Dynamic Data Cluster Policy Mapping via Inventory Discovery
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Solution Overview
Problem
Existing data protection systems face challenges in efficiently managing data protection services for dynamic data clusters with changing components, as they struggle to map and apply protection policies to newly deployed or removed components in a timely and accurate manner.
Innovation Solution
A method and system that utilize a mapping module within a data protection manager to identify discovery events, request and obtain inventory information, determine changes in data cluster components, map protection policies to newly deployed components, and update the inventory repository, thereby initiating data protection services based on these mappings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data protection systems use static policy mapping for data clusters, then policy application is simple and reliable, but the system cannot respond to dynamic changes in cluster components
Solution Approach 1:
The system performs preliminary actions by continuously monitoring for discovery events and proactively requesting inventory information before policy mapping is needed. The mapping module maintains a repository of component protection policies and pre-establishes the framework for automatic policy assignment, so when changes occur, the system can quickly apply appropriate policies without complex real-time analysis.
Solution Approach 2:
The system implements feedback mechanisms where the mapping module receives discovery events about cluster changes, requests updated inventory information from data cluster managers, compares current inventory with stored information, and automatically updates protection policy mappings. This continuous feedback loop ensures policies are dynamically adjusted in response to cluster component changes while maintaining a structured, manageable process.
2Measurement precision
If the system continuously monitors and updates data cluster component inventory, then protection policies are accurately applied to new components, but system response time and processing overhead increase
Solution Approach 1:
The system uses periodic action by monitoring for discovery events and requesting inventory information at scheduled intervals or when changes are detected, rather than maintaining constant continuous monitoring. The mapping module requests inventory information periodically from data cluster managers and compares it with stored information to identify changes, which balances accurate detection with reduced processing overhead and response time.
3Productivity
If data protection services are manually configured for each cluster component, then policy customization is precise, but operational efficiency and scalability are reduced
Solution Approach 1:
The system implements self-service by enabling the mapping module to automatically request inventory information, detect component changes, compare inventory data, and assign protection policies without manual intervention. The data cluster managers automatically provide inventory information in response to discovery events, and the system automatically initiates protection services based on detected changes, eliminating manual configuration while maintaining precise policy application through automated logic.
Data Source
AI summary
Techniques described herein relate to a method for managing data protection services for data clusters. The method includes identifying a discovery event associated with a data cluster; sending a request for currently deployed data cluster components to a data cluster manager associated with the data cluster; obtaining data cluster component inventory information associated with the data cluster from the data cluster manager; making a first determination that the currently deployed data cluster components comprise changed data cluster components using the data cluster component inventory information; mapping protection policy types to newly deployed data cluster components of the data cluster using the data cluster component inventory information and component data protection information; updating a data cluster component inventory repository using the data cluster component inventory information; and initiating performance of data protection services for the newly deployed data cluster components based on the mapped protection policy types.