Heterogeneous Database Cluster Upgrade Scheduling

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Solution Overview

Problem

Existing technologies lack the capability to coordinate and automate the upgrade process for heterogeneous multi-instance database clusters, leading to difficulties in obtaining best practices, lack of automation, inadequate impact analysis, fear of upgrade failure, significant downtime, and performance degradation.

Innovation Solution

A computer-implemented system that analyzes a multiple database installation to determine candidate upgrade operations and schedules their application, exploiting homogeneity and groupings to parallelize upgrade operations, thereby reducing the intrusiveness of the mass upgrade process.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If upgrade operations are performed on multiple database instances simultaneously, then productivity is improved, but reliability deteriorates due to increased risk of upgrade failure and lack of coordination

Engineering Contradiction:

Improveupgrade speedVSAvoidupgrade success rate

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The patent segments the heterogeneous multi-instance database cluster into homogeneous groups based on version, platform, and configuration characteristics. Each group can be upgraded independently with coordinated scheduling, allowing parallel processing while maintaining reliability through group-level isolation of upgrade operations

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system performs preliminary impact analysis and dependency assessment before initiating upgrade operations. It determines the optimal sequencing order of upgrade operations across different database instances, ensuring that prerequisites are met and dependencies are satisfied before each upgrade operation commences

Inventive Principle:

Principle #10Preliminary action

2Reliability

If upgrade operations are performed sequentially on each database instance, then reliability is improved, but productivity deteriorates due to extended total upgrade time

Engineering Contradiction:

Improveupgrade success rateVSAvoidupgrade speed

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

By dividing the database cluster into homogeneous groups, the system enables parallel upgrade operations within each group while maintaining sequential control across groups. This segmentation allows multiple upgrades to proceed simultaneously without compromising reliability, as each group is managed independently with proper coordination

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The upgrade scheduling system dynamically adjusts the execution plan based on resource availability, dependency constraints, and group homogeneity. It can parallelize operations when conditions permit while maintaining sequential execution when dependencies require it, optimizing both reliability and productivity

Inventive Principle:

Principle #15Dynamics

3Reliability

If comprehensive impact analysis is performed before upgrade, then reliability is improved, but loss of time increases due to extended analysis duration

Engineering Contradiction:

Improveupgrade failure preventionVSAvoidpre-upgrade analysis time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The impact analysis is segmented and performed at the homogeneous group level rather than individually for each database instance. This allows the system to analyze common characteristics and dependencies once per group, significantly reducing total analysis time while maintaining comprehensive coverage of all instances within each group

Inventive Principle:

Principle #1Segmentation

4Adaptability or versatility

If database instances are upgraded to different versions, then adaptability is improved, but device complexity increases due to heterogeneity management

Engineering Contradiction:

Improveversion flexibilityVSAvoidcluster management complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system groups database instances by version, platform, and configuration to create homogeneous groups. Within each group, instances share identical characteristics, simplifying management and upgrade operations. This homogeneity approach allows the system to maintain adaptability across different versions while reducing the complexity of managing heterogeneity at the cluster level

Inventive Principle:

Principle #33Homogeneity

Data Source

PatentUS12204500B2Upgrade of heterogeneous multi-instance database clusters

Publication Date: 2025.01.21 ORACLE INT CORP

AI summary

A method, system, and computer program product for management of large multi-database installations. The method form commences by analyzing a multiple database installation to determine a set of candidate upgrade operations to apply to individual instances of heterogeneous databases in the multiple database installation, and then scheduling an order in which order to apply individual operations from among the set of candidate upgrade operations. In exemplary operation, the candidate upgrade operations comprise database version upgrades, database stack upgrades, and/or database listener upgrades. Some embodiments exploit homogeneity and/or groupings in order to parallelize performance of various upgrade operations during mass upgrade of multi-database installations. In addition to performing upgrade operations in the form of database version upgrades, database stack upgrades, and/or database listener upgrades, the installation can be upgraded by receiving application upgrades.