Storage is getting progressively smarter as analytics capabilities are increasingly integrated into arrays and other parts of the storage layer. Predictive storage analytics, AI and machine learning are coming together to enhance and optimize storage infrastructure and proactively address problems.
Behind the move to more intelligent storage is the increasing use of all-flash arrays (AFAs) and hybrid and hyper-converged infrastructure, along with the greater demand for real-time data on storage capacity and performance.
"Storage is no longer a separate slice of the data center technology stack that you can intelligently manage or analyze in isolation. Looking at larger slices of the stack requires the use of more sophisticated analytical approaches over bigger data," said Mike Matchett, analyst at Small World Big Data.
Storage vendors are gathering vast amounts of data from their customers and applying data mining, analytical queries and predictive modeling to these aggregated data sets to forecast trends. They're feeding the resulting analysis back to their customers to help them plan infrastructure, reduce overhead and proactively address problems before they happen.
AI and machine learning have been added into the predictive storage analytics mix, to continually improve data collection tools and data analysis. The end result is self-healing storage infrastructures that autonomously identify and resolve issues, providing better capacity management, reduced downtime, and increased application availability, performance and productivity.
Below, we've pulled together insight into the current state of storage analytics, along with a look at how some enterprises are using new techniques and technology to make their storage infrastructure smarter. We also take a look at the roles AI and machine learning are playing. And if you're curious about the vendors that are active in this market and what products are available, we've included the latest updates on the vendors and the products they're offering.
1State of storage analytics-
Guidance and use cases
Learn how the use of all-flash arrays, predictive storage analytics, AI and machine learning are combining to make storage faster and smarter.
Predictive analytics tools proactively address storage issues. Find out what to look for in these products. Continue Reading
Storage monitoring and analytics help New York Life upgrade current products and evaluate new technologies. Continue Reading
2AI and better storage-
The latest insight and strategy
See how AI is being integrated into storage technology and providing unique insight into capacity and performance.
Hewlett Packard Enterprise brings AI-based infrastructure management software to market. Continue Reading
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The predictive analytics and AI market
Find out which vendors are offering intelligent storage products and how those products might help your organization.
Vendor updates Hitachi Storage Virtual Operating System and Virtual Storage Platform to address data mobility among data centers, edge environments and the cloud. Continue Reading
Vendor's XVS line streams telemetry data to Violin's cloud system using the Symphony flash management console. Continue Reading
Upgrade extends the role AI plays in storage analytics for data protection and hybrid cloud environments. Continue Reading
AFA upgrade targets need for fast storage in cognitive computing. Continue Reading
The AI engine learns from all workloads running on Pure arrays. Continue Reading
A list of essential definitions
Learn some of the key terms regarding predictive storage analytics, AI and machine learning.
Test your predictive storage analytics knowledge
Predictive analytics is a key technology behind smarter storage. How much do you know about it?Take this quiz