Legacy siloed storage systems cannot handle AI workloads, cloud-native applications, and hybrid cloud demands. Organizations waste up to 80% of IT budgets maintaining fragmented infrastructure while storage teams fight manual provisioning bottlenecks and data silos that cripple GenAI and modern app initiatives.

This whitepaper shows storage architects how to evolve to an Enterprise Data Cloud model. It provides practical guidance for unifying storage infrastructure and eliminating operational overhead. Download it to learn:

• AI storage requirements: Unified architecture supporting block, file, and object protocols with autonomous scaling and AIOps-driven optimization for GPU-accelerated workloads
• Modern application support: Container-granular data services, Kubernetes-native orchestration, and self-service provisioning aligned with DevOps methodologies
• Hybrid cloud integration: Single control plane management across on-premises and multi-cloud environments with seamless data mobility and consistent SLAs
• Cyber resilience architecture: Policy-driven security governance, immutable snapshot protection, and AI-driven threat detection replacing fragmented security models
• Operational transformation: Fleet-wide automation reducing storage management overhead by up to 75% while delivering 99.9999% availability SLAs
• Economic model: Consumption-based STaaS approach eliminating traditional CapEx cycles and reducing data center footprint by 80% with 20% space requirements