Pure Storage & Azure: Creating AI-Ready Data Foundations in the Hybrid Enterprise

Описание: Discover how enterprises are successfully modernizing their IT infrastructure to meet the demands of artificial intelligence (AI) while managing complexity and costs. Many organizations face trade-offs due to hybrid setups and legacy systems, but recent integrations between Microsoft Azure and storage vendors are offering clearer paths forward.Pure Storage & Azure: Creating AI-Ready Data Foundations in the Hybrid Enterprise
This video explores key strategies for AI readiness supported by Azure:
1. Practical Modernization: Learn how companies can use migration paths to move virtual machines (VMs) to Azure without immediate major changes, allowing early testing of cloud adoption and preparing systems for future AI workloads. This approach also helps organizations achieve lower, more predictable storage costs when managed through Azure’s tools.
2. Enhanced Data Protection: Address top concerns like data loss by building stronger recovery systems across on-premises, edge, and cloud locations. Unified control layers across hybrid models support strict compliance needs and data residency requirements, utilizing features like immutable snapshots and replication.
3. AI Readiness Without Rebuilding: Understand why AI readiness often starts with improving existing systems rather than adopting entirely separate platforms. For example, Microsoft’s SQL Server 2025 adds vector database features, allowing teams to build AI-driven applications by pairing SQL Server with high-performance storage arrays to improve throughput.
4. Simplified Container Strategy: See how unified data-management tools, such as the growing use of Portworx with Azure Kubernetes Service, help teams manage containers alongside legacy VMs, providing a safer, slower path to container adoption while supporting enterprise AI initiatives.
The overall lesson for enterprises is that modernization is becoming less about replacing systems and more about improving what is already in place through predictable, steady steps that prioritize cost, security, and data needs.

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Pure Storage, Azure, Microsoft, enterprise AI, AI-ready data, hybrid cloud, infrastructure modernization, cloud migration, data protection, data compliance, SQL Server 2025, vector database, Kubernetes, Portworx, Azure Kubernetes Service, virtual machines, legacy systems, IT strategy, storage costs, data engineering, MLOps.

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