Local Cache Rate-Limiting for Asynchronous Decision Nodes
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Solution Overview
Problem
Existing rate-limiting systems face inefficiencies and reliability issues due to remote server dependencies for configuration data, leading to high latency and potential failures in decision-making processes.
Innovation Solution
Implementing a system that uses local cache storage for rate-limiting configuration data, allowing for asynchronous updates and decoupling of decision-making from synchronization processes, enabling asynchronous, context-aware, and cost-aware rate-limiting techniques to improve efficiency and reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If remote server dependencies are used for configuration data, then centralized control is maintained, but latency increases and system reliability decreases
Solution Approach 1:
The patent segments the rate-limiting system into distributed decision nodes that operate independently with local cache storage, separating the configuration data retrieval from the decision-making process. This allows each node to make rate-limiting decisions locally without waiting for remote server responses, thereby reducing latency while maintaining centralized policy updates through asynchronous synchronization.
Solution Approach 2:
The patent implements preliminary action by pre-loading rate-limiting configuration policies into local cache storage at decision nodes before they are needed for actual rate-limiting decisions. This advance preparation ensures that when rate-limiting decisions must be made, the necessary configuration data is already available locally, eliminating retrieval latency and ensuring system availability even during remote server failures.
2Productivity
If synchronous rate-limiting is used, then configuration consistency is maintained, but system responsiveness and throughput decrease
Solution Approach 1:
The patent applies dynamics by transitioning from synchronous to asynchronous rate-limiting, allowing the system to adapt its behavior based on operational needs. Decision nodes can dynamically make rate-limiting decisions using locally cached policies without waiting for centralized confirmation, while policy updates are propagated asynchronously when changes occur, optimizing both responsiveness and resource utilization.
Solution Approach 2:
The patent implements feedback mechanisms where decision nodes periodically synchronize their local cache with the centralized policy server and report their operational status. This feedback loop ensures configuration consistency is maintained over time while allowing asynchronous operation during intervals between synchronizations, balancing consistency requirements with system responsiveness.
Data Source
AI summary
Systems and methods provide techniques for dynamic rate-limiting, such as techniques that utilize one or more of asynchronous rate-limiting, context-aware rate-limiting, and cost-aware rate-limiting. In one example, a method for asynchronous rate-limiting includes the steps of receiving a rate-limiting request for a service application; extracting one or more policy-defining parameters from the rate-limiting request; querying a local cache storage medium associated with the rate-limit decision node to identify one or more local rate-limiting policies associated with the rate-limiting request; determining, based on the one or more policy-defining parameters and the one or more local rate-limiting policies, a rate-limiting decision for the rate-limiting request; and transmitting the rate-limiting decision to the service application in response to the rate-limiting request.