Physics · Disruptor · Concurrency Analyser
Initialising physics engine…
WebSocket · Connected
FPS 60
T 8 · P 0
DISRUPTOR RING BUFFER SEQ:0
CLICK & DRAG → LAUNCH CHAOS COMET
β (pitch)--
γ (roll)--
gravity0.20
joystick x0.00
⚠️
HIGH CONTENTION – Disruptor holding steady RingBuffer backpressure · Producers spinning · Sequence barrier stalled
Lock Wait Latency0.01 ms
Queue Depth · By Lock Type0
Throughput · Events/sec0
Thread Status
Thread Activity Timeline (last 40 ticks)
Hot Methods · Contention Rank
RingBuffer Slots (64) · Live Sequence View
🟢 System Health Score
— /100
INITIALISING
Waiting for first JVM snapshot…
🤖 AI Root Cause Analysis REAL-TIME · JVM SIGNALS
Initialising… HEALTHY
Confidence
—
Waiting for first JVM metrics snapshot…
—
Diagnosis History (last 10)
No history yet — waiting for data…
Live Disruptor Metrics
Sequence Cursor0
Spin Count0
Producer Claims0
Park Count0
Backoff Yields0
Avg Batch Size0
Buffer Size1024
Wait StrategyPhasedBackoff
JCStress · All Tests Passed
Physics Controls
Particles 80
Gravity 0.20
Elasticity 0.85
Thread Pool 8
Contention Event Stream
◈ Advanced Metrics
⬡ How ThreadScope Works
① Your Java Application
Any JVM-based service — Spring Boot, Disruptor trading engine, microservice, batch processor. ThreadScope attaches to its JVM with zero code changes.
REAL JVM
▼
② ThreadMXBean Collection
java.lang.management.ThreadMXBean.dumpAllThreads() captures every thread's state (RUNNABLE, BLOCKED, WAITING), CPU%, lock names, and stack traces 10× per second.
JDK BUILT-IN
▼
③ LMAX Disruptor Engine
A real RingBuffer[1024] with 3 producer and 3 consumer threads runs inside the agent. This generates genuine contention, real latency measurements, and authentic backpressure — no simulation.
LIVE DATA
▼
④ AI Root Cause Engine
5 diagnostic rules evaluated every 100ms using 30-tick sliding windows. Detects Deadlock, Lock Contention, Consumer Backpressure, CPU Saturation, Memory Pressure. Confidence scores derived from metric signal strength — not random. Rule-based expert system, not an LLM.
AI ENGINE
▼
⑤ WebSocket Stream
Spring Boot broadcasts a JSON snapshot — threads, disruptor metrics, JVM stats, AI diagnosis — to every connected browser at 100ms intervals via the configured WebSocket endpoint.
10 FPS
▼
⑥ Physics Dashboard
Real-time HTML5 Canvas physics simulation maps thread states to particles — RUNNABLE (cyan), BLOCKED (red), WAITING (gold). Every particle represents a real JVM thread. Chaos mode spawns real contention threads and instantly reshapes the visualization.
CANVAS 60FPS
Is This Actually AI?
Yes — it is a rule-based expert system, the same architecture used in production APM tools (Datadog, New Relic, Dynatrace). It applies domain-expert rules to time-series signals with weighted confidence scoring and trend analysis. The difference from a static dashboard: it correlates multiple metrics simultaneously, tracks trends across 3-second windows, and generates a specific root cause + actionable recommendation — not just an alert.
What Problem Does It Solve?
Backend engineers see "high latency" in production but spend hours guessing whether it is lock contention, CPU saturation, GC pressure, or queue backlog. ThreadScope makes the invisible visible in real time and tells you exactly what is wrong and what to fix — in seconds, not hours.
1
Java app has a hidden performance problem
→
2
ThreadScope streams real JVM metrics
→
3
AI engine detects root cause in <3s
→
4
Developer gets exact fix recommendation
→
5
Click ⚡ CHAOS to simulate production load now