Storage Classifier for Automated Backup Target Recommendations
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Solution Overview
Problem
Current backup software lacks the intelligence to automatically classify files and assign the appropriate storage medium across multiple storage environments within a user's entire infrastructure, limiting optimal storage choices and incurring high costs due to manual optimization and inability to manage storage growth effectively.
Innovation Solution
A storage classifier system that works in conjunction with a data classifier and data labeling process to automatically classify each file and recommend the most efficient storage medium, considering factors like cost, performance, and capacity, across various storage targets, including on-premise and cloud storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual optimization of storage targets is performed on a per-file basis, then storage allocation precision is improved, but labor cost and time consumption increase significantly
Solution Approach 1:
The system enables self-service through automated storage target selection. The backup software independently classifies files and selects appropriate storage targets without human intervention, using algorithms that evaluate file properties, storage characteristics, and policy requirements to make autonomous decisions
Solution Approach 2:
The patent replaces the mechanical manual process with an automated computational system. Instead of human administrators manually evaluating and assigning storage targets, the system uses automated classification algorithms and policy engines to perform the same function with greater speed and consistency
2Adaptability or versatility
If multiple storage media types are used across the infrastructure, then storage versatility is improved, but system complexity increases
Solution Approach 1:
The patent implements a universal storage classification framework that works across multiple storage media types (disk, tape, cloud, object storage). The same classification engine and policy mechanisms handle diverse storage targets, providing a unified approach that manages complexity while supporting versatility
Solution Approach 2:
The system introduces an intermediary classification layer between the backup software and diverse storage targets. This intermediary component translates various storage media characteristics into a standardized classification scheme, simplifying the interface between heterogeneous storage systems
3Speed
If storage targets are selected based on performance requirements, then access speed is improved, but storage cost increases
Solution Approach 1:
The patent applies local quality by matching specific file characteristics with appropriate storage media properties. Instead of uniformly using high-performance storage for all data, the system classifies files based on their specific requirements (access frequency, size, criticality) and assigns them to storage targets with locally optimized characteristics, ensuring high performance only where needed
Solution Approach 2:
The system dynamically changes storage allocation parameters based on file classification results. By adjusting which storage targets are selected for different file types and access patterns, the system optimizes the balance between performance and cost, allocating premium storage resources only to files that require them
Data Source
AI summary
Embodiments for a storage classifier that provides recommendations to a backup server for storage targets among a plurality of disparate target storage types. The storage classifier receives metadata (name, type, size), and the Service Level Agreement with information such as: retention time, Recovery Point Objective, and Recovery Time Objective) from the backup software. The backup software itself receives policy recommendations from a data label rules engine based on certain file attributes. The storage classifier receives an initial recommendation for the storage type and location (e.g., on-premises deduplication storage or public-cloud object storage, etc.) from a data classifier. Based on these inputs, the storage classifier provides recommended specific storage targets to the backup software on a file-by-file basis for data stored in a backup operation.