run create --test-id MyLoadTest --resource-group RG
7. Analyze Performance Metrics
During & after testing, check:
Server Metrics
CPU usage consistently >80%?
Memory pressure?
Thread pool starvation?
Number of active connections?
Garbage Collection (GC) Gen2 spikes?
Application Metrics
Response time percentiles (P50, P95, P99)
Throughput (requests/sec)
Error rates (HTTP 500, timeouts)
Dependency failures (SQL, Redis, gRPC)
Database Metrics
Slow queries
Locking/blocking
Connection pool exhaustion
Missing indexes
Infrastructure Metrics
Load balancer latency
Autoscaling events
Network bandwidth saturation
8. Identify & Fix Bottlenecks
Common .NET issues and fixes:
✔ Thread Pool Starvation
Enable EventCounters or use:
ThreadPool.GetAvailableThreads(out int worker, out int io);
Fix: Increase thread pool or optimize async code.
✔ Database Bottlenecks
Fix: indexes, caching, batching queries.
✔ Heavy GC Pressure
Fix: reduce allocations, pool objects, use Span<T>, optimize serializers.
✔ Blocking Calls in Async Code
Fix: eliminate .Result / .Wait() usage.
✔ Slow External API Calls
Fix: caching, circuit breakers (Polly).
9. Re-run Tests After Each Optimization
Load testing is iterative.
Repeat the loop:
Run load test
Analyze data
Fix bottleneck
Run again
Stop when performance meets KPIs.
10. Integrate Load Testing into CI/CD
Example setups:
GitHub Actions + k6 Cloud
Azure DevOps Pipeline + Azure Load Testing
GitLab CI + Locust
Benefits:
Prevent regressions
Catch slow endpoints early
Enforce performance SLAs
🎯 Summary Checklist
✔ Prepare goals & metrics
✔ Choose tools (k6, JMeter, Azure Load Testing)
✔ Instrument app (Logging + Application Insights)
✔ Use production-like environment
✔ Write load test scripts
✔ Execute distributed/cloud tests
✔ Analyze performance (CPU, GC, DB, latency)
✔ Optimize
✔ Re-test
✔ Automate in CI/CD
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