By making storage resources programmable, software-defined storage (SDS) allows users and organizations to decouple or abstract storage resources from the underlying hardware platform for better flexibility, efficiency, and quicker scaling.
This strategy allows storage resources to be integrated into a wider software-designed data center (SDDC) architecture, where resources may be readily automated and coordinated rather than isolated.
For process automation, most complete application connections need open programmable APIs, which SDS is especially suited for.
How Does Software-Defined Storage?
Software-defined storage is a data management strategy in which data storage resources are isolated from underlying physical storage technology and, hence, more flexible. Resource flexibility is combined with programmability to offer storage that adjusts to changing needs quickly and automatically. This programmability covers policy-based resource management and automatic storage capacity provisioning and reassignment.
This deployment model’s software independence also substantially simplifies SLAs and QoS and makes security, governance, and data protection much simpler to implement.
When used properly, this model improves performance, availability, and efficiency.
SDS Use Cases in Hybrid Cloud Deployments
SDS is highly important in hybrid cloud architectures because it enables centralized management of multiple types of data storage and resources and extends on-premises storage services to the public cloud. The following are some of hybrid environments’ most significant software-defined storage use cases.
Disaster Recovery and Cloud Backup
Disaster recovery (DR) and business continuity are vital for today’s enterprises. Cloud-based SDS solutions may provide a discrete DR zone without required setup, installation, or maintenance. Data from on-premises systems is replicated to the cloud, and resources may be ramped up automatically on demand.
Cloud SDS systems also aid in off-site cloud backups and give a low-cost cold storage option. These systems are off-site, fail-safe, and automatically scale up without additional hardware. Administrators may utilize the SDS management plane to perform disaster recovery procedures from a single interface.
Hybrid Data Management
Cloud-based SDS solutions are essential for managing data in various environments, including on-premises, public cloud, multi-cloud, and hybrid cloud. These systems may expose on-premises storage via the iSCSI protocol to cloud IaaS instances and external hosts and clients via the NFS or CIFS protocols.
Hybrid SDS solutions imitate corporate storage capabilities and function similarly to traditional on-premises systems. However, it is vital to ensure that SDS can deal with any latency issues that may arise due to a hybrid architecture.
Cloud Dev/Test Environments
SDS is a development/test environment solution that controls many storage resources via a single interface. This simplifies the utilization of the CI/CD pipeline by allowing for the cloning of existing data sets and access to data kept on-premises in production scenarios.
On the other hand, existing cloning techniques in public cloud environments are time-consuming and costly, demanding process changes to connect with cloud provider APIs. Cloud-based SDS solutions solve these issues by providing on-premises systems with the same snapshot techniques and APIs, allowing faster deployments and easier integration into DevOps workflows.
Despite advancements in technologies such as thin provisioning, deduplication, and data compression, storage expenses account for a significant portion of corporate OPEX. SDS solutions can address this by bringing enterprise-grade storage capabilities to the cloud, increasing efficiency, and cutting costs. They cover underlying storage in cloud settings, making on-premises deployment possible. This is particularly useful for accessing cloud storage tiers like Amazon EBS and Amazon S3 storage in AWS Azure disks and Azure Blob storage. Tiering is managed automatically by cloud SDS systems, decreasing storage costs and enhancing technical agility across several infrastructures.
Data Replication and Migration
The capacity to migrate data from on-premises systems to the cloud and vice versa is another essential feature of cloud-based SDS solutions. This enables you to use a lift-and-shift strategy for your applications and workloads. A “lift and shift” migration moves existing on-premises data and workloads to the cloud “as-is,” without modifying them for the new environment, making it the fastest and easiest option for cloud on-boarding.
Challenges of Data Storage
Cloud computing, artificial intelligence, machine learning, big data, and 5G technologies are enabling rapid transformation of IT throughout the globe, which is essential in ushering in the digital age we now live in, and this is accelerating further in the post-Covid era. Businesses and services are getting more intelligent and diversified, creating massive amounts of data in various formats, posing a significant challenge to existing storage systems.
In this section, we will go over these challenges in further depth.
- Maintenance and operations difficulties– Traditional storage design operates in silos, making troubleshooting difficult. Different applications need the use of different storage devices.
- Inflexibility of capacity expansion – Traditional storage is difficult to scale since it can only be scaled per disk group or array of disks. The storage controller limits storage performance. Performance suffers as a consequence of capacity growth.
- Not able to meet high throughput demands – Storage controllers restrict the performance of traditional storage architectures, preventing high throughput When the volume of data surpasses 100 million items, this might cause instability and performance degradation.
- High TCO due to rapid growth – Traditional storage systems need periodic hardware upgrades, high prices, and considerable financial and personnel input, with costly peripherals and original disk sets required to increase storage capacity.
Benefits of Software-Defined Storage
Storage abstraction offered by software-defined storage solutions benefits businesses in several ways.
- Software-Defined Storage for Lower TCO – One of the primary advantages of SDS is that it uses storage virtualization on X86 standard servers, which are less expensive and easier to maintain. Platform consolidation reduces hardware costs, maintenance charges, and the complexity of managing various storage resources.
- Flexible expansion of Distributed architecture– SDS uses a distributed architecture to allow enterprises to scale out storage on demand to meet rising storage and performance demands. This method eliminates the necessity for a pre-assessment of current storage resources.
- High performance for parallel processing – Multi-node parallel data processing provides high throughput and IOPS performance. Several storage nodes collaborate to process and manage data requests. Workload distribution between nodes to obtain greater performance than standard storage systems
- Single interface to manage the entire cluster – SDS manages a full cluster of storage nodes or pools via a single interface. A single window provides a unified view and control over all resources.
- Single click operation – SDS is a unified solution for managing operations and maintenance with a single click for the convenience of data management. While updating hardware, no new software licenses must be obtained; just physical devices must be replaced.
The exponential expansion of data creation by businesses and industries necessitated the development of a strong and efficient storage management system. Existing storage devices cannot meet the demands for on-demand scalability, agility, fault tolerance, redundancy, capacity, and performance control.
The advent of Software Defined Storage systems allows dynamic allocation of storage resources, single interface administration, and several other advantages. SDS systems provide seamless scaling of capacity and performance to meet ever-changing storage resource needs.