AI-powered unstructured data is the gift that keeps on coming. Enterprises are challenged with leveraging this historical volume of data flow to maximize benefits and choosing storage technology that can effectively house the data. Unfortunately, legacy cloud storage systems are not designed or equipped to support AI storage volumes. As a result, enterprises are looking for strategic counsel and what storage solutions to invest in, knowing AI data shows no signs of slowing down. Object storage offers a means of better managing and controlling large data sets. In the market now, there are technological advances that refine object storage and enable enterprises to have more effortless scalability and flexibility in their AI workloads. These refinements present an opportunity for solution providers and MSPs to advise and help customers gain more control over their AI integration and storage, and most importantly, be a partner to customers navigating a more productive AI future.
Cloud storage evolution
Enterprises started looking at cloud-ready data storage as early as the 1990s when virtualization took hold and people wanted data access that was no longer tied to a specific device or physical space. It spawned an ecosystem of cloud service providers and public clouds like AWS, Amazon and Google. As data usage and volume grew at an accelerated pace, organizations needed storage solutions to support this volume. AWS’ Amazon Simple Storage Service (S3) hit the market in 2006 and became the preferred solution to scale data storage and enable efficient retrieval. AWS S3 also helped popularize the use of object storage as a means of treating unstructured data as ‘objects’ rather than files. It enables each object to have its own meta data and unique identifier, making it useful for retrieving data across cloud environments and for scaling up.
Today S3 is a standard that object storage providers and cloud service providers integrate for hybrid and multi-cloud applications in backup and recovery, analytics, and document archives.
Object Storage 2.0
So, beyond S3, where are we today in giving channel customers the storage services they need to translate AI investments and employee time into real-world benefit and bottom-line value? Well, there is a gap in focus that needs to be filled to satisfy the storage requirements of the majority of organizations. This gap exists because the industry has focused on hyperscalers who offer scale at the expense of control, sovereignty, and visibility. Another factor is some vendors’ focus on GPU-heavy deployments that can lead to compromised security.
What most organizations actually need is an AI infrastructure that is built on a cyber-resilient storage layer, which offers data security, and scalability and provides the compliance that is mandatory for healthcare organizations, research labs and any enterprise that values security above ‘speed-at-all-costs’ risk taking.
This more strategic, rational, secure approach is what we call Object Storage 2.0, a practice that channel providers can embrace to increase storage services for organizations looking to develop and scale AI applications without introducing security risks.
MDS: A modern option for scalability
Object Storage 2.0 is the responsible strategy for managing AI-powered data. At its most powerful, this approach delivers multidimensional scale (MDS). Built on S3 object storage architecture, MDS is a key refinement to object storage, scaling across ten different dimensions, and giving your customers the flexibility they need to adapt to a variety of workloads. The dimensions are apps, capacity, storage compute, metadata, objects, buckets, authentication transactions, throughput, object transactions and systems management.
Some of the ways MDS benefits your customers include:
Application flexibility: Traditional storage solutions struggle to support large numbers of concurrent workloads, using data from a variety of applications. MDS, in a single system, can scale on demand to support ever-changing workloads and data volume. Its multi-dimensional capability is application and cloud origin agnostic.
Budget-saving storage compute: Sometimes organizations need more compute performance but not additional storage. However, many traditional storage systems can’t scale performance resources without the addition of new storage servers — an inefficient and costly limitation. MDS solves this with disaggregated architecture that enables independent scaling of compute and capacity. By decoupling services onto dedicated servers and resources, businesses can scale exactly what they need whether it’s handling more API requests or boosting metadata services for higher ops/second — without the added expense of unnecessary capacity.
Exabyte scaling on demand: Modern storage server designs are reaching capacities of multiple petabytes per server, so organizations may need to scale into the exabyte range. For control and flexibility, MDS enables your customers to incrementally add disks, servers or data centers while staying online, thereby avoiding any service disruption.
Effortless large object data handling: Video streaming, medical imaging and AI-generated data analytics can stress storage system throughput. An answer to this potential bottleneck is implementing scale-out throughput by increasing system resources for S3 API services and, when needed, by disaggregating these services onto dedicated servers. Additionally, S3 connectors can be scaled to any number as required to allow for load-balancing via standard HTTP/IP techniques.
Fast small object processing: Businesses operate with an extensive list of transactions based on vast quantities of small objects. They range from IoT sensor data to test environmental quality in buildings, to online payment gateways to end user authentication. These transactions need storage that supports high transaction rates, or minimal latency. Traditional storage systems are often unable to achieve this at scale. MDS enhanced architecture incorporates S3 metadata service, using fast flash storage for metadata and indexes, which are cached in memory, ensuring near-instantaneous access to small objects and high transaction rates.
Selling a storage strategy for your customer’s future
Object Storage 2.0, incorporating MDS technology, can be a powerful asset in solving your customers’ challenges when managing, using, and storing unstructured AI data. Moving your customers into a more refined and beneficial approach to modern cloud storage helps to further solidify your position as their most trusted counsel in navigating the AI data era.
