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Simulation

Adaptive Simulation Platform

Stress-test system behavior under configurable load, latency, and failure conditions before production.

A real-time simulation environment for modeling distributed topologies, applying control policies, and observing emergent system behavior under pressure.

D3.jsSimulation EngineTypeScriptReact
Overview

Problem Space

Production environments are too costly and fragile for exploratory testing. Teams cannot safely model burst traffic, partial outages, or the cascading effects of policy changes without risking real services.

Solution

System Design

A real-time simulation environment with configurable topology, pluggable control policies, and live metric visualization. Teams stress-test system behavior under varying load, latency, and failure conditions.

Architecture

System Components

Simulation Engine
discrete-time tick loop with seeded RNG
Topology Model
services, queues, workers, dependencies
Policy Module
autoscale, load shedding, retry strategies
Metrics Collector
RPS, queue depth, latency, error sampling
Scenario API
preset configurations for common patterns
Comparison Engine
A/B policy overlay with differential metrics
Interactive Demo

Live Prototype

Loading prototype...

Interactive prototype — all data generated client-side with deterministic seeds.

Benchmark

Reference Performance

Reference benchmark: Ingress, Queue, Worker Pool, Dependency topology. Burst traffic scenario (120 to 900 RPS at t=30s). Measured recovery time and saturation under different control policies.

Throughput (evt/s): minimum 120.0, maximum 900.0, average 452.9
P95 Latency (ms): minimum 90.0, maximum 800.0, average 294.3
Error Rate: minimum 0.0, maximum 0.1, average 0.0

Deterministic seed · 60s window · Simulated workload · Local environment

Technology

Implementation Details

D3.jsSimulation EngineTypeScriptReact
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