5 Days Program Advanced performance engineering in .NET:

Category	Tool(s)	Why it’s the best (quick note)
Code Profiling & Debugging	Visual Studio Profiler, JetBrains dotTrace	Deep CLR insights; VS built-in + dotTrace’s powerful async/timeline views
Memory & GC Analysis	JetBrains dotMemory, PerfView	dotMemory excels at leak/retention graphs; PerfView is unmatched for ETW/GC deep dives
Micro-Benchmarking	BenchmarkDotNet	Gold standard for accurate, repeatable .NET microbenchmarks
Load & Stress Testing	k6, Apache JMeter	k6 is modern/CI-friendly; JMeter remains versatile and widely adopted

10 Days Program Advanced performance engineering in .NET:

Category	Tool(s)	Why it’s the best (quick note)
Code Profiling & Debugging	Visual Studio Profiler, JetBrains dotTrace	Deep CLR insights; VS built-in + dotTrace’s powerful async/timeline views
Memory & GC Analysis	JetBrains dotMemory, PerfView	dotMemory excels at leak/retention graphs; PerfView is unmatched for ETW/GC deep dives
Micro-Benchmarking	BenchmarkDotNet	Gold standard for accurate, repeatable .NET microbenchmarks
Load & Stress Testing	k6, Apache JMeter	k6 is modern/CI-friendly; JMeter remains versatile and widely adopted
APM (Production)	Azure Application Insights, Dynatrace	App Insights is first-class for .NET/Azure; Dynatrace offers superb auto-discovery & AI insights
Distributed Tracing	OpenTelemetry (.NET SDK), Jaeger	OTel is the vendor-neutral standard; Jaeger is a robust open-source backend
System & Infra Monitoring	Prometheus + Grafana, Azure Monitor	Prom+Grafana for flexible metrics/visuals; Azure Monitor for tight Azure integration
CI/CD Perf Automation	k6 (in pipelines), BenchmarkDotNet (in CI)	Shift-left perf gates with k6; catch code-level regressions via BenchmarkDotNet on PRs

Here’s a comprehensive and balanced agenda (theory + hands-on + labs + project).

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Comprehensive 5-Day Training Program

Advanced Performance Engineering in .NET

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Day 1 – Foundations of Performance Engineering in .NET

1.1 Introduction to Performance Engineering

• Importance of performance engineering in modern .NET systems
• Difference between performance testing and performance engineering
• Key metrics: throughput, latency, response time, scalability
• Understanding SLAs, SLOs, SLIs for .NET services

1.2 .NET Runtime and Performance Model

• CLR execution model (JIT, RyuJIT, Tiered Compilation)
• Garbage Collection (GC) modes (Workstation, Server, Background, Low-latency)
• Threading model in .NET Core/5/6/7/8

1.3 Performance Metrics & Baselines

• Establishing baseline performance for .NET apps
• Identifying acceptable thresholds for web vs desktop vs microservices

1.4 Hands-On Lab

• Build a sample ASP.NET Core application
• Use built-in Visual Studio Diagnostic Tools to measure CPU, memory, and response times
• Capture baseline metrics and document

Takeaway: Clear understanding of how performance is measured and baselined in .NET apps.

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Day 2 – Identifying Bottlenecks in .NET Applications

2.1 Common Bottlenecks in .NET Systems

• CPU-bound vs I/O-bound workloads
• Async/await pitfalls, deadlocks, and thread starvation
• Memory leaks, excessive allocations, and GC pressure
• ORM/Database inefficiencies (EF Core pitfalls)

2.2 Tools & Techniques to Find Bottlenecks

• Visual Studio Profiler (live profiling)
• JetBrains dotTrace (timeline + async flows)
• dotMemory for leak detection and heap analysis
• PerfView for ETW-based deep runtime analysis

2.3 Hands-On Labs

• Lab 1: Profile a .NET Core Web API under simulated load (Visual Studio Profiler)
• Lab 2: Identify memory leaks with dotMemory and fix them
• Lab 3: Analyze GC events with PerfView

Takeaway: Developers can confidently locate performance bottlenecks at code and runtime level.

