Tracely.cc — The "Holographic Camera" for Distributed Systems

Stop logging blindly. Capture every logical heartbeat in complex AI agent orchestration and distributed architectures with full-chain tracing.

Deploy Tracely SDK View Demo

tracely-demo.ts

import { Tracely } from '@tracely/sdk';

// Initialize Tracely with one line
const tracely = new Tracely({
  apiKey: process.env.TRACELY_API_KEY,
  serviceName: 'my-rag-system'
});

// Auto-trace your entire system
tracely.start();

// Track RAG pipeline
const span = tracely.startSpan('rag-query');
const docs = await vectorDB.search(query);
span.setTag('docs.count', docs.length);
span.finish();

// 🎯 View holographic trace in dashboard

Core Value Propositions

Holographic Flow Visualization

Stop staring at black terminals. Tracely renders complex RAG retrieval paths, Agent decision chains, and microservice calls into dynamic 3D topology maps in real-time.

Bottleneck Oracle

Automatically identify tail latency spikes. Using systems engineering algorithms, precisely pinpoint whether it's database index failure, slow LLM response, or network jitter.

Zero-Friction SDK

Supports MCP protocol and OpenTelemetry standards. Enable system-level deep observation with just one line of code.

Engineering-Grade Diagnostics

Designed for systems engineers. Built-in queuing theory models predict system stability performance under high concurrency.

Three-Layer Architecture

The Sensor - Data Collection Layer

eBPF-based kernel-level collection for non-invasive monitoring
Trace Context Propagation ensures Trace ID never gets lost
Seamless integration with RAG vector databases (Milvus/Pinecone)

The Brain - Processing Engine

Stream aggregation with Flink-like architecture
Lightweight AI models analyze data flow patterns
Identifies abnormal logic branches (loops, deadlocks)

The Lens - Holographic Display

WebGL/Three.js powered 3D topology interface
Zoom from global system state to individual function stacks
Real-time visualization of distributed traces

Key Functional Modules

RAG Deep Dive

Track query transformation, embedding latency, and Top-K retrieval scores with contribution analysis to final generation.

Agentic Workflow Trace

Monitor multi-agent collaboration, task distribution paths, and state synchronization across shared memory or databases.

Stability Analytics

Real-time Little's Law calculations (L = λW) predict system bottlenecks and potential crash points before they happen.

MCP Protocol Integration

Auto-discover all Model Context Protocol tools and servers for seamless cross-ecosystem tracing.

Natural Language Query

Ask "Why did RAGDebugger slow down yesterday at 3 PM?" and get instant trace analysis with root cause identification.

See Tracely in Action

▶

Interactive Demo

99.9%

Trace Capture Rate

<1ms

Overhead Latency

Real-time

3D Visualization