If you really want to transform your business, get AI to transform your infrastructure first

ITOps isn’t enough anymore reckons HPE. You need AIOps


Sponsored Feature AI isn't magic. But applied correctly it can make IT infrastructure disappear. 

Not literally of course. But Ronak Chokshi, who leads product marketing for InfoSight at HPE, argues that when considering how to better manage their infrastructure, tech leaders need to consider what services like Uber or Google Maps have achieved.

The IT infrastructure behind the delivery of these services is immaterial to the rest of the world - except perhaps for frazzled tech leaders in other sectors who wonder how they could achieve similarly seamless operations.

"The consumers don't really care how it works, as long as the service is available when needed, and it's easy to manage," he says.

Pushing infrastructure behind the scenes is the raison d'etre of HPE InfoSight AIOps platform. Or, to put another way, says Chokshi, InfoSight worries about the infrastructure, so tech teams can be more application-centric.

"We want the IT teams to be a partner to the business, to the line of business stakeholders and application developers, in executing their digital transformation initiatives," he explains.

That's a stark contrast to the all too common picture of admins fretting over whether a given host is being overburdened with VMs, or crippled by too many read-write cycles.

It's not that this information is unimportant. Rather it's a question of how it's gathered, and who – or what – is responsible for collating the data and gaining insight from it. And, most of all, taking positive action as a result.

From the customer's point of view, explains Chokshi, "InfoSight becomes your single pane of glass for all insights, for any issues that come up, any metrics, any attributes, or any activity that you need to track in terms of IOs, read write, throughput, latencies, from storage all the way up to applications." This includes servers, networking, and the virtualization layer.

More importantly though, the underlying system predicts problems as they arise, or even before, and takes appropriate action to prevent them.

It all starts with telemetry

The starting point for InfoSight is telemetry, which is pulled from every layer of the technology and application stack. Chokshi emphasizes that this refers to performance data from HPE's devices, not production or customer data. "That's IO read writes, throughput latencies, wait times, things of that nature."

Telemetry itself potentially presents an IO and performance challenge. Badly implemented real time telemetry could impact performance. Spooling off data intermittently when systems are running quiet means the chance for real-time insight and remediation is lost.

"We actually instrument our systems very intelligently to send us specific kinds of telemetry data without performance degradation," says Chokshi. This extends right down to the way HPE structures its storage operating system..

HPE InfoSight aggregates the telemetry data from across HPE's global install base, together with information from HPE's own (human-based) support operation.

"When there is an issue and our support personnel get a call from a customer, they troubleshoot it, and fix it... but when the fix is implemented, we don't just stop there. That is where the real work begins. We actually create a signature pattern. It's essentially a fingerprint for that issue, and we push it to our cloud."

This provides a vast data pool against which InfoSight can apply AI and machine learning, which then powers support case automation.

As telemetry data from other devices across the installed base continues to stream into HPE, Chokshi continues, "we create signature patterns for issues that might come up from those individual systems."

When the data coming from a customer matches an established signature pattern within a specific environment, InfoSight will push out a "wellness" alert that appears on the customer's dashboard. At the same time, a support case is opened.

Along with alerting customers, InfoSight will also take proactive actions, tuned to customers' individual environments. For example, if it detects that a storage OS update could result in a conflict or incompatibility with the VM platform a customer is running, it will halt or skip the upgrade.

Less time solving storage problems

The potential impact should be pretty obvious to anyone who's had to troubleshoot an underperforming system, or a mysterious failure, which could be down to storage…but might not be.

Research by ESG shows that across HPE's Nimble Storage installed base, HPE InfoSight lowered IT operational expenses by 79 percent, while staffers spent 85 percent less time resolving storage-related tickets. An IDC survey also showed that more than 90 percent of the problems resolved lay above of storage. So, just taking storage as a starting point, InfoSight can have a dramatic impact right up the infrastructure stack.

At the same time, InfoSight has been  extended to encompass the software layer, with the launch of App Insights last year. As Chokshi says, it's often a little too easy for application administrators to shift problems to storage administrators, saying "hey, looks like your storage device is not behaving properly."

App Insights creates a topology view of the entire stack and produces alerts and predictions of problems at every layer. So, when an app admin suggests that their app performance is being degraded by a storage problem, Chokshi explains, "The storage admin pretty much almost instantly would have a response to that question saying they can look up App Insights dashboard."

So, the admin can identify, for example, whether a drive has failed, or alternatively that a host is running too many VMs, "and that's slowing your applications down."

For a mega scale example of how InfoSight can render infrastructure invisible,  look no further than HPE's Greenlake edge to cloud platform, which combines on-prem infrastructure management and deployment with management and further services in the cloud.

For example, HPE has recently begun offering HPE GreenLake for Block Storage. Traditionally, deploying block storage for mission- or business-critical systems meant working out multiple parameters, says  Chokshi. "How much capacity? How much performance do you need from storage? How many applications do you plan to run, etc, etc.."

With the new block service, admins just need to set three or four parameters, including whether the app is mission-critical or business-critical and choosing an SLA.

"And you provision that, and that's all done through the cloud. And it essentially makes the block storage available to you. Behind the scenes, HPE InfoSight powers that experience from enabling the cloud operation experience and ensuring that systems and apps don't go down. It predicts failures, and prevents them from occurring."

Greenlake expansion on the way

Over the course of this year, InfoSight will be extended to more and more HPE Greenlake services. This is a big deal because what was originally brought to market for storage, then servers, is now being integrated with nearly every HPE product that is provisioned through HPE Greenlake

At the same time, HPE will extend the InfoSight-powered support automation it has long offered on its Nimble Storage, which sees customers bypassing level 1 and 2 technicians, and being put straight through to level 3 support. "Because by the time you call, we already know the basics of the issue and we already know your environment. We don't have to ask you questions. We don't have to ask for logs, we don't have to ask for any sort of data. We actually already have it through the telemetry data."

So is this as good as it gets? No, it will actually get better in the future, argues Chokshi, because as InfoSight is rolled out to more services and products, and to more customers, it will be accessing ever more telemetry and analyzing ever more customer contexts.

"To actually get the advantages of AIOps, you need large sets of relevant data," he says. "And you need to let time go by because AI is not a one and done. It improves over time."

Sponsored by HPE.

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