If you’re grappling with ballooning cloud costs, aging infrastructure, sustainability targets, or mounting AI ambitions, you are not alone. Many IT leaders are finding their data centres at a critical crossroads. The question isn’t “if” you modernise, but “how fast.”
The good news? Hybrid cloud architectures have matured and are delivering on the early promises. This is particularly the case with the emergence of true hybrid solutions like Microsoft Azure Local and AI-ready infrastructure bundles.
This is opportunistic timing to explore a new path forward. In this guide to data centre modernisation, we walk through three strategic routes:
The public cloud wake-up call
For years, public cloud adoption was heralded as the gold standard of digital transformation. However, many organisations now realise that simply lifting and shifting workloads into the cloud – particularly legacy virtual machines – has not delivered the cost savings or agility originally promised. In many cases, it has had the opposite effect: unpredictable bills and underutilised services.
The problem isn’t the cloud; it’s how it has been used. Many businesses moved workloads without re-architecting them for the cloud-native environment, which led to inflated expenses and operational inefficiencies. That’s why cloud repatriation is making a comeback.
Putting the right workloads in the right place
Repatriating workloads—bringing them back from public cloud to on-prem infrastructure—is a better option for predictable, steady-state applications. For workloads that are always on and show little variability, running them on local infrastructure can lead to more controlled spending and improved performance.
Modern options like Azure Local (formerly Azure Stack HCI) are enabling a new kind of hybrid model. With Azure Local, organisations can run Azure services on-premises using platforms like Cisco UCS, while maintaining seamless integration with the broader Azure ecosystem. This setup allows for the agility of the cloud with the cost predictability and control of on-prem.
You can test and scale AI models in public cloud, then bring production environments back on-prem into an AI-ready Cisco infrastructure, maximising performance and predictability without blowing your cloud budget.
Key considerations
A catalyst for change
Often, the trigger for a modernisation initiative is straightforward: aging infrastructure. Many data centres are housing equipment approaching, or past, end-of-life – whether it’s networking infrastructure like the first generation of Cisco Nexus switches, or server platforms running outdated operating systems such as Windows Server 2012.
But this kind of trigger can be a golden opportunity. When systems are due for replacement, it’s the perfect time to step back and assess the architecture as a whole. Are you simply upgrading like-for-like, or could you modernise to achieve better efficiency, sustainability, and scalability?
Efficiency, sustainability, and agility
Today’s data centre decisions are driven by more than just performance. Sustainability and carbon reporting are climbing the corporate agenda. Older infrastructure often consumes more power and delivers less performance per watt, while modern platforms offer better energy profiles and support for dynamic scaling.
Containerisation and application refactoring also come into play. By moving to containers or PaaS services, organisations can reduce VM sprawl, improve resource utilisation, and lay the foundation for cloud-native development practices, even if they remain on-prem.
Cisco’s UCS portfolio supports modern workloads with flexibility and integration into hybrid environments. Combined with hyperconverged infrastructure and intelligent networking through Nexus switching, it’s possible to build a future-ready data centre without a complete rip-and-replace.
Key considerations
AI is changing the game – but can your infrastructure keep up?
Few forces are reshaping IT strategy more profoundly than AI. Whether you’re building models, experimenting with machine learning, or simply looking to integrate AI-powered applications, your infrastructure needs are changing fast.
AI workloads differ significantly from traditional enterprise apps. They demand high-density compute, accelerated networking, and massive data throughput, often beyond the capability of legacy systems.
Test in the cloud, scale on-prem
Public cloud environments offer an excellent sandbox for experimenting with AI. They provide access to GPU resources and AI services on demand – ideal for proof-of-concepts or small-scale deployments. However, running AI in production in the cloud can lead to skyrocketing costs.
That’s why many organisations are shifting to a hybrid AI model. Test and train in the cloud, then bring production in-house. Cisco’s AI-ready pods offer a pre-packaged, optimised infrastructure for AI workloads, making it easy to deploy and scale AI in your data centre.
Key Considerations
Whether you’re addressing end-of-life infrastructure, re-evaluating your cloud strategy, or preparing for AI, each journey begins with a simple question: What does your business need next from its data centre?
There is no single “right” answer. You might choose to repatriate now and modernise later. Or perhaps your priority is AI readiness, and modernisation follows from there. The important thing is to start with a clear assessment and a strategic view of where you’re heading.
Let’s map your modernisation journey
As a Cisco Data Centre Architecture Specialised Partner and Cisco APJC Customer Experience Partner of the Year (2023 and 2024), Data#3 is uniquely positioned to help customers proactively navigate a modernisation journey – including end-of-life products in the Cisco Nexus family in a way that suits your needs.
For organisations looking to modernise their infrastructure, reduce data centre costs and focus on sustainability, Data#3 has a comprehensive Data Centre Assessment. Run over 3-5 days (depending on your environment), it’s a detailed, methodical approach to transformation planning.
Alternatively, if AI is your top priority, our AI assessment helps you understand the performance capacity and next-generation architecture you need.
For more details and qualifying criteria, contact us today.