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Expanding the Storage Vision across the Data Center



Let’s go. . . and look at what happens when we take our storage vision and apply it to the entire data center.

Storage vision across data center_blog.jpgAbout a year ago I shared some thoughts around the future of data storage and where it was going. That particular blog was mostly focused on available and emerging technologies.  Specifically, I dove into the technology choices consumers were going to be facing when it came to storage of the present and future.

What I didn’t address was what these technologies needed in order to thrive in the modern world. So let’s get started.

The app-data gap

There’s an expectation today that data has to be available at all times and access to that data has to be fast. Very fast. We want Netflix, Google Maps, Amazon Prime, YouTube, Instagram, and everything else we use to be on all the time with no delays.  And that’s just in our personal lives. 

Imagine then how any type of application disruption or slowness would impact our businesses.  No bueno.

We call that disruption, or slowness, the “app-data gap.” It’s what happens when the infrastructure stack (storage, networks, servers and VMs) feels the pain of a disruption or slowness which in turn disrupts the application and makes our users wait. When there’s a gap between end-users’ applications and the data they need access to businesses lose money. 


Eliminating the app-data gap requires more than just a highly available storage platform.   Guaranteeing a 6x9 solution is awesome but that doesn’t close the gap. 

Basic troubleshooting 101: Before you can solve a problem you must first find the source of the problem. That in and of itself can be a daunting task. You can spend hours, or even days, just trying to find the source of an issue because the reality is that the app-data gap is rarely ever caused by just one thing. Just because storage gets the blame more often than not doesn’t mean it’s the culprit. Man, if I had a nickel every time storage was blamed for a “slowness” issue only to find out it wasn’t the storage, I would have enough money to take a party of twelve for a great steak dinner.

In the real world, storage is culpable less than half the time. Most of the time the problems relate to complex infrastructure interactions. And even if you had the time and expertise to navigate through all the moving parts, their best practices, and dependencies in order to keep the infrastructure running at an optimal level, that still doesn’t guarantee finding the root cause of the app-data gap in a timely fashion. 

Solving the problem? That’s another issue all together. How do you solve a problem when you have no idea where the problem is and what’s causing it and no time to track it down?

That’s where predictive analytics and AI come in to save the day. Google tells us that predictive analytics is the practice of extracting information from existing data sets in order to determine patterns and predict future outcomes and trends. And if you Google the phrase “importance of predictive analytics” you’ll get thousands of links with articles saying exactly that. 

In the case of storage an array today must possess the ability to proactively and autonomously self-diagnose and correct issues before they happen. But it can’t end there. The storage must also have the ability to look out across the infrastructure stack and help solve non-storage issues as well. That’s the only way to ensure an always-on, always -fast ecosystem.

Cloud readycloud ready.jpg

It’s the king of buzz words for a reason: it’s important. In fact, it’s safe to say that having a cloud strategy has become a major initiative for every single IT leader out there. If you don’t have a cloud strategy, then you need to get one. Fast. Why is the cloud so important?  Let’s start with the obvious: mobility, flexibility, agility and cost. There’s also simplifying infrastructure, which is attractive to everybody.

That’s not to say that all data is moving to the cloud. No, far from it. But data is moving to the cloud and it’s moving there quickly. IDC predicts expenditures in cloud computing will reach as high as $162B by 2020—and that’s right around the corner.

Is private cloud driving this push? Public cloud? Some mix of on-prem vs. cloud?  Hybrid IT? (My new favorite buzz word by the way.)

It doesn’t matter. Becasue there is still a ton of legacy infrastructure out there and it has data trapped in rigid old-school silos.  While that tech was great for its time, today it drives up costs and hampers IT’s ability to move, grow and respond quickly. 

That’s why it’s of critical importance to be prepared with cloud-ready storage. While pondering the benefits of public cloud, private cloud, on-prem and/or hybrid IT, cloud-ready storage lets you say "It doesn’t matter!"  You’re prepared for any of those directions.  Heck you’re prepared all of them—and that’s the key.  The struggle of keeping everything going, i.e. responding to the needs of the apps, adding more capacity, moving VMs, whatever, and getting your data center future-proofed is very, very real. That’s what makes cloud-ready storage possibly the most critical investments that can be made today. 

Now take that a step further. Cloud-ready storage built on a modern platform can link primary, secondary and public cloud storage which would eliminate any and all silos. The end result is unlocked storage that enables you to move application data easily and quickly whenever necessary. 

From no bueno to muy bueno

HPE InfoSight is light years ahead of where everyone else is. Scratch that. HPE InfoSight is light years ahead of where everyone else’s roadmap is. Muy bueno!

It’s all done through a combination of rich telemetry, sensors, and cross correlations between active components. Then we leverage real-time predictive analysis and global learning from a wide breadth of system data being reported back to us. In fact, every second InfoSight processes millions of sensor data points from customers globally.

A way of thinking about HPE InfoSight is AI for the data center. This is what gives it the ability to predict issues before they occur and proactively resolve issues as they pop up. For example, HPE InfoSight automatically resolves 86% of issues before a customer even knows there’s a problem. And it has helped to drive measured available for all HPE Nimble Storage customers to greater than six-nines. Muy bueno!

Future is now

There you have it. Storage modernization for now and the future already set. Now imagine what happens when we take our storage vision and apply it to the entire data center. Imagine when we simplify ALL the technologies in the stack. 

We’re already way ahead of you!!!

Jorge Maestre_HPE Storage.jpgMeet Around the Storage Block blogger Jorge Maestre, Competitive Strategist, Global Storage, HPE. @BigStrongGeek



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