Backup Data Storage Tiering via Reference Count Migration
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Solution Overview
Problem
Backup management systems face inefficiencies in data storage and retrieval due to varying retention and restoration policies across different organizations and within an organization, leading to high storage costs and latency issues.
Innovation Solution
Implementing a tiered data storage system with warm and cold tiers, where data blocks are migrated based on reference counts and retention periods, allowing for deduplication and cost-effective storage by grouping similar data blocks as units for transfer to a cold-tier data store.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If all backup data is stored in a single high-performance storage tier, then data retrieval speed is improved, but storage costs increase significantly
Solution Approach 1:
The storage system is segmented into multiple tiers: hot tier for frequently accessed data, warm tier for moderately accessed data, and cold tier for rarely accessed data. This segmentation allows the system to apply different storage media and performance characteristics to different data sets, optimizing both retrieval speed for critical data and cost efficiency for archival data.
Solution Approach 2:
Different storage locations are assigned different quality characteristics based on local access patterns. Data blocks that are frequently accessed are placed in high-performance storage with fast retrieval, while data blocks that are rarely accessed are placed in lower-cost storage with slower retrieval. This local optimization of storage quality matches the actual access patterns of different data sets.
2Reliability
If data is retained longer to meet organizational policies, then data loss protection is improved, but storage space consumption increases
Solution Approach 1:
The retention system is segmented into multiple time-based tiers: hot retention for recently backed up data, warm retention for intermediate-age data, and cold retention for historical data. This segmentation allows the system to maintain comprehensive retention policies while optimizing storage resource utilization by placing older data in more efficient storage tiers.
Solution Approach 2:
The system performs preliminary assessment of data access patterns and retention requirements to proactively migrate data between tiers before actual retrieval or deletion is needed. This preliminary action ensures that data is positioned in the appropriate storage tier in advance, optimizing both retrieval performance and storage efficiency.
3Productivity
If data is migrated frequently between storage tiers, then storage optimization is improved, but system complexity increases
Solution Approach 1:
The storage tiering system operates autonomously by continuously monitoring data access patterns, block age, and retention policies to automatically determine optimal tier placement. The system self-manages migration decisions without requiring manual intervention, using predefined policies and algorithms to assess when data should be moved between tiers based on current system state and organizational requirements.
4Loss of time
If critical data is prioritized for fast restoration, then restoration time for critical data is reduced, but overall system resource consumption increases
Solution Approach 1:
Different restoration quality levels are applied to different data blocks based on their criticality and access patterns. Critical data blocks are maintained in high-performance storage with fast restoration capability, while non-critical data blocks are stored in lower-performance storage. This local differentiation of restoration quality allows the system to prioritize restoration speed for critical data without unnecessarily consuming resources for all data.
Data Source
AI summary
A backup management system may include a data management server, a warm-tier data store, and a cold-tier data store. Snapshots may be captured from various client devices. A data block stored in the warm-tier data store may be referenced by multiple backup snapshots and/or referenced by one or more users. When a data block's total reference count is equal to the cold reference count or equal to or less than a threshold total reference count, the data management server may determine that the data block is ready to be migrated to the cold-tier data store. The data management server may send the data block into a candidate queue. In the queue, data blocks with similar retention periods or similar expected restoration may be grouped as a unit. The unit may be transmitted to the cold-tier data store in a single write request.