jit

Diagnose .NET JIT compilation overhead using Prometheus and OpenTelemetry metrics.

12|2|Updated May 4, 2020
One-click install
npx skills add https://github.com/hoangnh2412/jarvis --skill jit-hoangnh2412
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: jit
Source: https://github.com/hoangnh2412/jarvis/tree/main/.opencode/skills/analyze-metric-dotnet/providers/jit
Command: npx skills add https://github.com/hoangnh2412/jarvis --skill jit-hoangnh2412

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill eliminates the guesswork when diagnosing .NET application performance issues caused by JIT (Just-In-Time) compilation, helping you quickly identify whether cold starts, dynamic code generation, or large assembly loads are impacting your service's latency and throughput.

Core Features & Use Cases

  • JIT Metric Interpretation: Parse and explain key JIT-related metrics including compiled method count, total IL bytes processed, and cumulative JIT compilation time from Prometheus and OpenTelemetry data sources.
  • Anomaly Detection: Recognize common JIT behavior patterns such as expected post-deploy spikes versus abnormal persistent high JIT times that indicate underlying runtime issues.
  • Use Case: Imagine your .NET service experiences a 30-second cold start after each deployment. Use this Skill to analyze JIT metrics, confirm the spike is expected tiered compilation activity, and get recommendations for warm-up tests to meet your SLA requirements.

Quick Start

Use the jit skill to analyze the JIT time metrics for your .NET service deployed in the last hour and identify if any abnormal compilation patterns are affecting performance.

Frequently Asked Questions about jit

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I diagnose .NET JIT performance issues using Prometheus metrics?

Diagnose .NET JIT performance issues by interpreting Prometheus metrics like compiled method count and cumulative JIT time to distinguish expected tiered compilation spikes from abnormal dynamic code generation overhead. This identifies compilation bottlenecks affecting service latency.

Why does my .NET service have a long cold start after deployment?

Long .NET cold starts after deployment are often caused by JIT compilation overhead. Analyze OpenTelemetry JIT metrics to confirm if the spike is expected tiered compilation activity and apply warm-up tests to meet SLA requirements.

What is abnormal JIT compilation behavior in .NET applications?

Abnormal JIT compilation behavior in .NET involves persistent high JIT times that indicate runtime issues, contrasting with expected post-deploy spikes. It often points to underlying dynamic code generation or large assembly load problems.

Can I use OpenTelemetry to find .NET dynamic code generation bottlenecks?

Yes, you can use OpenTelemetry to find .NET dynamic code generation bottlenecks by parsing total IL bytes processed and cumulative JIT compilation time to pinpoint abnormal runtime code generation impacting performance.

How do I identify large assembly load issues from JIT metrics in .NET?

Identify large assembly load issues in .NET by analyzing JIT metrics for abnormal compilation patterns. High cumulative JIT times and total IL bytes processed reveal when large assemblies degrade application throughput.