Non-disruptive Application Replication Configuration Transition
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Solution Overview
Problem
Transitioning a computing environment from one configuration to another in a networked environment, such as a cloud computing environment, is challenging due to unknown impacts on production systems and obsolete backup recovery points, making it difficult to define a restoration workflow.
Innovation Solution
A method is provided for non-disruptive transitioning of application replication configurations using a common integration model (CIM)-compatible representation of a system replication plan, which creates a hierarchical tree data structure to classify and analyze configuration updates, determining if nodes are isomorphic and modifying the replication plan accordingly for implementation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a system configuration is revised, then the replication plan can be updated to reflect new requirements, but backup recovery points taken over a given period of time become obsolete and difficult to restore
Solution Approach 1:
The system performs preliminary analysis of the replication plan before implementing changes. It identifies all affected recovery points and their relationships to the current configuration, allowing the system to proactively determine which recovery points will become obsolete and plan the transition accordingly, preventing restoration issues before they occur.
Solution Approach 2:
The system continuously monitors the replication plan and configuration state, providing feedback about the impact of proposed changes. It analyzes the relationship between configuration updates and existing recovery points, allowing administrators to see the consequences of changes before implementing them, thus maintaining reliability while enabling updates.
2Adaptability or versatility
If a new configuration is implemented, then the system can adapt to new requirements, but the impact on the production computing system remains unknown and difficult to ascertain
Solution Approach 1:
The system performs preliminary impact analysis by analyzing the replication plan structure and identifying all nodes and recovery points that would be affected by a configuration change. It pre-calculates the impact scope, allowing administrators to understand potential consequences before implementing changes, thus reducing the difficulty of detecting and measuring impacts.
Solution Approach 2:
The system segments the replication plan into discrete nodes and recovery points, allowing impact analysis to be performed on individual components. This segmentation enables precise identification of which specific recovery points and system components are affected by a configuration change, making impact detection and measurement more manageable and accurate.
3Productivity
If configuration updates are applied without analysis, then the transition process is faster, but errors in the replication plan may go undetected
Solution Approach 1:
The system performs preliminary validation and analysis of the replication plan before applying configuration updates. It checks for errors, inconsistencies, and potential issues in advance, allowing the system to correct problems before they cause failures during transition. This preliminary action maintains high transition speed while ensuring replication plan correctness through automated validation.
Data Source
AI summary
Embodiments of the present invention provide an approach for providing non-disruptive transitioning of application replication configurations and proactive analysis of possible error scenarios. Specifically, under embodiments of the present invention, a common integration model (CIM)-compatible representation of a system replication plan is provided in a computer data structure. Based on the representation, a hierarchical tree data structure having a set of nodes is created. A set of system configuration updates pertaining to the set of nodes are then classified (e.g., based upon the type of configuration update). Once the set of nodes has been classified, the set of nodes may then be analyzed to determine if any nodes of the set are isomorphic. If so, the plan can be modified accordingly. In any event, the replication plan (or modified replication plan) may then be implemented.