Software-defined storage platforms, SDS
Software-defined storage (SDS) is a marketing term for computer data storage software for policy-based provisioning and management of data storage independent of the underlying hardware.
SDS software typically includes a form of storage virtualization to separate the storage hardware from the software that manages it. The software enabling a software-defined storage environment may also provide policy management for features such as data deduplication, replication, thin provisioning, snapshots and backup.
SDS system hardware may or may not also have abstraction, pooling, or automation software of its own. When implemented as software only in conjunction with commodity servers with internal disks, it may suggest software such as a virtual or global file system. If it is software layered over sophisticated large storage arrays, it suggests software such as storage virtualization or storage resource management, categories of products that address separate and different problems. If the policy and management functions also include a form of artificial intelligence to automate protection and recovery, it can be considered as intelligent abstraction.
Software-defined storage solutions may be implemented via appliances over a traditional storage area network (SAN), or implemented as network-attached storage (NAS), or using object-based storage.
Vendors Software-defined storage platforms, SDS
F.A.Q. about Software-defined storage platforms, SDS
What does SDS mean?
SDS stays for software-defined storage solution - it is a computer program that manages data storage resources and functionality and has no dependencies on the underlying physical storage hardware.
All storage systems have always been software-defined. What's changed is that the software has become portable.
But nothing in the storage world elicits more divergent opinions than the term "software-defined storage products". With no universally accepted definition, SDS is vendor-specific. Software defined storage leaders shape the SDS definition to match their storage offerings. The result is that every storage vendor appears to offer SDS.
Storage system software historically was tied to the hardware it managed. When the hardware ran out of capacity or performance, it had to be replaced and the software licensing was repurchased along with the hardware.
What made matters significantly worse was that storage system architectures created isolated silos. Unique infrastructures made everything from storage provisioning, data protection, disaster recovery, tech refresh, data migration, power and cooling more and more untenable. Compound that with the ongoing trend of rapid data growth and the need to store ever-increasing amounts of data, and the available architectures made storage systems management too complicated, difficult, expensive and ultimately unmaintainable.
What are SDS categories pros and cons?
With no working standard SDS definition, a variety of technologies have emerged in the software-defined storage market. For our purposes, the four categories of SDS include:
- Hypervisor-based SDS
- Hyper-converged infrastructure (HCI) SDS
- Storage virtualization SDS
- Scale-out object and/or file SDS
Hypervisor-based SDS pros:
Flexibility. VSAN works with both hard disk drives (HDDs) and solid-state drives (SSDs), including DIMM-based flash drives, PCIe, SAS, SATA and even NVMe. VMware vSAN supports both HDDs and SSDs in a hybrid mode or all SSDs in all-flash mode.
Scalability and performance. VSAN is highly scalable while delivering high levels of performance. It scales out through vSphere clustering and can support up to 64 vSphere hosts per cluster. Each vSphere host supports approximately 140 TB raw storage capacity and well north of 8 PB of raw storage capacity per cluster. On the performance side, each vSAN host can supply 100,000 or more IOPS, yielding millions of IOPS per cluster.
Hypervisor-based SDS cons:
Scalability and performance issues. If a VM requires more IOPS than one physical vSphere host can provide, it can get them from other nodes in the cluster, but with a considerable latency penalty. Inter-cluster storage performance is another issue. Most vSAN clusters use 10 Gbps to 40 Gbps Ethernet and TCP/IP to interconnect the hosts. This architecture essentially replaces a deterministic system bus with a non-deterministic TCP/IP network so latencies between hosts become highly variable. Unless the cluster uses more sophisticated and faster interconnections, its storage performance from one clustered host to another will be highly variable and inconsistent.
Some things are not so simple. Converting from a siloed storage environment to a pure vSAN requires converting non-VM images to VMs first. It's a time-consuming process for non-vSphere environments.
Hyper-converged infrastructure (HCI) SDS pros:
Scalability and performance. Scaling HCI is as simple as adding a node to the cluster. Scaling storage capacity just requires adding drives (HDDs or SSDs) up to a node's maximum or adding additional nodes. Each HCI product has its own scalability and performance limitations; however, most scale well into the PBs and add performance linearly with each server node added to the cluster.
Simplicity. Plug it in, turn it on, configure and you're done. Few systems are simpler. No DIY, and there's just one throat to choke for support.
Hyper-converged infrastructure (HCI) SDS cons:
Scalability and performance issues. HCI cluster capacity is limited by the number of nodes supported in the cluster and the amount of capacity supported per node. If a VM requires more IOPS than a given host can provide, it can get IOPS from other nodes, but with a considerable latency penalty. Inter-cluster storage performance is another issue. Most HCI clusters use 10 Gbps to 40 Gbps Ethernet and TCP/IP to interconnect the hosts so latencies between hosts can be highly variable.
Some things are not so simple. Converting from a siloed storage environment to an HCI cluster requires first converting both non-VM images and VMs to the HCI VMs or Docker containers, a time-consuming process.
Storage virtualization SDS pros:
Flexibility. It works with most x86 physical hosts or VMs as long as the hardware or hypervisor is certified and supported by the vendor. It converts all storage that sits behind it into the virtual storage pool, enabling repurposing of older storage. The scale-out versions permit physical or VM access to any node. Multi-copy mirroring isn't necessary to protect against a single controller failure, although it's available. Storage virtualization SDS can be provided as software or bundled with server hardware similar to HCI.
Total cost of ownership (TCO). The biggest cost savings in storage virtualization SDS comes from commodity hardware and server-based drives. Another cost saving comes from inline data reduction technologies. Compared to equivalent storage systems, most storage virtualization SDS will yield a much more favorable TCO.
Storage virtualization SDS cons:
Flexibility issues. Most storage virtualization SDS can only run on the specific commodity hardware certified and supported by the vendor. Products that can run as VSAs require hypervisors certified and supported by the vendor.
Scalability and performance issues. On paper, these systems support tremendous capacity scalability, but the pragmatic approach is a bit different. Storage virtualization SDS capacity is constrained by x86 server limitations. Each server can handle only so much capacity before performance declines below acceptable levels. Storage virtualization SDS scale-out is constrained by clustering because the number of storage controller nodes supported is limited. Performance may also be constrained by the same limitations.
Scale-out object and/or file SDS pros:
Scalability and performance. Scaling is multi-dimensional: each node can be scaled individually and generally the cluster itself can add nodes for capacity or performance. Performance for both will never approach that of high-performance block storage.
Simplicity. When bundled with hardware, scale-out object or file storage is very simple to set up, configure, and manage. Implementing it as software requires DIY systems integration. Both types leverage commodity hardware, have exceptional scalability and -- in the case of scale-out object storage -- unmatched data resilience and longevity via erasure coding.
Scale-out object and/or file SDS cons:
Flexibility issues. Whether delivered as software or bundled with hardware, the hardware must be certified and supported by the vendors.
Scalability and performance issues. Scale-out file SDS generally doesn't scale as high as scale-out object storage, but object will have somewhat higher latencies. Object storage has significant additional latencies from the metadata and data resiliency functions. Both types are best suited for secondary applications where high performance is not a requirement.
Some things are not so simple. When scale-out file or object storage SDS is purchased as software, it's a DIY project, so special skills, professional services or a systems integrator may be required.