Nutanix details infrastructure for streamlined workload portability in era of containerization & AI
First, the cloud grew.
Then, after a period of widespread adoption that eventually led to mass-market acceptance and a groundswell of platform-level standardisation that took us through the “growing pains era” where security was merely a bolt-on afterthought, we started to build out hybrid multi-cloud realities.
The period of rational reality on the evolutionary curve of the cloud saw distributed computing deployments diffuse outwards from on-premises computing environments across mobile, between remote multi-cloud instances of all disciples… and then throughout the edge-compute firmament that forms the internet of things.
But even with the gargantuan weight of momentum that coalesced all these forces, there is still much change afoot in cloud.
Hybrid multi-cloud computing company Nutanix points to the next phase of growth in this arena with the UK findings of its seventh annual Enterprise Cloud Index (ECI) survey and research report.
Containerisation & generative AI
Ask a passing stranger what the two or three most visibly still-nascent and pertinent bellwether technologies are in the enterprise computing space and they’ll probably say Kubernetes and generative intelligence models. Okay, make sure you ask a passing stranger in Santa Clara or somewhere near Europe’s major IT hubs including London, Paris, Berlin, Stockholm and so on – but regardless, the point is made i.e. containerisation (and the world of Kubernetes) and generative (let’s not also forget predictive and reactive) AI is at the fore of modern IT progression.
What that means in this Nutanix study is that figures specifically from UK organisations suggest that more than 90% are at least in the process of containerising their applications and 91% state they are making live production use of generative AI tools and services (in one form or another) today.
With almost a third (32%) of British firms stipulating that all newly developed applications are containerised, this outpaces the global average of 27%. Given that containerisation is widely agreed to be the foundation of modern, scalable and efficient cloud-native application development, we might suggest that UK organisations are positioning themselves for greater agility, portability and automation.
However, says Nutanix, a “significant skills gap” threatens to slow progress, with only 42% of IT leaders confident in their teams’ ability to support cloud-native adoption. To bridge this gap, UK businesses are prioritising skills investment, with 59% actively hiring for container and cloud-native expertise
“The UK is at a pivotal moment in its generative AI adoption journey. While organisations are eager to leverage AI-driven productivity and automation, security, integration with existing infrastructure, and skills shortages continue to slow progress,” said James Sturrock, director of systems engineering at Nutanix. “The findings from this year’s ECI highlight the need for a strategic approach that ensures secure, scalable, and well-governed AI implementations. A hybrid multi-cloud foundation and strong data security and governance frameworks will be critical in moving from early experimentation to real-world impact. This [current UK] focus on talent development will be critical in sustaining momentum and ensuring containerised applications move seamlessly from development to production.”
The UK is keeping pace with global counterparts in GenAI adoption, with 91% of organisations already using the technology.
Pilot-to-production pitfalls
However, true maturity remains elusive as 37% of UK respondents are reportedly still in the early stages of developing a generative AI strategy, compared to just 13% globally and 15% in EMEA. This approach reflects real-world concerns as UK decision-makers navigate key roadblocks and pitfalls that stand in the way of scaling generative AI from pilot to production.
Security, compliance and IT infrastructure readiness remain pressing issues, while a lack of in-house expertise further complicates progress.
Nutanix’s Sturrock: A strategic approach to containers & gen-AI ensures secure, scalable and well-governed implementations.
Looking at the state of the nation then, Nutanix says that overcoming these hurdles requires a deliberate shift, including investing in generative AI-ready infrastructure to more proactively address security concerns. With 72% of UK organisations expecting positive ROI from generative AI projects in the next three years, Sturrock and team insis that the focus must shift from experimentation to execution.
Other key findings in the 2025 report include the fact that cloud-native momentum is growing because of infrastructure gaps, so UK organisations are prioritising investment in modernising IT environments to fully support cloud-native applications and containers, ensuring long-term scalability and efficiency.
With 86% of UK organisations acknowledging room for improvement in securing GenAI models, there is clear intent to enhance data protection and governance, laying the groundwork for trusted AI adoption
“As UK enterprises accelerate their cloud-native transformation, containerisation is becoming the backbone of modern application development. However, gaps in Kubernetes adoption and persistent data silos indicate that many organisations are still struggling to operationalise these technologies at scale. To fully harness the potential of cloud-native and AI workloads, businesses need a consistent, hybrid multi-cloud operating model that simplifies deployment, enhances security and ensures workload portability across environments,” said Sturrock.
Other findings here point to the news that regulatory and compliance hurdles remain a challenge for UK organisations, with 46% citing these concerns as a key factor in scaling generative AI workloads from development to production. Further here we can see that there is a recognition of how some 62% of UK organisations face challenges with siloed data, so there is a growing focus on integrated, hybrid multi-cloud strategies that enable data access and AI-driven insights.
A profound shift
Taking this now seasonably established market study and survey at face value, it appears to be the case that the UK market in particular is eager to capitalise on the potential of generative AI and cloud-native applications. But, despite the positive face, the nation does face fundamental challenges in skills, security and infrastructure readiness.
Nutanix tells us that the widespread use of containers and Kubernetes signals progress, yet the fragmented approach to deployment – combined with persistent data silos – suggests organisations are still grappling with how to manage and scale these environments efficiently.
What does all this mean for the average cloud deployment? It is (as Nutanix has suggested) a profound shift towards realising the importance of investment in AI-ready infrastructure, security and upskilling initiatives. There’s a simple reason why the term “platform engineering” is becoming so widely popularised and it’s because of the cloud, it’s because of service-based computing models and it’s because of the need to embrace higher-level orchestration technologies (did somebody mention Kubernetes?) that we can use to corral, coalesce and control otherwise disparate data silos.
On the one hand, there’s discombobulated data repositories in badly governed inefficient data execution environments. On the other hand, there’s streamlined workload portability for secure, scalable and efficient operations in a unified cloud operating model.
Which sounds better?
Nutanix president & CEO : Rajiv Ramaswami