Throttling
Throttling is the intentional control or limitation of system resources to prevent overuse or congestion, often applied to APIs, network traffic, or application processing. Throttling can regulate the rate of incoming requests, maintain performance stability, and protect resources from being overwhelmed, particularly in systems that serve multiple clients or handle high traffic.
Types of throttling include:
Rate Limiting: Restricting the number of requests a user or client can make to a server in a set timeframe (e.g., 100 requests per minute).
Traffic Shaping: Controlling bandwidth allocation to prioritize specific types of traffic over others, useful in managing network resources for optimal performance.
Data Throttling: Used by internet service providers (ISPs) to limit data usage, often after reaching a predefined threshold, to manage network loads.
Throttling helps ensure fair usage of resources, preventing system slowdowns and service outages. For APIs, it maintains availability by limiting excessive client requests that could exhaust server resources. Many services provide customizable throttling policies, enabling administrators to adjust limits based on user needs and application demands.
How CodeBranch applies Throttling in real projects
The definition above gives you the concept — but knowing what Throttling means is different from knowing when and how to apply it in a production system. At CodeBranch, we have spent 20+ years building custom software across healthcare, fintech, supply chain, proptech, audio, connected devices, and more. Every entry in this glossary reflects how our engineering, architecture, and QA teams actually use these concepts on client projects today.
Our work combines AI-powered agentic development, the Spec-Driven Development (SDD) framework, CI/CD pipelines with agent rules, and production-grade quality gates. Whether you are evaluating a technology for your product, trying to understand a vendor proposal, or simply learning, this glossary is written to give you practical, accurate context — not theoretical abstractions.
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