Cloud API Caching Flow for Low-Latency Data Retrieval
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Solution Overview
Problem
Conventional techniques for retrieving data objects in cloud computing environments are inefficient in handling numerous data retrieval operations, leading to high latencies due to the reliance on synchronous calls in serial manner.
Innovation Solution
Implementing a system that leverages asynchronous and synchronous application program interfaces (APIs) in tandem with a process flow, using an asynchronous controller to pre-fetch and cache data objects, and a synchronous controller to retrieve specific data objects when necessary, thereby reducing latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If synchronous calls are used to retrieve data objects in a serial manner, then data retrieval operations can be performed reliably, but user latency increases significantly
Solution Approach 1:
The system performs preliminary actions by pre-fetching data objects using asynchronous calls before they are actually needed. The asynchronous controller proactively retrieves data in advance and stores it in a cache, so when synchronous requests arrive, the data is already available, eliminating waiting time while maintaining reliability.
Solution Approach 2:
An intermediary caching layer is introduced between the data source and the synchronous requests. The cache acts as a mediator that stores pre-fetched data objects, allowing synchronous calls to retrieve data quickly from the cache rather than performing slow serial operations, thus reducing latency while maintaining data accuracy.
2Loss of time
If asynchronous calls are used to pre-fetch and cache data objects, then user latency is reduced, but system complexity increases
Solution Approach 1:
The system segments the data retrieval functionality into distinct components: an asynchronous controller for pre-fetching operations, a cache for storage, and a synchronous controller for on-demand retrieval. This segmentation allows each component to specialize in its function, managing complexity through modular design while achieving low latency.
Solution Approach 2:
The cache serves multiple functions: it stores pre-fetched data for quick retrieval, acts as a buffer between asynchronous and synchronous operations, and provides a unified interface for both types of calls. This multi-functionality reduces overall system complexity by consolidating operations into a single intermediary structure.
3Speed
If data is pre-fetched and cached in advance, then data retrieval speed improves, but storage requirements increase
Solution Approach 1:
The system applies partial pre-fetching by caching only the data objects that are likely to be needed soon, rather than caching all possible data. The asynchronous controller intelligently selects which data to pre-fetch based on usage patterns, achieving fast retrieval for critical data while limiting cache storage requirements.
Data Source
AI summary
Systems, methods, and devices are disclosed herein that provide management of usage of application program interfaces. A computing platform may include one or more processors configurable to cause detecting a first action comprising an event at a user interface associated with an on-demand application hosted by the computing platform, and making an asynchronous call for one or more data records in response to detecting the first action, the asynchronous call being made to a storage location of the computing platform. The computing platform may also cause detecting a second action associated with the on-demand application, determining whether a synchronous call should be performed, the synchronous call being made in response to determining that a cache does not include the one or more data records, and generating a result responsive to the second action.