Software-defined storage (SDS) is a data storage methodology in which a software layer is used to decouple storage resources from an underlying physical storage hardware infrastructure.
Effectively, SDS abstracts available storage resources within an organization’s broad storage environment across various types of storage devices and systems. While traditional network-attached storage (NAS) or storage area network (SAN) systems are often dependent on proprietary hardware or vendor-specific software, SDS solutions generally use commodity hardware, such as any industry-standard or x86 server, and can unite otherwise incompatible systems.
Through abstraction, SDS allows for policy-based provisioning and dynamic storage resource management, independent of the unique storage hardware being used. SDS uses virtualization to create a unified pool of storage resources that can be dynamically allocated either through automation or manually through a software-enabled dashboard interface.
Typically, traditional data storage infrastructure is composed of various pieces of storage hardware, each managed by proprietary software. This approach often results in a rigid structure bound to inflexible vendor or manufacturer systems, making maintenance, data migration and expansion more difficult. Data fragmentation and reduced data visibility also become greater issues as traditional storage techniques contribute to increased data silos and system complexity.
SDS frees organizations from relying on proprietary infrastructure and offers the freedom to select the vendors and hardware best suited for their needs. Abstracted storage also offers better flexibility, efficiency and faster scalability, with the ability to scale out specific storage resources independent of other data center components, such as compute and networking resources.
As a category, software-defined storage (SDS) comprises many individual technologies that separate storage management and resources from the underlying hardware, each with its own task-dependent use cases. Some common forms of SDS include:
Software-defined storage (SDS) achieves the process of abstracting storage through a software layer, such as a hypervisor. This software functions as a central supervisory system that is capable of effectively managing, virtualizing and controlling all available storage resources across different types of storage, including SAN, SSD and more. Additionally, a storage hypervisor increases the availability, speed and use of total resources over disparate storage systems with improved flexibility and efficiency, while providing valuable services like automated provisioning, snapshots, data duplication and replication.
As a virtual layer, a storage hypervisor can provide centralized and streamlined storage access, greatly simplifying IT operations and facilitating smooth integrations of dissimilar or incompatible storage models suitable for diverse applications.
Software-defined storage (SDS) solutions are composed of several key features.
A defining feature of SDS, the software layer is a storage management application capable of provisioning, managing and optimizing all storage resources.
Through virtualization, SDS solutions decouple storage from the underlying hardware and offer system-wide access to all storage resources.
An aggregated, unified and centralized pool of all available storage is created through virtualization, which enables dynamic resource allocation and optimized utilization of storage capacity.
A common feature among SDS solutions, APIs enable interoperability between different systems, software and hardware.
Unified and centralized storage facilitates a range of data management features capabilities, including data protection, replication, deduplication (the practice of deleting unwanted file copies and redundancies) and disaster recovery.
In addition to improved efficiency and performance, SDS offers several compelling benefits to organizations.
SDS is a cost-effective method for maximizing the value of existing storage resources and improving the capacity of owned storage without purchasing new hardware. By freeing storage resources from the underlying hardware, SDS also allows organizations to use low-cost storage alternatives instead of expensive proprietary hardware.
Because virtualized storage is not dependent on any proprietary hardware or software limitations, SDS is an effective way to free organizations from vendor lock-in, allowing for greater flexibility in hardware selection.
SDS can significantly streamline many storage-management-related tasks, reducing IT expenses by either automating or simplifying complicated workloads related to storage provisioning, monitoring and troubleshooting.
SDS is well suited for operations seeking to not just scale up, but also scale out. SDS supports linear scalability by enabling organizations to easily add additional storage nodes—including SAN disks, SSD and others—without requiring the addition of extraneous compute and network nodes.
Software-defined storage (SDS) is a valuable solution for organizations looking to optimize their storage architecture either for efficiency, compatibility or flexibility, and it can prove an even greater value for many specific use-cases common in today’s digital landscape, including the following.
SDS solutions are often deployed in the management of virtualized environments, in which dynamical storage reallocation is particularly valuable for optimizing virtual machines (VMs) based on workload requirements.
For organizations embracing cloud computing and its private cloud, public cloud and hybrid cloud environments, SDS provides a cost-effective and agile framework to facilitate the transfer between on-premises and cloud-based data management.
Organizations working on data-intensive projects that require high-performance computing, such as scientific modeling and machine learning, often benefit from SDS for optimized and dynamic storage allocation and management.
Inherently scalable and flexible, SDS excels at storing and processing large volumes of data, making it especially useful for big data analysis.
Across industries, SDS provides robust data protection for resilient disaster recovery. When data availability and integrity are mission-critical, SDS is used to expedite data replication to reduce downtime and ensure business continuity.
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