Multi-Tenant Database Snapshots for Tenant-Aware Resource Forecasting
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Solution Overview
Problem
Existing multi-tenant server systems face challenges in accurately determining and forecasting resource usage due to the lack of tenant identification in follow-on requests and the inefficiency of relying solely on applications for tracking, leading to inaccurate forecasts and resource wastage.
Innovation Solution
Implementing a system that stores context data from resource requests in a database and takes periodic snapshots to determine resource usage, allowing for more accurate forecasting by identifying tenants and adjusting forecasts based on their intentions and request contexts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If applications are used to track resource usage, then resource tracking can be performed, but processing overhead increases and accuracy decreases due to lack of tenant identification in follow-on requests
Solution Approach 1:
The system performs preliminary action by capturing and storing tenant identification information and request context data in a database before follow-on requests occur. This allows the system to quickly retrieve pre-stored tenant information during resource usage tracking, eliminating the need for complex real-time tenant identification and reducing processing overhead while maintaining accuracy.
2Productivity
If multi-tenant server systems share resources without boundaries, then resource utilization efficiency improves, but accurate attribution of resource usage to individual tenants becomes difficult
Solution Approach 1:
The system introduces a database as an intermediary between resource requests and resource allocation. The database stores and manages tenant identification information and request context data, serving as a mediator that enables accurate tracking and attribution of resource usage to individual tenants while maintaining the shared resource architecture. This intermediary layer preserves resource sharing efficiency while solving the attribution accuracy problem.
3Measurement precision
If periodic snapshots are taken to determine resource usage, then forecasting accuracy improves, but system resource consumption increases
Solution Approach 1:
The system creates periodic snapshots (copies) of the database containing tenant identification information and request context data at specific intervals. These snapshot copies enable accurate resource usage analysis and forecasting without requiring continuous real-time monitoring of the live system, thereby improving forecasting accuracy while minimizing disruption and resource consumption.
Data Source
AI summary
Some implementations of the disclosed systems, apparatus, methods and computer program products may provide for determination of resource usage by tenants in a multi-tenant server system. Tenants may provide resource requests to a database of the multi-tenant server system and such resource requests may include context data. Periodic snapshots of the database may be performed to determine the pending resource requests received by the various tenants and, based on the snapshots and the context data, the resource usage of the various tenants, as well as the system as a whole, may be determined and forecasted for the future.