The rush to digitalise has pushed businesses to move to the cloud, though, there remain nagging concerns about vendor lock-in and their ability to move between different cloud environments. In their efforts to address these issues, both Google and Oracle are touting service offerings that they say will ensure openness and flexibility.
And as adoption grows, can cloud's core components become commoditised and go the way of network pipes, with focus shifting to value-added service delivery as it did for telcos?
Chris Chelliah, Oracle's group vice president and chief architect of core technology and cloud, believes so, pointing to compute and storage as components that are likely to become commoditised.
Value then would have to be driven around data and data management as well as collaboration tools, he said, clearly touting Oracle's heritage. Chelliah underscored the importance of the vendor's "differentiated services" around autonomous databases since data would be coupled with cloud compute and would power artificial intelligence (AI) and machine learning applications.
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He also pointed to the vendor's software-as-a-service (SaaS) offerings, such as enterprise resource planning (ERP) and customer relationship management (CRM), which he said would help drive its cloud offerings as organisations modernised their supply chains.
Oracle currently runs 29 cloud regions worldwide, including in Japan, Australia, and India, with plans to add another nine by July this year that will include Singapore. A year ago, it had 19 regions, having added one every 26 days, Chelliah said. He said the expansion was fuelled by strong customer demand for data centres that were as close in proximity to their location as possible.
Google Cloud's Asia-Pacific vice president Karan Bajwa, though, believed cloud still was far from commoditisation and provided the foundation for multiple components such as compute and networks. He noted that price-points would continue to see downward pressures as more users hopped on board and hyperscalers saw greater adoption, adding that just 20% of enterprise workloads today had moved to the public cloud.
There remained significant growth potential amongst enterprises that needed to gain the confidence to move the remaining 80% workloads to the cloud, Bajwa said, pointing to the global pandemic as a driving factor pushing these businesses to overcome their initial fear to migrate.
Other key issues also needed to be addressed such as ensuring they could retain flexibility and openness as more workloads were migrated. he noted that CTOs were especially concerned about cloud lock-in and would want to work with providers that did not restrict their ability to move between platforms or services.
Here, Google looked to differentiate itself with offerings such as Anthos, which he said enabled businesses to manage containerised hybrid- and multi-cloud workloads across different environments such as on-premise, Amazon Web Services (AWS) and Microsoft Azure.
"They're moving from an [on-premise] environment that they could control within their own four walls, to one that is a public environment. They want to be assured this will not lock them to one provider and will be multi-cloud," he said.
Chelliah, too, touted Oracle's pledge to provide an "open, secure" platform that supported workloads across different environments including on-premise and multi-cloud. He named Zoom and Nissan as amongst customers that had deployed their own ISV (independent software vendor) and cloud-native applications on Oracle's platform.
Commenting on a 2018 ZDNet report in which analysts had noted Oracle's lack of a multi-cloud strategy, he said the vendor's focus had always been to give customer's choice and not lock them in. This, he said, was critical to foster innovation and customer loyalty. "Oracle has, in fact, been leading the charge amongst the hyperscalers to drive multi-cloud portability," he adde.
He noted that the vendor had rolled out cross-cloud connectivity with Azure, currently running an interconnect out of Tokyo for the region, and worked with VMware to speed up the latter's workloads to OCI (Oracle Cloud Infrastructure). Chelliah added that Oracle customers could provision VMware workloads in cloud in under three hours as well as move these on-premise workloads with rules and policies intact, without the need for refactoring.
He added that Oracle further differentiated its cloud services by enabling organisations to operate isolated networks across tenancies and with consistent service level agreements. Supported on OCI, he said this capability was not on the roadmap of other hyperscalers in the industry, such as Alibaba and Huawei.
With the cloud market still largely untapped, though, Bajwa noted that there had yet to be clear leaders in the region, when asked about competition from Asian players including Alibaba and Huawei as well as others such as Oracle that were broadening their cloud offerings.
"This is a marathon with many laps before we decide who's the winner," he said, adding that Google believed it had "strong proposition" with its continued investment in building out its infrastructure and ecosystem.
The US vendor's cloud business, which includes Google Cloud Platform and Google Workspace, in the fourth quarter of 2020 chalked up $3.83 billion in revenue on losses of $1.24 billion. For its full fiscal 2020, cloud accounted for $13.06 billion in revenue, up 47% from $8.92 billion in 2019.
With 2020 a "watershed" year for digital adoption, he said cloud in future would not simply be about infrastructure but driving transformation and innovation.
Enterprises were looking for customised industry-specific applications, Bajwa said, adding: "The cloud isn't horizontal anymore."
He noted that growing demand for immersive applications, which were latency sensitive, would be better supported in future as commercial 5G networks rolled out and this could change how organisations consumed services online. Telcos, for example, would be able to offer far beyond voice-centric services and push more bandwidth-intensive applications to the edge, at scale, such as data analytics and artificial intelligence.
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