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Day 3 – Benchmarking & Load Testing for .NET

3.1 Benchmarking in .NET

• Importance of benchmarking in microservices and libraries
• Writing micro-benchmarks with BenchmarkDotNet
• Avoiding benchmarking pitfalls (JIT warmup, dead-code elimination)

3.2 Load & Stress Testing

• Types of performance tests: load, stress, spike, endurance
• When to use each in a .NET application lifecycle
• Integrating load testing into CI/CD pipelines

3.3 Tools for Load Testing

• k6: modern load testing for APIs/microservices
• Apache JMeter: traditional load/stress/endurance testing

3.4 Hands-On Labs

• Lab 4: Write and run micro-benchmarks with BenchmarkDotNet
• Lab 5: Execute load tests on ASP.NET Core APIs using k6
• Lab 6: Stress test with JMeter and analyze reports

Takeaway: Ability to design and execute reliable benchmarks and load tests.

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Day 4 – Multi-Layer Optimization in .NET Systems

4.1 Application Layer Optimizations

• Efficient memory management in .NET (object pooling, Span, ValueTask)
• Async programming best practices (Task vs Thread vs Parallel)
• LINQ optimizations and avoiding hidden allocations
• Using caching strategies in ASP.NET Core

4.2 Middleware & Server Optimizations

• Kestrel tuning for high-throughput APIs
• gRPC performance tuning in .NET Core
• Messaging broker performance (Azure Service Bus, RabbitMQ, Kafka with .NET)

4.3 Database Layer Optimizations

• Optimizing EF Core queries (N+1 problems, eager vs lazy loading)
• Indexing and query execution plans (SQL Server Profiler, Query Store)
• Database connection pooling and transaction management

4.4 Hands-On Labs

• Lab 7: Optimize EF Core queries and compare performance before vs after
• Lab 8: Tune Kestrel server settings and measure throughput improvements
• Lab 9: Database profiling with SQL Profiler on a sample .NET app

Takeaway: Developers can optimize performance across application, middleware, and database layers.

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Day 5 – Continuous Performance Engineering & Capstone Project

5.1 Continuous Performance Monitoring

• Integrating BenchmarkDotNet + k6 in CI/CD pipelines (Azure DevOps, GitHub Actions)
• Automated performance regression tests
• Monitoring .NET services with Azure Application Insights
• Using OpenTelemetry .NET SDK for distributed tracing

5.2 Resilience & Chaos Engineering

• Implementing Polly for retries, fallbacks, circuit breakers
• Testing resilience with Azure Chaos Studio
• Observability dashboards with Grafana + Prometheus (for .NET containers)

5.3 Capstone Project

• End-to-end performance engineering project on a sample ASP.NET Core microservice:
  • Profile & identify bottlenecks
  • Optimize code, database, and middleware
  • Benchmark with BenchmarkDotNet
  • Load test with k6
  • Monitor with Application Insights
  • Demonstrate improvements in metrics

5.4 Wrap-Up & Knowledge Consolidation

• Performance engineering checklist for .NET projects
• Best practices for enterprise adoption
• Q&A and discussion on applying learnings to real projects
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Takeaway: Developers leave with a full lifecycle understanding — from profiling to optimization to continuous performance in production.

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📊 Tools Focused Summary (Quick Reference)

Category	Tool(s)	Why it’s the best
Code Profiling & Debugging	Visual Studio Profiler, JetBrains dotTrace	CLR + async/timeline insights
Memory & GC Analysis	JetBrains dotMemory, PerfView	Leak detection + ETW runtime deep dive
Micro-Benchmarking	BenchmarkDotNet	Accurate, repeatable benchmarking
Load & Stress Testing	k6, Apache JMeter	CI/CD friendly + versatile
Continuous Monitoring & APM	Azure Application Insights, OpenTelemetry	First-class .NET monitoring & tracing
Chaos & Resilience	Polly, Azure Chaos Studio	Code-level + infrastructure-level resilience

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