.NET Performance Monitoring

Get end-to-end visibility into your .NET performance with application monitoring tools. Gain insightful metrics on performance bottlenecks with .NET monitoring to optimize your application.

When .NET Production Becomes Opaque?

Thread Contention Blindness

Thread pool pressure builds gradually. Engineers notice slowdowns without clear visibility into execution blocking.

Async Flow Breakage

Async and await chains lose continuity. Root-cause analysis stalls when execution context fragments across calls.

Exception Context Gaps

Unhandled exceptions surface without full runtime state. Engineers see failures but lack execution ownership.

Dependency Injection Shadows

External calls degrade unpredictably. Failures appear internal while root causes sit outside service boundaries.

Database Bottleneck Ambiguity

Latency spikes lack attribution. Mapping slow responses to specific database interactions becomes manual.

Configuration Drift Risks

Runtime behavior diverges across environments. Teams lose confidence in pre-production validation.

Garbage Collection Pressure

Memory pressure accumulates silently. Performance degrades before engineers recognize GC impact.

EF Query N+1 Plagues

Change tracking triggers hidden roundtrips per entity load. Devs profile DB hits without ORM execution plans.

Core Platform Capabilities

Inspect Performance Characteristics of .NET Requests with Precision

Break down how long each request spends in key stages of your .NET app so you can isolate slow components and optimize with confidence.

End-to-End Request TimingRoute Handler CostSQL Execution WeightCache Read EfficiencyOutbound Call Latency

Unclear Request Breakdown Under Load

Without request-level timing, slow pages can feel random, and precise spans are needed to see how long controllers, model binding, and serialization actually take.

Database Execution Padding Overall Response

Heavy SQL, inefficient LINQ, or repeated queries extend request duration, and correlating SQL cost with traces shows exactly where time is consumed.

Cache Miss Costs Masked Without Traces

Under-utilized or failing cache layers add time to request handling, and per-trace cache timing reveals the true impact on delivery duration.

Outbound Services Adding Invisible Waits

Third-party APIs such as authentication, payment gateways, or search services can extend response time, and per-call latency in traces shows which calls are most costly.

Garbage Collection and Thread Contention Affecting Throughput

Runtime pauses and thread pool contention under concurrent traffic can degrade overall handling, and correlating runtime metrics with traces exposes actionable patterns.

Frequently Asked Questions

Find answers to common questions about our platform