Operations | Monitoring | ITSM | DevOps | Cloud

Building smarter with AI: Why legacy infrastructure is the biggest bottleneck

Josh Mesout (Chief Innovation Officer at Civo) took the main stage at Civo Navigate London 2025 to deliver a critical message: The AI revolution isn't just coming, it's here, and the way companies are built is changing faster than ever before. His session cut through the hype, delivering hard data on what separates the companies that scale AI from the ones that sink money into failed prototypes. The takeaway is blunt: The biggest threat to your AI ambition isn't the model; it’s your infrastructure.

What we learnt about digital sovereignty at Civo Navigate London 2025

The concept of digital sovereignty has become increasingly important in today's technology-driven world. As organizations rely more heavily on cloud services and artificial intelligence (AI), they face new challenges in maintaining control over their data and IT resources. At Civo Navigate London, we brought together industry leaders to discuss the topic of digital sovereignty and its implications for the cloud industry.

The sovereignty of the builder: Lessons from Civo Navigate London 2025

Digital sovereignty isn’t won in policy papers. It’s earned in production. That was the challenge issued by Civo CEO Mark Boost and Board Director Kelsey Hightower at Civo Navigate London 2025. They argued that the cloud's real failure lies not with the providers, but with the customers who refused to change. Catch up on the full fireside chat below The power shift is underway, moving from large vendors back to the practitioner.

Decoding cloud credits: Are "free" credits locking you in?

“Free" cloud credits, they sound like a gift, but they often come with hidden costs and an agenda: lock-in. The illusion of a cost-saving measure can quickly become a vendor-specific trap, forcing costly migrations or leaving your business overpaying for cloud services. This issue, which the UK Competition and Markets Authority (CMA) estimates contributes to £430M of annual over-payments in the UK alone, is what we call the "cloud credit trap.".

Sovereignty over silence: Why Microsoft's data opacity is the real lock-in

The refusal by Microsoft to detail data flows to Police Scotland confirms the real price of hyperscale: control is an illusion. This incident isn't the problem. It’s the proof. It proves the need for a new standard in cloud computing, one that prioritizes true digital sovereignty and architectural transparency. Sovereignty, after all, is all about the customer being able to exercise control over the IT resources they use.

Navigating the geopolitical maze of digital sovereignty at Civo Navigate London 2025

Trust in Big Tech is eroding. Geopolitical tensions are rising. The only predictable thing about the cloud today is that it’s time to re-evaluate everything. At Civo Navigate London 2025, we pulled together a panel of industry experts to cut through the noise and finally define what digital sovereignty means for the UK.

The hidden costs of "free" cloud credits: A wake-up call for businesses

To read the full findings from this research, visit our whitepaper "Decoding Cloud Credits" by clicking here. The allure of "free" cloud credits can be tempting, but beneath the surface lies a complex web of risks and consequences that can ultimately lock businesses into costly and restrictive cloud ecosystems. Our latest whitepaper, "Decoding Cloud Credits", explores the true costs of these promotional offers and the implications for businesses.

What we learnt from our panel discussion on AI in the UK

At Civo Navigate London 2025, we hosted a panel discussion with Josh Mesout, James Faure, Abdul Hummaida, Jonas Vermeulen, and Daniel Miodovnik to discuss the latest trends and challenges in AI adoption. Through this conversation, the panelists covered topics such as the current state of AI adoption to the challenges of scaling AI, and the future of work.

Why your Kubernetes clusters and GPUs should live under one roof

The world remains abuzz with AI hype, but the reality is that most modern applications aren’t purely AI workloads. The average company will have web services, APIs, databases, and background jobs running alongside its machine learning inference or training components. An architecture question everyone faces: should your Kubernetes cluster and GPU compute live in the same data center, or can you split them across providers?