Available exclusively via Arrow Electronics, the solutions integrate exascale AIStor software with hardware from Supermicro and others to simplify private cloud AI infrastructure
MinIO, the leading exascale object store for AI Data, today announced a new line of AIStor-powered pod solutions to deliver solutions designed for private cloud modernization. Available exclusively via Arrow Electronics’ intelligent solutions business, MinIO AIStor object store software is now pre-integrated as AIStor-powered pod solutions beginning with certified AIStor on Supermicro (NASDAQ: SMCI), pairing the familiarity and convenience of appliance-oriented purchasing with the power and flexibility of the cloud operating model. MinIO plans to continue unveiling more AIStor-powered pods that leverage additional storage vendor hardware in the future.
For global corporations with standardized IT procurement and large-scale infrastructure needs, purchasing and deploying storage software and hardware separately to create storage pods can add friction to the procurement process. Taking a page out of the “Hyperscaler Economics” playbook, MinIO is combining standardized, certified hardware and highly optimized object store software into a hardened single-node SKU, streamlining procurement of storage pods with a pre-integrated, pre-configured, and ready-to-deploy solution.
The first AIStor-powered pod solutions will pre-integrate Supermicro hardware, with starter four-node pods delivering ~1.1 PiB of usable capacity. Each pod consists of multiple hardened, certified AIStor on Supermicro Hyper 1U servers engineered for performance and reliability. Enterprises can now confidently purchase, quickly deploy, and effortlessly scale AIStor pods via hardened Supermicro nodes, eliminating the need for separate hardware and software negotiations, avoiding lock-in, and reducing operational risk.
“Appliance-based solutions tightly couple hardware and software together so you’re locked into those respective vendors, which makes long-term flexibility difficult,” said Mahesh Patel, Chief Business Officer, MinIO. “AIStor pods deliver the simplicity of the appliance purchasing model paired with full cloud-operating model flexibility, enabling customers to easily and cost-effectively consolidate all of their data onto a modern, AI-ready private cloud infrastructure.”
Unlike proprietary appliances or “hardware-defined storage” that come with forced refresh cycles, AIStor pods enable organizations to upgrade software or hardware independently to take advantage of performance, cost, and density advancements. This flexibility allows organizations to future-proof investments and reduce operational costs, while enabling greater innovation up the stack for analytics and AI. AIStor pods leverage standard off-the-shelf servers, including Supermicro x86 servers, avoiding the markup associated with proprietary storage appliances and lowering Total Cost of Ownership (TCO).
Every pod includes first-call 24x7x365 direct-to-engineer AIStor support through MinIO SUBNET. MinIO will engage the respective hardware provider as necessary to provide support.
“Supermicro’s extensive portfolio of storage optimized servers is a great fit for MinIO’s AIStor data management solution,” said Michael McNerney, senior vice president of Marketing and Network Security, Supermicro. “Customers want easy-to-deploy solutions and the pre-integrated and pre-validated AIStor on Supermicro servers provides that simplified deployment experience and can accelerate- time-to-value for customers.”
“Enterprises are quickly discovering that successful AI initiatives depend as much on data infrastructure as on algorithms and GPUs,” said Steve McDowell, Chief Analyst at NAND Research. “Managing AI-scale data requires not just performance, but procurement simplicity and predictable economics. Pre-integrated pod solutions like these from MinIO align with the broader industry shift of bringing hyperscaler-style efficiency and scale into enterprise private clouds. This gives organizations a clearer path to align infrastructure investments with AI-driven business priorities.”