Multi-Instance Data Synchronization for Unified Resource Visibility
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Solution Overview
Problem
Users of remote network management platforms face challenges in easily viewing and managing computing resources across multiple computational instances, leading to wasted resources and unnecessary login overhead due to separate access and authentication requirements.
Innovation Solution
A multi-instance framework (MIF) enables data sharing and automatic synchronization across computational instances using mutual transport layer security (mTLS) and public key infrastructure (PKI) authentication, allowing for centralized data management and reduced login overhead.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If users remotely access each computational instance separately to query computing resource allocation, then they can obtain detailed information about each instance, but it results in wasted time and computational overhead due to multiple logins and separate queries
Solution Approach 1:
The patent merges multiple computational instances into a single unified view accessible through one login. The system combines resource allocation data from multiple instances and presents it through a consolidated interface, eliminating the need for users to separately access each instance while maintaining complete visibility of computing resources across all instances.
2Adaptability or versatility
If computing resources are allocated to multiple computational instances, then users can run different workloads (production, testing, development), but it leads to wasted computing resources due to out of date allocations and lack of visibility
Solution Approach 1:
The patent implements a feedback mechanism that continuously monitors computing resource allocation and usage across multiple instances. The system provides real-time or near-real-time visibility into resource utilization, enabling dynamic adjustment of allocations based on actual usage patterns. This feedback loop prevents both over-provisioning (wasted resources) and under-provisioning (insufficient resources), optimizing resource distribution across production, testing, and development instances.
3Ease of operation
If users remotely access each computational instance separately, then they can manage each instance independently, but it creates unnecessary login overhead and authentication requirements for each instance
Solution Approach 1:
The patent creates a universal access interface that serves multiple functions simultaneously. A single authentication mechanism provides access to multiple computational instances, and a unified dashboard performs multiple query functions (CPU usage, memory allocation, storage, etc.) across all instances. This multi-functional approach maintains independent instance management capabilities while eliminating repetitive authentication processes.
Data Source
AI summary
An example embodiment may involve receiving, by a central instance, a data synchronization pull request from a computational instance, wherein the central instance stores data shared by one or more other computational instances related to the computational instance; based on the data synchronization pull request, determining portions of the data to be shared with the computational instance; validating that the computational instance is permitted access to the portions of the data; and transmitting, by the central instance and in response to the data synchronization pull request, the portions of the data to the computational instance.