langfuse-performance-tuning
Optimize Langfuse tracing performance for high-throughput applications. Use when experiencing latency issues, optimizing trace overhead, or scaling Langfuse for production workloads. Trigger with phrases like "langfuse performance", "optimize langfuse", "langfuse latency", "langfuse overhead", "langfuse slow". '
Profile →npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill langfuse-performance-tuning --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Langfuse Performance Tuning ## Overview Optimize Langfuse tracing for minimal overhead and maximum throughput: benchmark measurement, batch tuning, non-blocking patterns, payload optimization, sampling, and memory management. ## Prerequisites - Existing Langfuse integration - Performance baseline to compare against - Understanding of async patterns ## Performance Targets | Metric | Target | Critical | |--------|--------|----------| | Trace creation overhead | < 1ms | < 5ms | | Flush latency (batch) | < 100ms | < 500ms | | Memory per active trace | < 1KB | < 5KB | | CPU overhead | < 1% | < 5% | ## Instructions ### Step 1: Benchmark Current Performance ```typescript // scripts/benchmark-langfuse.ts import { performance } from "perf_hooks"; import { startActiveObservation, updateActiveObservation } from "@langfuse/tracing"; import { LangfuseSpanProcessor } from "@langfuse/otel"; import { NodeSDK } from "@opentelemetry/sdk-node"; async function benchmark() { const sdk = new NodeSDK({ spanProcessors: [new LangfuseSpanProcessor()], }); sdk.start(); const iterations = 1000; // Measure trace creation const timings: number[] = []; for (let i = 0; i < iterations; i++) { const start = perfo
- Overview
- Prerequisites
- Performance Targets
- Instructions
- Step 1: Benchmark Current Performance
- Step 2: Optimize Batch Configuration
- Step 3: Non-Blocking Trace Wrapper
- Step 4: Payload Size Optimization
- Step 5: Sampling for Ultra-High Volume
- Step 6: Memory Management
- Optimization Impact Matrix
- Error Handling
- Resources
What does the langfuse-performance-tuning skill do?
Optimize Langfuse tracing performance for high-throughput applications. Use when experiencing latency issues, optimizing trace overhead, or scaling Langfuse for production workloads. Trigger with phrases like "langfuse performance", "optimize langfuse", "langfuse latency", "langfuse overhead", "langfuse slow". '
How do I install it?
Run `npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill langfuse-performance-tuning --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From jeremylongshore/claude-code-plugins-plus-skills, a repository with 2,630 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.