What goes into the right storage for AI?
Artificial intelligence (AI), machine learning and cognitive analytics are having a tremendous impact in areas ranging from medical diagnostics to self-driving cars. AI systems are highly dependent on enormous volumes of data—both at rest in repositories and in motion in real time—to learn from experience, make connections and arrive at critical business decisions. Usage of AI is also expected to expand significantly in the not-so-distant future.
As a result, having the right storage to support the massive amounts of data required for AI workloads is an important consideration for an increasing number of organizations. To deliver on the promise of AI, many organizations will require storage systems with five key attributes:
- Availability
- Reliability
- Performance
- Ease of use
- Automation
Ensuring storage can support AI systems
Availability: When a business leader uses AI for critical tasks such as understanding how best to run their manufacturing process or to optimize their supply chain, they cannot afford to risk any loss of availability in the supporting storage system. If the storage is not available, then the AI software can’t do its job. High-availability storage with data replication to a secondary site is highly recommended, if not an imperative, for enterprises adopting AI.
Reliability: AI systems can’t make a decision if the data they use is corrupt. The reliability of the data depends on building capabilities such as error checking into the software that runs the storage array. Another aspect of reliability is the dependable operation of the storage hardware. Storage arrays that use flash memory are well suited to AI systems because the solid-state drives have no moving parts that can wear out.
Performance: Systems processing AI workloads have got to be fast because they are increasingly making real-time data decisions. Consider the high degree of performance that a Wall Street company may require for making high-velocity trading transactions. If the company’s system is not as fast as a competitor’s system, the results could be financially damaging. A fast AI engine requires high-performance storage, and the fastest storage technology available today at the right price point is a storage system equipped with all-flash technology. As big data and cognitive analytics become more pervasive, all-flash technology is definitely the future for storage systems supporting these workloads. In fact, a recent IDC press release on the world enterprise storage market reported that all-flash array revenue in Q2 2017 represented a 37.6 percent year over year increase.
Ease of use: Even while the volume of data is increasing, budgets for hiring IT storage administrators has dropped significantly across many industries. As more storage is added to support AI and other data-hungry applications, organizations require storage in their IT infrastructure that offers ease of use for an IT generalist—or the application owner who is configuring the AI system—to easily install, deploy and manage that storage.
Automation: Because fewer people today are managing more IT infrastructure, automation is essential. Automation of functional storage features such as replication, tiering and backups can greatly reduce the storage management impact of AI. And the more automated the system, typically the lower the costs are to run it.
Building AI into storage
Today, providers such as IBM are also leveraging AI inside the storage array so that the system can make smart storage management decisions. Examples of such decisions include sensing the IT environment and making the necessary adjustments to run better within it, moving data to a location closer to where it’s being accessed and understanding when information is becoming cold data that can be archived. An AI-assisted system can even help predict when an environment is running out of storage and generate a notification to increase capacity as necessary or as circumstances change.
IBM Flash Storage systems are engineered to meet the storage requirements of AI, big data analytics, machine learning and other cognitive applications with mission-critical availability and reliability, high performance, ease of use and automation. Learn more about the value of storage with all-flash technology to support AI workloads.
The post What goes into the right storage for AI? appeared first on IBM Systems Blog: In the Making.