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Keep useful work flowing when demand exceeds capacity

Apply queue, capacity, fairness and overload-control ideas to software, agent fleets and operational workflows so backlog, retries and one noisy workload do not turn pressure into collapse.

12 elements · Explore in any order.

5 principles · 7 protocols

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12 elements

Protocol

Find the breaking point before production finds it for you

Capacity is a fact you discover by pressure, not a number you inherit from last year's diagram.

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Principle

Keep headroom for variability and recovery

Slack looks inefficient until the first spike, outage or slow task arrives.

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Protocol

Give queued work an expiry condition

A queue can preserve work long enough to make it useless.

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Protocol

Move poison work out of the main queue

One bad item should not get infinite turns at the front of the line.

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Principle

Push back on intake before the backlog becomes the outage

A growing queue is a message from capacity, not a storage success story.

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Protocol

Isolate concurrency for the slow dependency

A slow neighbor should not be allowed to rent the whole building.

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Protocol

Give shared capacity a noisy-neighbor rule

First-come-first-served can become whoever-spams-most-wins.

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Principle

Fail work that cannot meet its useful deadline

Late work can consume real resources while producing zero useful result.

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Protocol

Open the circuit when a dependency keeps failing

Sometimes the kindest request to a failing service is the one you do not send.

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Protocol

Define the cheaper mode that preserves the core function

Degraded and useful beats complete and unavailable.

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Principle

Let reliability data slow feature velocity when the budget is spent

Reliability work needs permission to outrank new features before the next outage makes the choice for you.

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Principle

Use queueing only when delayed work remains valuable

A queue stores pressure; it does not create capacity.

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