Multi-Tenant Database Scalability Scores from Performance Metrics
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Solution Overview
Problem
Cloud platforms with multi-tenant database systems face challenges in effectively scaling capabilities under load, leading to performance inefficiencies and errors that are difficult to identify and address on a tenant-by-tenant basis, resulting in inconsistent and biased views of performance health.
Innovation Solution
A system that aggregates performance metrics for individual tenants, calculates scalability scores by comparing these metrics to common thresholds, and provides insights and corrective actions through a user interface, ensuring a consistent and unbiased view of performance health across tenants.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the cloud platform implements highly-customizable solutions for different tenants, then the adaptability and versatility of the platform is improved, but the system fails to effectively scale under load, introducing errors and performance inefficiencies
Solution Approach 1:
The patent segments the monolithic performance analysis approach into tenant-specific analyses. By dividing the multi-tenant system into individual tenant performance profiles, the system can evaluate and optimize each tenant's scalability independently, allowing customized solutions to scale effectively without compromising overall system reliability under load
Solution Approach 2:
The patent changes the parameter of performance evaluation from a single system-wide metric to multiple tenant-specific metrics. By calculating scalability scores for each tenant based on their unique performance characteristics and comparing them against common thresholds, the system maintains adaptability while ensuring reliable scaling behavior across all tenants
2Measurement precision
If the system analyzes performance metrics on a tenant-by-tenant basis, then the measurement precision of performance health is improved, but the device complexity and difficulty of detecting and measuring performance increases
Solution Approach 1:
The patent creates a universal scalability score calculation framework that can be applied to all tenants simultaneously. The same methodology and thresholds are used across the multi-tenant system, allowing precise tenant-specific measurement without proportionally increasing system complexity, as the analysis engine serves multiple tenants with a single unified approach
Solution Approach 2:
The patent applies homogeneous performance thresholds and evaluation criteria across all tenants. By using common scalability thresholds and consistent measurement methodologies for every tenant, the system achieves precise individualized measurement while maintaining operational simplicity through standardized processes
3Productivity
If the platform supports multiple tenants with different solutions, then the productivity and output of the cloud platform is improved, but performance inefficiencies and errors increase under load
Solution Approach 1:
The patent performs preliminary scalability analysis by calculating scalability scores for each tenant before performance degradation occurs. By proactively identifying tenants with suboptimal scalability through threshold comparisons, the system can address performance inefficiencies before they manifest as errors or failures under production load
Solution Approach 2:
The patent implements a feedback mechanism where scalability scores are calculated and compared against thresholds to generate insights about performance health. This feedback loop enables the system to continuously monitor and improve tenant performance, reducing errors and inefficiencies while maintaining high productivity across multiple tenants
Data Source
AI summary
Methods, systems, apparatuses, and computer program products are described. A multi-tenant database system may store a set of data logs indicating performance data for multiple tenants of the system. The system may calculate one or more aggregate performance metrics based on performance data for a tenant stored in the logs, where a performance metric of the one or more aggregate performance metrics may be based on design time data for the tenant, runtime data for the tenant, or both. The system may compare the one or more aggregate performance metrics to one or more performance thresholds defined for multiple tenants and may generate scalability scores corresponding to the one or more aggregate performance metrics for the tenant. The system may send, for display at a user interface of a user device operated by a user associated with the tenant, an indication of the generated scalability scores.