Cryptographic Key Caching with LRU Eviction for Low-Latency API Access
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Solution Overview
Problem
Existing systems for managing cryptographic keys in AWS KMS result in high latency and cost due to frequent network calls for key retrieval, as the same API requests the same key multiple times.
Innovation Solution
A computing system that caches cryptographic keys in a writable storage location with a predetermined maximum capacity, allowing for efficient retrieval and reuse of keys from a serverless computing platform, reducing the need for repeated network calls.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cryptographic keys are retrieved from AWS KMS through network calls for each API request, then key security is maintained through centralized management, but system latency increases and operational costs rise due to repeated network calls
Solution Approach 1:
The system performs preliminary action by retrieving and caching cryptographic keys before they are actually needed for API operations. The cache stores keys locally so that when API requests arrive, the keys are already available in the cache, eliminating the need for time-consuming network calls to AWS KMS at the moment of need.
Solution Approach 2:
The cache acts as an intermediary between the API and AWS KMS. Instead of direct communication between the API and the key management service for every request, the cache mediates by holding local copies of keys, reducing the frequency and impact of network calls while maintaining security through controlled access mechanisms.
2Reliability
If cryptographic keys are retrieved from AWS KMS for every API request, then key access control is enforced through the key management service, but operational costs increase due to the number of network calls
Solution Approach 1:
The system performs preliminary action by retrieving and caching cryptographic keys before they are actually needed for API operations. The cache stores keys locally so that when API requests arrive, the keys are already available in the cache, eliminating the need for time-consuming network calls to AWS KMS at the moment of need.
Solution Approach 2:
The system creates copies of cryptographic keys and stores them in the local cache. These copies allow multiple API requests to be served without requiring repeated access to the original key source in AWS KMS, significantly reducing the number of network calls and associated costs while maintaining security through controlled access to the cached copies.
3Speed
If cryptographic keys are cached in a writable storage location with predetermined maximum capacity, then key access speed improves, but cache management complexity increases
Solution Approach 1:
The system changes the parameter of storage capacity by implementing a cache with a predetermined maximum capacity. This parameter change enables faster key access by keeping frequently used keys in a limited-size local cache, while the defined capacity constraint simplifies management by automatically determining when to evict older keys using LRU (Least Recently Used) policies.
Solution Approach 2:
The cache implementation dynamically adapts to usage patterns by implementing LRU eviction policies that automatically adjust which keys to retain or evict based on recent access patterns. This dynamic behavior optimizes key access speed without requiring manual intervention, as the cache automatically reorganizes itself based on actual usage rather than static pre-configuration.
Data Source
AI summary
Systems and methods for cryptographic key storage management whereby the system receives a first request to access a first API and communicatively connects a channel to a key management service (KMS) that is on a serverless computing platform. After receiving a cryptographic key from the KMS, the system attaches the cryptographic key to the first API, thereby creating a first data structure. The system stores the first data structure to a writable storage location that has a predetermined maximum capacity for data structures. The system receives a second request to access the first API and retrieves and uses the stored first data structure to grant access to the first API. The system also determines when the writable storage location has reached the predetermined capacity and determines and evicts a least recently used data structure stored to the writable storage location.