In this article

  • With a lean IT staff across the globe, iland increasingly relies on automated solutions to ensure its offerings meet customer needs
  • iland CTO Justin Giardina explores businesses’ growing need for predictive analytics and how the industry’s first AI recommendation engine is helping reduce latency and improve performance
Justin Giardina of iland shares how predictive analytics are key to managing a complex global infrastructure

Five-nines reliability just isn’t good enough for iland.

With its standard service-level agreement (SLA) guaranteeing 100 percent uptime, the global cloud service provider must ensure its own IT infrastructure is pristine. And with a lean IT staff of just a few dozen across its North American, European and Asian footprint, the Houston-based company increasingly relies on automated solutions to ensure its infrastructure (IaaS), disaster recovery (DRaaS), and backup (BaaS) as a service offerings are meeting customer needs.

Justin Giardina, chief technology officer at iland Secure Cloud, shares his observations on managing a complex global infrastructure and his company’s increasing reliance on the HPE InfoSight predictive analytics platform, including its newest feature – the industry’s first artificial intelligence (AI) recommendation engine.

What business challenge are you addressing through your infrastructure choices?

Justin: For us, the name of the game is automation — as much automation as possible. iland architects things in a repeatable manner to help ensure we meet our SLAs and not have any downtime with the various pieces of our infrastructure.

We have two major issues to consider when we look at an infrastructure vendor:

One is the SLA and uptime. We offer 100 percent uptime, outside of maintenance, so we need an infrastructure that can help us maintain that. Secondly, we include robust data security, encryption and compliance capabilities as part of our offering. So it’s very important that we can have a singular storage infrastructure that covers all of these bases.

 What lead you to deploy HPE InfoSight and other solutions from HPE Nimble Storage?

Justin: We started working with HPE Nimble Storage (acquired by HPE in April 2017) a few years ago, because we knew they could scale to the size we need for a global footprint. The fact that Nimble offers multiple types of arrays for our infrastructure is really huge for us. We don’t have to pick Vendor A for our flash tier, or Vendor B for the hybrid tier, and Vendor C for archive.

And to be able to manage it all with HPE InfoSight is an added bonus.

What it comes down to is this … we chose HPE Nimble Storage for the great features like HPE InfoSight, overall performance and cost per gig. But most importantly, the whole package gives us the ability to meet our SLAs.

What makes HPE InfoSight different from other predictive analytics platforms you considered?

Justin: When we’ve dealt with other vendors, the management tools were subpar or not scalable. With InfoSight, we have a singular tool that is effective and comes with the price we pay for the arrays.

As far as I’m concerned, InfoSight has been great for everything we’ve needed -- from dealing with a technology issue, looking at things like performance or cash utilization, and even to help with business-grade issues, like quickly looking up warranties or checking capacity.

HPE InfoSight has now added the industry’s first AI recommendation engine to its capabilities. Why is that important for iland?

Justin: It goes along with what I mentioned about capacity and performance. If we see a problem, like with latency or some performance hit, InfoSight enables us to use not just our own data - but we’re also able to use the (aggregated) data from the entire HPE Nimble Storage customer base to spot trends or get answers quickly. That is tremendously important to us.

We see real benefits in the AI engine to proactively determine potential problems to solve important issues and help run our business.

Just as we are very interested in automation and data-driven analytics, it’s very refreshing to see that InfoSight is based on that same methodology. Those types of advantages are what drew us to Nimble and InfoSight, and we remain very interested in your roadmap to see where it’s headed next.