Cloud Document Backup via Object Storage Bitmask
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Solution Overview
Problem
Cloud-based document backup solutions for applications like Microsoft Office365 face challenges in achieving cost and performance efficiency, particularly due to the higher costs associated with compute resources compared to storage resources, and existing methods are complex and resource-intensive.
Innovation Solution
A cost-efficient document backup model that utilizes object storage, minimizing compute resources by employing a data model with metadata databases and data structures like Backup Records, Container Records, and Document Records to manage document backups and restores efficiently, leveraging object storage's tiering mechanisms to reduce costs and simplify operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cloud-based compute resources are used for document backup, then backup functionality is provided, but compute costs increase significantly
Solution Approach 1:
The patent extracts the backup functionality from compute-intensive operations and relocates it to object storage operations. By using object storage's native capabilities for versioning and retention policies, the system eliminates the need for complex compute-based backup processes, thereby reducing compute costs while maintaining backup protection.
Solution Approach 2:
The system enables object storage to perform backup functions autonomously through its inherent versioning and lifecycle management capabilities. The storage system self-manages document versions, retention periods, and restoration operations without requiring external compute resources, thus reducing compute cost while ensuring reliable backup protection.
2Reliability
If traditional backup methods are used for cloud documents, then data protection is achieved, but solution complexity increases
Solution Approach 1:
The patent merges data protection functionality directly into the object storage system itself. By combining storage and backup protection into a single integrated solution with unified versioning and retention policies, the system eliminates the need for separate backup infrastructure and complex data management layers, thereby reducing solution complexity while maintaining robust data protection.
3Use of energy by moving object
If cloud storage resources are used instead of compute resources, then cost efficiency improves, but backup performance may be reduced
Solution Approach 1:
The patent changes the operational parameters from compute-intensive to storage-optimized operations. By leveraging object storage's high throughput and parallel access capabilities, the system achieves efficient backup performance using storage resources rather than compute resources, thereby improving cost efficiency without sacrificing backup productivity.
Data Source
AI summary
Storing documents in an object store in the cloud by creating a container for the documents, defining a document record including unique document ID and an index. A backup record for every backup includes a timestamp for each backup, and a bitmask for each document in the container has a single bit position for each document to indicate the corresponding document as unchanged or that it has been changed/deleted. Each bit location in the bitmask is referenced by the index in the document record. Large documents have a multi-part record identifying the containers. During point-in-time recovery, containers that match a given timestamp are found, and documents where the bitmask bit is set are restored.