An estimated 6.64 billion people, or 82 per cent of the world’s population, are now covered by some form of data privacy legislation.
In a web of complexity that spans 144 countries, compliance with local regulations and data sovereignty laws are a growing challenge for companies working across multiple geographies.
Alex has over 20 years in the IT industry.
To help ensure local compliance, greater control and security, IT leaders may devote more resources to repatriating data to private cloud computing infrastructures.
In this article, the author explores how organizations can strategically plan their on-premises cloud infrastructure for compliance and modern workloads like AI while also boosting planning and cost predictability.
Private cloud infrastructures: a silver lining
Public clouds continue to remain critical for a majority of businesses as they deliver flexibility and scale, global reach and access, and speed of innovation at a level that private clouds struggle to meet.
However, in certain scenarios, private clouds may be a better option. There are three main reasons why companies worldwide might repatriate their workloads from public to sovereign private cloud infrastructures: security & compliance, new workloads and cost predictability.
Security & Compliance: A Private Cloud Outlook 2025 report found that 92% of respondents trust private cloud for security and compliance, propelling the adoption of private cloud systems. Two out of 3 IT leaders also reported being “very” concerned with storing data in public cloud environments and maintaining compliance. And with an increasing amount of data privacy legislations around the world and the need to comply with them, more and more companies are adopting sovereign clouds.
The EU’s General Data Protection Regulation (GDPR), for example, imposes strict rules for businesses in the EU, or those trading with companies in the bloc, when collecting and handling personal data. For companies bound by these regulations, establishing on-premises deployments can help ensure thorough compliance. As a result, investments in private cloud infrastructures are surging. The worldwide sovereign cloud market, for instance, is projected to grow to over $100bn by 2034, according to Polaris Market Research.
New Workloads: AI is accelerating at an unprecedented pace. Organizations around the world are continuing to invest in the new technology. Generative AI (GenAI) spendings are foreseen to reach 644 billion USDs this year, increasing 76.4% from 2024. And Agentic AI tools are expected to be adopted even faster. But these new technologies are data-hungry beasts.
Especially in enterprise environments, AI experiments are often conducted by several teams, pulling unstructured data from everywhere they can. The more quality datasets you have, the better the result. In doing so, they often trigger petabytes of data moving across the network, causing a spike in capacity and traffic costs. It is not surprising, that analysts predict seven out of ten enterprises using AI say that sustainability and digital sovereignty will become the top criteria for choosing the appropriate cloud systems by 2025.
Cost Predictability: As trends continue to show, enterprise cloud spending is skyrocketing around the world. A “State of the Cloud Report” from 2025 showed that 40% of enterprises spend more than 12 million USDs per year on public cloud – an increase from 36% compared to 2024. Cost management and optimization are becoming key priorities – especially when it comes to avoiding over-provisioning. Most companies therefore value the financial visibility and predictability of private cloud.
Taken together, these factors indicate that companies are now more likely to pick cloud environments – public, private or hybrid cloud – based on workload needs and attributes. Depending on the requirements, private clouds may be more attractive – especially for data-intensive workloads that either demand high security and compliance, speed or are highly integrated with other systems.
Security & Compliance:
Enterprises on cloud nine: On-premises cloud architecture implications
With the workload-first mentality of most organizations, both the importance and expectations of the private cloud have increased. IT management nowadays want the “best of both worlds”. They want the benefits of a public cloud operating model with the control, security, efficiency, and (cost) predictability of an on-premises solution.
Organizations currently looking to repatriate workloads need to consider scalability, flexibility and total cost of ownership (TCO) without compromising on compliance and resilience.
Private clouds allow companies to adapt and scale their on-premises IT architecture to business-specific requirements and workloads, while enabling greater financial transparency, speed and predictability. With sovereign cloud architectures, IT managers can physically “hug” their server if they really want to.
The private cloud approach also supports future-proofing storage infrastructure, as on-premises IT infrastructures unlock the emerging ability of storage disaggregation, which public cloud providers have been using for years.
Storage disaggregation: the blue sky thinking for enterprises
Not long ago, it was common for organizations to expand their storage capacity by buying new servers. After maxing out the typical three-year warranty on a server, IT managers often choose to simply replace the entire server (along with the processors, random-access memory, and flash storage). For the time, this thinking made sense, but it was a wasteful and costly value proposition.
Decoupling storage and compute – disaggregating storage – and placing them on separate racks eliminates the problem associated with scaling through the purchase of new servers, as storage and compute can now scale independently.
Especially in on-premises cloud architectures, disaggregated storage makes it easier for multiple servers to share the same storage pool, helping organizations use resources more efficiently.
So, instead of investing in servers loaded with maximum storage, the nimbler approach is to disaggregate and extract storage from a pool and assign it to applications as needed. As projects ebb and flow, the demand for storage resources transfers from one part of the workflow to another.
But disaggregation doesn’t only assist in creating more efficient data resource management. It also increases the flexibility to adapt to rapidly changing needs brought on by new applications (e.g., GenAI or Agentic AI), data sets and use cases. Disaggregation also creates the opportunity to scale storage resources according to changes to the business over the course of time.
While anticipating storage, CPU, GPU, and networking needs still isn’t easy to predict, disaggregated storage can eliminate the need for private cloud IT departments to make big, long-term bets on purchasing expensive servers loaded with storage.
Instead, it enables them to scale compute, GPU, and storage capacity independently. It also supplies the IT managers with more freedom to change their resource allocations on the fly.
Time to go private?
There’s no shortage of opinions and resources telling why companies should or should not repatriate their data and workloads. And there is no one-size-fits-all approach.
Security, compliance, independent scalability, cost, performance, location and talent all must be carefully considered before deciding if a sovereign private cloud architecture is the right choice for the business or the specific applications.
While on-premises solutions offer greater control, and can lead to better planning and cost predictability, public cloud solutions provide quick(er) scalability and ease-of-use.
At a time of unprecedented data growth and increasingly intensive workloads, the private cloud architecture route can become an attractive alternative for those seeking greater control over data, cost predictability and data access.
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