Cloud Node Data Synchronization via Local Caching and API Updates
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Solution Overview
Problem
In cloud systems, synchronizing data across multiple instances of an application is challenging, particularly for real-time and cached data, as existing methods may not efficiently manage updates without relying on costly database calls, and not all middleware components support data synchronization.
Innovation Solution
A method and system where each node in a cloud cluster registers its information during application initialization, stores updates in both local storage and the database, generates a modified request with updated data details, and uses an API to synchronize updates across nodes, thereby avoiding costly database calls for cached data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is fetched from database for every access, then data is always real-time, but system performance deteriorates due to costly database calls
Solution Approach 1:
The patent implements preliminary action by caching data locally on application nodes before it is actually needed. During application initialization or beforehand, data is fetched from the database and stored in local cache storage, so that subsequent accesses can use the cached data without requiring database calls, thus improving performance while maintaining data availability.
Solution Approach 2:
The patent applies local quality by implementing distributed caching where each application node maintains its own local cache storage. This allows each node to have fast access to cached data locally without requiring centralized database access for every operation, improving system performance while the database remains the source of truth for data accuracy.
2Productivity
If data is cached locally across multiple instances, then system performance improves, but data synchronization becomes challenging
Solution Approach 1:
The patent implements feedback mechanisms to monitor and detect data changes across distributed cache storages. When data is updated in the database or in one node's cache, the system detects this change and propagates the update to other nodes' caches, ensuring all instances have synchronized data while maintaining local caching benefits.
Solution Approach 2:
The patent introduces an intermediary synchronization mechanism that acts as a mediator between the database and distributed cache storages. This intermediary layer handles the coordination of data updates across multiple nodes, ensuring that when data changes occur, all cache instances are updated consistently without requiring direct peer-to-peer communication between nodes.
3Reliability
If middleware components are used for synchronization, then data can be synchronized across instances, but not all middleware support this functionality
Solution Approach 1:
The patent implements a universal synchronization approach that does not depend on specific middleware components. The synchronization mechanism is built into the application architecture itself, using standard protocols and methods that can work across different platforms and environments, making the solution adaptable and compatible with various middleware or no middleware at all.
Solution Approach 2:
The patent enables self-service synchronization where each application node autonomously participates in the synchronization process. Nodes independently detect changes, generate update requests, and propagate data to other nodes without requiring external middleware coordination, making the system adaptable to environments with or without middleware support.
4Reliability
If real-time data is always fetched from database, then data is always up-to-date, but database access dependency increases
Solution Approach 1:
The patent applies preliminary action by pre-fetching and caching data before it is actually needed for operations. Data is loaded into local cache storages in advance during application initialization or based on prediction, reducing the frequency of database calls while maintaining data freshness for cached items.
Solution Approach 2:
The patent implements periodic action by establishing scheduled data synchronization cycles where cached data is refreshed from the database at regular intervals or based on change events. This periodic update mechanism ensures data remains fresh and up-to-date without requiring continuous database connectivity or real-time access for every operation.
Data Source
AI summary
A method and system are provided for data synchronization. The method includes registering, in a database accessible by nodes in a cloud cluster system, node information for each node during an initialization of an application context for an application having at least one instance running on each node. The method further includes storing an update for data in (i) a local storage of a given one of the nodes and (ii) the database, responsive to a request to update the data received by the given one of the nodes. The method also includes generating a modified request that includes details for the updated data. The method additionally includes calling an application programming interface to update a state of respective local storages for the other nodes with the update responsive to the modified request, such that the update is synchronized across the at least one instance running on each node.