Australia and New Zealand gear up for storage analytics

Despite the marketing wars, ANZ is ahead of the adoption curve for storage analytics, which promises to alleviate storage management woes

This article can also be found in the Premium Editorial Download: CW ANZ: CW ANZ: Home in on storage minutiae

The tectonic shifts happening in storage technology will profoundly affect the enterprise technology landscape in Australia and New Zealand (ANZ) over the next few years.

On the hardware front, the world, including the ANZ market, is rapidly moving to solid-state memory and more recently, non-volatile memory express (NVMe), in place of spinning disk and tape.

As for applications, there has been a raft of heavy-duty use cases waiting for high-performance storage, such as video rendering, online transaction processing (OLTP) databases, financial analysis, fraud detection, genome sequencing and data mining.

Although the different types of solid-state memory bring many advantages over spinning disk, the technology poses challenges in the somewhat messy zone where disparate storage technologies must work together.

Gartner points to the management problem in its 2018 Strategic roadmap for storage. “Storage management within a single storage platform or an HCIS [hyper-converged integrated system] is becoming more automated, but management across a heterogeneous storage environment continues to be a challenge,” the analyst company says.

Then there is also the increasing use of enterprise public cloud storage, which Gartner says tends to be confined to use cases where network latency is not an issue.

The customers I have spoken to in ANZ see analytics as future proofing them against any curve balls that may arise in the business.
Sumit Kalia, Oracle

Part of the answer for technology leaders presiding over storage in ANZ is putting analytics capabilities – supported by machine learning and artificial intelligence (AI) – into storage platforms.

Indeed, Gartner sees machine learning becoming deeply embedded in storage infrastructure, moving from merely providing periodic updates to detecting problems using algorithms that are constantly updated based on incoming data.

But storage is just a part of the IT infrastructure and should operate in concert with compute and networking. Also, while machine learning is necessary, it is insufficient for improving the overall performance, manageability and availability of IT infrastructure.

“The ideal end state of a self-managing, self-optimising, self-healing IT infrastructure can only be attained when all components are included in the machine learning analytics process,” says Gartner.

There is another caveat to the impact of storage analytics. Gartner says cloud-based machine learning is likely to be better at its job than on-premise systems because the data used by such machine learning engines comes from multiple organisations, thus providing a wider set of storage circumstances to analyse.

“Some organisations, however, will be unwilling or unable to share the data that feeds a supplier’s machine learning engine outside their own premises,” it says. “For these organisations, the benefits of machine learning-enhanced systems may be reduced.”

Changing with the times

Oracle, the database and enterprise application giant, has thrown its hat into the predictive storage analytics ring. It needs to be there to make sure its often massive databases and downstream applications play nicely with storage infrastructure.

Times have changed in storage analytics, says Sumit Kalia, Oracle Australia’s director for systems.

Some 15 years ago, when Kalia was hired by a storage supplier as an architect, things were simpler when businesses were evaluating their storage or data management strategy.

“It was very much about performance, IOPS [input/output operations per second], capacity and the level of redundancy and protection,” he says. “Storage was created as a dead low silo piece which was part of a larger solution stack.”

These days, the sheer size of incoming data means the storage game has changed profoundly, says Kalia.

“If you fast forward to 2019, it is estimated that we will generate more data this year than in the previous 5,000 years,” he says. “That’s close to 1.7MB of data per second, per person globally. That’s a lot of data and from that, there’s more demand from our customers searching for a competitive edge. It’s about mining that data and turning it into intelligent business decisions.”

Kalia says it is much harder to architect storage these days compared with 15 years ago. “That’s where the smarts of storage analytics can help,” he says. “The customers I have spoken to in ANZ see analytics as future-proofing them against any curve balls that may arise in the business.

“Storage analytics helps them in terms of their capacity planning, historical trends and factoring in data optimisation techniques such as compression and deduplication, which a lot of platforms provide these days.”

Read more about storage in Australia and New Zealand

  • All-flash storage is set for primetime in Australia, with more enterprises turning to the technology to replace spinning disk storage systems at a lower cost than before.
  • Airtasker is using Amazon Web Services to ramp up its storage capabilities to meet the needs of an expanding user base.
  • Projects involving cloud storage and back-up feature strongly for CIOs based in Australia and New Zealand.
  • Australian enterprises are turning to software-defined storage to improve data management and speed up testing and development.

But how keen is awareness among ANZ technology leaders about storage analytics and what it can do? Kalia says most are aware of what the market has to offer, and the challenge is keeping up with the pace of change.

“The market is evolving so rapidly and there is so much competition,” he says. “Everyone is coming up with what might be the same feature, but they are giving it a different name – then that’s the buzzword for the next few months.”

Despite the marketing wars, ANZ is ahead of the adoption curve for storage analytics, says Kalia. “If you look at the Asia-Pacific market, we do tend to take on newer vendors and newer approaches.”

The next two years promise to see increasing demand for storage analytics in Australia and New Zealand.

“With the emergence of AI, machine learning, big data and the internet of things [IoT], we are seeing a lot more projects, especially in that IoT space,” says Kalia. “We are seeing a shift in the conversations. It’s no longer a bottom-up platform – it’s very much an outcome-driven game.”

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