Protocol
Give shared capacity a noisy-neighbor rule
First-come-first-served can become whoever-spams-most-wins.
When it fits
- One user, project or automated agent can consume most of a shared resource and starve normal workloads.
When to avoid it
- Fair does not always mean equal; critical workloads may legitimately receive more capacity.
Why it matters
Define per-tenant, per-project or per-workload quotas and priority rules before contention becomes political. Allow justified bursts within a bounded policy, then throttle the source creating excess load while preserving service for workloads within normal usage.
Steps
- One workload can exceed its planned rate without causing unrelated compliant workloads to become unavailable.
An example
Cap background content-generation agents so they cannot consume every API slot needed for interactive user tasks.
Check your result
One workload can exceed its planned rate without causing unrelated compliant workloads to become unavailable.
Keep this limit in mind
- Fair does not always mean equal; critical workloads may legitimately receive more capacity.
Evidence and sources
Supports
AWS's 2026 fairness guidance uses throttling, quotas and backpressure to prevent one workload from starving others in a shared system.
Fairness policy must reflect actual priorities rather than equalizing workloads that have different importance.
Fairness in multi-tenant systems · Admission control and fairness