Database Rules Engine for RAS and SLA Configuration Reviews

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Solution Overview

Problem

Customers lack the necessary software system engineering expertise to optimize database performance in public clouds, leading to difficulties in predicting configuration performance, ensuring reliability, availability, and serviceability (RAS), and compliance with best practices, which hinders cloud adoption.

Innovation Solution

Novel performance optimization rules that analyze database configurations and generate improved configurations by assessing service level agreements, detecting needed architecture options, and recommending adjustments to achieve recovery time and recovery point objectives, using interactive questionnaires and diagnostic reports to predict and improve RAS performance.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If customers configure database settings in public cloud, then database performance optimization is attempted, but lack of software system engineering expertise prevents achieving optimal performance and RAS compliance

Engineering Contradiction:

Improvedatabase RAS complianceVSAvoidconfiguration complexity

Core Design Contradiction:

ReliabilityVSEase of operation

Solution Approach 1:

The system performs self-diagnosis by automatically analyzing current database configuration settings against best practices and RAS requirements, generating compliance reports without requiring customer expertise in software system engineering

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

An automated rules engine acts as an intermediary between customer configuration choices and RAS compliance requirements, evaluating configurations and providing guidance to bridge the knowledge gap

Inventive Principle:

Principle #24Intermediary (Mediator)

2Measurement precision

If customers test database configurations in laboratory, then configuration performance prediction is attempted, but inability to recreate similar workload makes prediction difficult or impossible

Engineering Contradiction:

Improveperformance prediction accuracyVSAvoidtesting infrastructure complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system replaces physical laboratory testing infrastructure with automated rules-based evaluation that analyzes configuration settings directly, eliminating the need for complex test environments and workload recreation

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system performs preliminary evaluation of configuration settings before production deployment by checking against predefined rules and best practices, preventing performance issues before they occur in production

Inventive Principle:

Principle #10Preliminary action

3Difficulty of detecting and measuring

If state of the art cloud diagnostics are used, then database configuration issues are detected, but diagnostics are inconsistent, cryptic, or incomplete and require infrastructure expertise to interpret

Engineering Contradiction:

Improvediagnostic interpretation difficultyVSAvoiddiagnostic information completeness

Core Design Contradiction:

Difficulty of detecting and measuringVSLoss of information

Solution Approach 1:

The system provides structured feedback by generating comprehensive compliance reports that clearly indicate which configuration settings comply with RAS requirements and which do not, eliminating cryptic diagnostic output

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The diagnostic system segments analysis into distinct compliance categories (reliability, availability, serviceability) with specific rules for each, making diagnostic information organized, complete, and easy to interpret

Inventive Principle:

Principle #1Segmentation

4Reliability

If customers manually ensure best practices compliance, then RAS compliance may be achieved, but compliance verification and guidance are not provided in state of the art public cloud

Engineering Contradiction:

Improvebest practices complianceVSAvoidcompliance verification automation

Core Design Contradiction:

ReliabilityVSExtent of automation

Solution Approach 1:

The system automatically verifies compliance by evaluating configuration settings against predefined rules and best practices, eliminating the need for manual verification expertise

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

An automated rules engine serves as an intermediary that objectively evaluates compliance without requiring customer expertise, providing authoritative verification of best practices adherence

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS20260064659A1Rules engine for automatic MAA reviews

Publication Date: 2026.03.05 ORACLE INT CORP

AI summary

For reliability, availability, and serviceability (RAS) of a database, here are novel performance optimization rules that generate a configuration of a new database or an improved configuration of an existing database. These rules perform a service level agreement (SLA) assessment to detect which database architecture options are needed. The rules recommend improvements to the database's current architecture so that recovery time objectives (RTO) and recovery point objectives (RPO) can be achieved by non-expert technicians. The rules analyze database diagnostics from health monitoring, diagnostic logs, persistent and network storage statistics, database performance statistics, and operating system (OS) statistics. The rules may analyze a database configuration that contains an interactively completed questionnaire or a diagnostic report generated by database infrastructure. The rules can be used speculatively to predict the RAS performance characteristics of an unimplemented configuration or used remedially to generate suggestions for improving RAS performance of a deployed configuration.