AI and the Cloud Call for a New Data Storage Approach.
The hybrid cloud and the processing of location-independent data as well as the huge amounts of data generated by AI are forcing storage technology vendors to adopt new approaches and different ways of thinking. Consistent access to and availability of data streams in a hybrid cloud infrastructure is a challenge that can be solved through intelligent data management. Storage technology must be designed for this.#IBM #Cloud Services #Cloud Strategy #Artificial Intelligence
With the rising popularity of the hybrid cloud it is becoming increasingly important to manage the network edge. Efficient edge computing[i] generates large amounts of data that can be used for analytics and AI. This becomes more and more desirable because the edge continues to grow along with the entire digital universe, creating more and more data sources and data silos. According to IBM, enabling the rapid availability of this and other data in the enterprise starts with building a foundational data layer, a containerized information architecture and the right storage infrastructure.
The latest trend in storage technology is based on a principle that is not new, namely software-defined storage. SDS separates the storage software from the hardware and is generally designed to work on any industry standard or x86 system. Therefore, the software is no longer dependent on proprietary hardware. As a result, storage capacities can be expanded at will and contribute enormously to the flexibility of modern IT infrastructures. Often, such environments are hyperconverged infrastructures (HCI)[ii], where all software is separated from the hardware. IT giant IBM began applying this principle already 30 years ago - with the implementation of software-defined storage and the introduction of IBM Spectrum Scale.
The new reality calls for new storage solutions
Over the past few decades, Spectrum Scale has made immense strides. Today, the system specializes in managing unstructured data for cloud and artificial intelligence analytics while streamlining enterprise workflows. The introduction of the new storage platform Spectrum Fusion[iii] is a technology leap and part of IBM's strategy to focus on hybrid clouds and AI and thus a direct consequence of the new IT reality that will be dominated by the cloud - especially the hybrid cloud - and AI. IBM Spectrum Fusion, a hyperconverged infrastructure system, integrates computing, storage, and networking. IBM laid the corporate foundation for this capability with its $34 billion acquisition of Linux and open source leader Red Hat in 2019, a purchase that included OpenShift Kubernetes container management technology and the Red Hat Enterprise Linux operating system. IBM's combination of Red Hat Linux, Watson AI, and its Spectrum offerings provide a combination of solutions that directly address a new IT reality: More and more applications and data are being accessed, processed, executed, and stored independently of traditional data centers. The trend leads to container-native storage, with IBM being one of the key drivers for this trend.
Continuous data management
Spectrum Fusion is IBM's solution for delivering relevant storage solutions in a cloud-native world, designed to access the hybrid cloud globally. The first version is offered in the form of a container-native[iv] HCI system. It integrates computing, storage and networking into a single solution and is equipped with Red Hat OpenShift so that companies can support environments for virtual machines and also for containers, as well as provide software-defined storage for cloud, edge, and containerized data centers. IBM plans to release a pure SDS version of IBM Spectrum Fusion in early 2022.
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[iii] IBM Spectrum Fusion| IBM