Module 1 · Foundation

Queueing Theory — see the flow

Move the sliders. Watch the queue form, drain, or explode in real time.

The single idea

Arrivals meet capacity. The gap is your queue.

When λ < c·μ the system drains.

ρ < 0.7

Relaxed

Servers idle often.

0.7 ≤ ρ < 0.9

Healthy

Queue forms and clears.

0.9 ≤ ρ < 1.0

Fragile

Small spikes cause large delays.

ρ ≥ 1.0

Unstable

Queue grows without bound.

Interactive

Flow Lab

Tune the sliders.

arrival queued serving dropped
Utilization ρ 0%

Queue length 0

now / max 0

Avg wait 0.0 s

moving average

Throughput 0.00 /s

served items

Dropped 0

capacity overflow

Queue length over time
Queue length vs utilization

What you should see

Six situations, one model

Click each preset above.

Idle

λ ≪ μ.

Steady

ρ ≈ 0.8.

Fragile

ρ ≈ 0.95.

Overload

λ > c·μ.

Bursty

High CV².

Multi-server

Same λ, more servers.

Cross-domain transfer

Same law — different context

After the lab, map the model to your stack.

SW

API queue

Requests wait for workers.

HW

Test stand queue

Boards queue for ICT/FCT.

FW

Event queue

ISR enqueues faster than main loop drains.

FPGA

Backpressure

Pipeline stall when downstream is slow.

Self-check

Did I get it?