Define limits by tenant, operation, cost or dependency capacity.
Throttling
Measure consumption and delay, reject or degrade requests that exceed defined limits. Good throttling communicates limits clearly and protects both shared capacity and important workloads.
How can a system keep legitimate demand within the capacity and fairness limits of a shared resource?GateSift summary based on Microsoft Azure Architecture Center guidance. The wording, visualization, Azure mapping and analyzer context are original GateSift material.
How Throttling works
Requests are measured against capacity or fairness limits before they consume a constrained resource.
Allow, delay, queue or reject work when the configured limit is reached.
Return clear retry guidance and monitor whether limits protect the system without blocking valid traffic.
What this pattern helps you decide
Measure consumption and delay, reject or degrade requests that exceed defined limits. Good throttling communicates limits clearly and protects both shared capacity and important workloads.
Where you may see it
- APIM rate-limit and quota policies
- Service Bus or Event Hubs producer pacing
- Application-level tenant and operation limits
How the analyzers can surface it
- APIM APIs without rate limiting or quota controls
- Shared integrations with no tenant or consumer isolation
- HTTP 429 handling and retry-after behavior
Pattern detection is contextual. GateSift should present these as architectural signals, not claim a pattern is implemented solely because one policy statement or adapter exists.
This page links to Microsoft Azure Architecture Center for the source architecture guidance. GateSift summaries, diagrams, Azure examples and analyzer signals are original. No endorsement by Microsoft is implied.