Parallel Reliability Simulator — Independent Redundant Branches Interactive

Interactive 3D reliability laboratory: two redundant server nodes in parallel; fail either branch and compare at-least-one survival with a single node.

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About the Parallel Reliability Simulator

This simulator places two independent server nodes in parallel, each able to carry the full service demand, in front of a single service terminal. You choose the mission duration and failure rate, fail either node by hand, and watch the routing and the survival probability respond.

What the simulator shows

• A 3D server A rack, server B rack, independent service paths and a service terminal. • Sliders for mission duration (100-3000 h) and component failure rate (0.05-2 per 1000 h), two fault switches (server A, server B) and a motion-marker toggle. • Five live readouts: individual mission survival, at-least-one survival, system failure probability, live healthy branches and whether live service is available. • Two presets: Lose A (B continues to serve the terminal) and Lose both (service stops).

Why parallel paths help

Each branch survives with Ri = exp(-lambda T). Service is lost only when both fail, so R_parallel = 1 - (1 - R1)(1 - R2). If each branch has a 0.9 survival probability, the pair gives 1 - 0.1 x 0.1 = 0.99. Adding a second independent, full-capacity branch therefore cuts the unreliability by multiplying the two unreliabilities together.

Model limits and the role of independence

Two active, independent, full-capacity branches are assumed with perfect routing. This is mission reliability, not repairable availability, and the manual faults are illustrative states. Shared-cause and routing failures are excluded, which is exactly why the result is optimistic when real branches share power, cooling or software. The Common-Mode Failure lab shows how a shared cause defeats that assumption.

Frequently asked questions

What does parallel success require?

At least one healthy full-capacity branch. Either independent branch is sufficient to keep the terminal served.

How is parallel reliability calculated?

R_parallel = 1 - (1 - R1)(1 - R2): multiply the two unreliabilities and subtract from 1. With exponential branches each R is exp(-lambda T).

Why is independence important?

The formula assumes the branches fail separately. A shared cause, such as common power or routing, can defeat both at once and make the real reliability lower than this calculation.

What does this simulator not model?

It excludes repair, routing failures and shared-cause failures, and it assumes each branch can carry the full load alone.

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