Inside the AWS Storage Assessment: How intelligent analysis replaces guesswork

This article explains how AWS Storage Assessment analyzes workload telemetry to deliver accurate service recommendations, right-sized configurations, and validated cost models for storage migration planning.

• Automated classification pipeline adapts to different data sources using keyword matching, protocol analysis, and IOPS behavior patterns
• Identifies inactive volumes, replicas, and infrastructure components to reduce in-scope workload by 20-40% before sizing
• Applies vendor-aware efficiency modeling to avoid double-counting deduplication and compression already present in source systems
• Uses I/O density analysis to optimize SSD versus capacity pool allocation in FSx for ONTAP, reducing costs by 60-80%
• Solves multi-constraint configuration optimization across throughput tiers, deployment options, and generations for each service
• Models data protection costs including AWS Backup, Elastic Disaster Recovery, and SnapMirror replication
• Provides what-if scenario engine to compare regions, targets, scope boundaries, and architecture options from single data collection

The assessment replaces spreadsheet estimates with multi-stage analysis that weighs workload characteristics, removes non-productive capacity, and validates recommendations against live AWS pricing.