MinIO, an exascale object store for AI data, recently announced a new line of AIStor-powered pod solutions meant to enable delivery of solutions for private cloud modernization.
Simplicity of appliance purchasing comes to cloud flexibility
MinIO AIStor object store software is now pre-integrated as AIStor-powered pod solutions beginning with certified AIStor on Supermicro, which pairs the “familiarity and convenience of appliance-oriented purchasing with the power and flexibility of the cloud operating model.”
The company plans to continue unveiling more AIStor-powered pods in the future.
“Appliance-based solutions, especially ‘unified’ approaches which bolt-on object gateway onto a legacy file/block backend, tightly couple hardware and software together so you’re locked into those respective vendors, which makes long-term flexibility difficult,” said Mahesh Patel, MinIO’s chief business officer. “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.”
MinIO is working to eliminate the friction in the procurement process by combining standardized, certified hardware with highly optimized object store software into a hardened, single-node SKU. This streamlines and simplifies the procurement of storage pods with a pre-integrated, pre-configured, and ready-to-deploy solution.
Pods enable independent upgrades as enterprises seek to avoid vendor lock-in
According to MinIO, the first AIStor-powered pod solutions will pre-integrate Supermicro hardware, with starter four-node pods delivering approximately 1.1 PiB of usable capacity. Each of the pods will consist of multiple hardened, certified AIStor on Supermicro Hyper 1U servers engineered for performance and reliability.
This will enable enterprises to confidently, quickly, and effortlessly purchase, deploy, and scale AIStor pods via those hardened Supermicro nodes, eliminating the need for separate hardware and software negotiations, avoiding lock-in, and reducing operational risk.
AIStor pods enable organizations to upgrade software or hardware independently, taking advantage of performance, cost, and density advancements. This enables enterprises to future-proof their investments, reduce operational costs, and foster greater innovation throughout the analytics and AI stack.
MinIO to provide AIStor support
The pods leverage standard off-the-shelf servers, including Supermicro x86 servers, to avoid the markup associated with proprietary storage appliances and lower Total Cost of Ownership (TCO).
“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.”
Additionally, every AIStor-powered pod solution includes first-call 24x7x365 direct-to-engineer AIStor support through MinIO SUBNET. MinIO will engage the respective hardware provider to offer support.
“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.”
MinIO has been on a roll with its commitment to helping organizations master AIStor and further AI adoption. Read more about the MinIO Academy, an education portal designed for IT professionals that focuses on AIStor training.