Storage automation shifts storage management tasks away from IT personnel, who can be overloaded with a myriad of modern data center needs, to software and preconfigured devices. In enterprise data centers, storage needs to scale quickly, be agile, and maximize resources.
Appropriately programmed or intelligent software is able to notice issues within data center storage, such as a lack of space or an increased need for storage to support a particular workload. Storage automation can be programmed into a system at the API level.
Storage automation includes:
- Provisioning hardware
- Improving and optimizing storage systems and devices
- Avoiding issues that could arise from humans performing storage tasks and making an error.
One of the top needs in modern data centers is flexibility. To meet current technology needs and stay atop the demand for instant data transmission and availability, enterprise data centers are expected to send resources wherever they will be most effective. This includes storage space — providing data stores the moment they’re needed. Those data stores can be both cloud and on-premise environments.
Enterprises are also expected to provide data to their customers rapidly. A software-defined storage infrastructure prevents IT personnel from having to manually retrieve data; computers can do it instead.
Storage tasks that can be automated include:
- Software-managed data migration between environments.
- Workflow creation, which can often be shortened by software. Simple workflows can be automated so that users can simply select them, instead of manually controlling the entire run process.
Workflow automation in data centers applies to storage workflows as well as compute ones. If storage workflows include both cloud and on-premises, an ideal automation solution should be able to manage both. Often, storage workflows are performed manually by IT staff and have more steps than they would if they were automated.
One example of a workflow automation tool is NetApp OnCommand. It manages basic or standard storage tasks on its own and designs and schedules workflows. Users can automate elements of data protection and disaster recovery. IT admins are responsible for initially designing workflows, but then users can simply click a button to run those workflows in the future.
Predictive analytics are useful for managing data center growth and resource optimization. Analytics contribute to good automation platforms: all data and storage solutions within a system are compared and analyzed, so that the automation platform can then make intelligent decisions regarding the storage.
Predictive analytics often use machine learning and AI to predict what might happen in a data center based on evidence from layers of infrastructure. ML and AI techniques are incredibly helpful in automation, especially as automatic processes and data centers become more intelligent.
The Role of Flash Storage in Data Center Automation
Flash storage is incredibly fast, which automatically increases the rate at which data can be transmitted and processed. Flash arrays also sometimes include built-in features that allow users to create automated tasks and workflows. NetApp All-Flash FAS customers can use FabricPool to automatically ship inactive data to less expensive object storage platforms.
Many enterprise-level storage arrays include APIs with programmable automation. Flash arrays play an important role in enterprise data center storage, including in an autonomous data storage infrastructure.
Also Read: Best All-Flash Storage Arrays
Read More:Implementing Storage Automation in Data Centers | ESF