The latest implementation was the NCM Cost Governance solution.
Canberra-based managed services provider (MSP) Qirx has used the Nutanix Cloud Platform to help the University of Canberra (UC) optimize its cloud capabilities.
The project has seen the university slash its infrastructure needs, improve its carbon footprint, and set the foundation for its AI artificial intelligence (AI) research offering.
The MSP and UC have worked together for at least a decade, with the university referring to the business as its technology partner. UC has more than 15,500 students, academics, researchers, and professional staff and has utilized Nutanix technology since 2013.
“Qirx has been a very stable partner for us,” said UC CIO Matt Carmichael. “When we originally went to Nutanix, they were brave enough right at the beginning because it was such a new technology; they were early adopters in bringing that to the table. We bought our first cluster from them and have procured through them ever since.”
While UC’s cloud/network architecture comprises several elements of the Nutanix Cloud Platform, the latest implementation was the vendor’s NCM Cost Governance solution – one that Carmichael said had an immediate impact on its cloud usage.
“We have a small IT team, and the tool gives us a single pane of glass to monitor our usage across Azure, AWS, and Google Cloud, automatically alerting us to any ‘gotchas’ where spend might tick up and we don’t know why,” he said. “That has saved us a couple of times. One instance was when our backups in Google Cloud weren’t being aged out appropriately, increasing our bills exponentially. We quickly got it back in line with Nutanix technology.”
Carmichael said these cost savings were just the tip of the iceberg, as previous implementations had reduced the university’s IT expenses and infrastructure needs.
“Using Nutanix to implement our private cloud was a major reason we were able to replace our disaster recovery (DR) datacentre with a micro data center,” he said. “This meant when we needed a new DR facility, it only required three racks of space, instead of the existing 24 – this led to upfront financial savings of around $2 million and ongoing savings in operational costs and energy usage.”
“Further, we’ve been able to consolidate the server and storage assets we need by 78%, which led to an additional projected saving of more than $1.5 million as we didn’t have to purchase all that new equipment.”
Carmichael said that as existing infrastructure reached the end of its lifecycle, workloads previously running on three-tier architecture were migrated to Nutanix.
More than 90% of the UC’s core applications run on Nutanix Cloud Platform, including the key student management, finance, human resources and database systems.
“What we saw as we migrated more workloads to Nutanix was massive consolidation in the IT hardware we needed – we saw shrinking in our data center footprint requirements almost immediately,” he said.
“It was also much easier to manage and support, particularly with seamless one-click upgrades. Previously, our traditional infrastructure meant we had all these hoops you had to jump through.”
While the financial and operational savings have enabled UC to invest in enhancing the student learning experience, Carmichael said one of the greatest benefits had stemmed from improving the quality of its teaching in AI and deep learning.
“We recently added undergraduate specialist majors in robotics, AI and data science, a Masters of Data Science and post graduate specializations in AI and machine learning. To teach these courses effectively requires a significantly increased capacity for GPU-enabled computing resources,” Carmichael said.
“With Nutanix end user computing (EUC), students are able to work on their lab work, assessments and research from anywhere without requiring excessively expensive terminals – they can use their normal laptops, log in to the VDI portal and access all the computing resources they need,” Carmichael said. “Improving the student experience by offering a flexible, remotely accessible teaching environment with enough computing resources for AI and deep learning is one of the strategic goals of the Faculty of Science and Technology.”
Carmichael said postgraduate researchers – such as those conducting research at the university’s Visual and Decision Analytics Lab (VIDEA) and the Australian Geospatial Health Lab (AGeoH-L) – were also able to easily access all the computing power they required as Nutanix’s platform enables them to scale up or down as needed in UC’s research cluster.
