Backup Storage Prediction via Pilot Phase Data Collection
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Solution Overview
Problem
IT departments face challenges in accurately predicting storage capacity and performance requirements for backup and recovery solutions in enterprise environments due to inefficiencies in existing resource planning tools, which often rely on generic assumptions and heuristic methods, leading to inaccurate estimates and resource bottlenecks.
Innovation Solution
A system that performs an initial pilot phase or 'dry run' to gather detailed information from client devices, using agents to collect file manifests and deduplicate data, allowing for more accurate computation of storage capacity and performance requirements based on unique data and backup policies, optimizing storage and network resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If generic assumptions and heuristic methods are used for resource planning, then the planning process is simple and quick, but the accuracy of storage capacity and performance requirements prediction is poor
Solution Approach 1:
The system performs a pilot phase before actual backup operations to collect real data from client devices. This preliminary action includes gathering file manifest information, analyzing data characteristics, and simulating backup processes to generate accurate predictions of storage capacity and performance requirements, avoiding the need for complex real-time measurements during actual backup operations
Solution Approach 2:
The system creates a virtual model of the backup environment by collecting file manifest data from client devices and simulating backup operations. This copy or representation of the actual backup process allows for accurate prediction of resource requirements without requiring the full complexity of the actual backup system during the planning phase
2Measurement precision
If detailed information is collected from all client devices, then the prediction accuracy improves, but the time and network resources required for data collection increase
Solution Approach 1:
The system extracts only the essential information needed for prediction from client devices, specifically file manifest data including file paths, sizes, and metadata. This selective extraction avoids collecting unnecessary detailed information while still providing sufficient data for accurate storage capacity and performance requirement predictions
Solution Approach 2:
The system collects file manifest information from a subset of client devices during the pilot phase rather than attempting to collect complete data from all devices simultaneously. This partial action approach provides sufficient statistical data for accurate predictions while minimizing the time and network resources required for data collection
3Quantity of substance
If storage capacity is increased to accommodate all backup data, then data retention is improved, but network bandwidth and IOPS requirements increase
Solution Approach 1:
The system uses prediction results to optimize storage capacity parameters and configure appropriate network bandwidth and IOPS allocations. By accurately determining the actual storage requirements through pilot phase data collection and analysis, the system avoids over-provisioning resources, thereby reducing network bandwidth and IOPS consumption while maintaining sufficient storage capacity for data retention
Solution Approach 2:
The system creates a virtual model of the backup data to predict storage requirements without actually storing all backup data during the planning phase. This copying approach allows for accurate determination of storage capacity needs and corresponding network/IOPS requirements without the resource consumption of handling actual backup data volumes
Data Source
AI summary
Techniques are described for predicting the storage capacity and performance requirements for deploying and maintaining a backup solution within an enterprise. In particular, a backup system is described which uses an initial pilot phase, during which the system can gather information about the files and data on each end user's device (i.e., client device) that will be backed up and provide a more realistic estimate and resource planning for the backup solution deployment. This initial pilot phase can be performed before any content is actually backed up from the client devices.