Cloud vs colocation: key questions for IT and infrastructure decisions
Cloud computing and colocation are two common approaches for running business infrastructure in external data centre environments. Cloud services typically run from large-scale cloud data centres, while colocation allows organisations to place their own hardware inside professionally operated facilities. Each model offers different levels of control, flexibility and operational responsibility.
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How secure is cloud computing for critical data?
Security in cloud computing comes down to controls across infrastructure, networks, identity, monitoring, and recovery, with UK data residency included where regulatory or governance requirements depend on hosting location. This FAQ addresses how cloud computing security protects critical and regulated data across infrastructure, networks, identity, monitoring, and recovery controls.
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What is edge colocation and when does it make sense?
Edge colocation places infrastructure across multiple data centre locations to support application performance, connectivity and operational requirements. Instead of relying on a single centralised site, organisations deploy workloads in regional facilities closer to where data is generated or used. This FAQ explains what edge colocation is, how edge data centres work, and when this approach fits infrastructure strategy.
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Where is cloud data stored and how does it work?
Cloud storage services run on physical infrastructure hosted in data centres. While data is accessed through cloud platforms, it is stored on hardware located in specific facilities and regions. This FAQ explains where cloud data is stored, how cloud data storage works, and why location, connectivity and control matter when managing data in the cloud.
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What is hybrid cloud computing and who needs it?
Hybrid cloud computing allows organisations to operate workloads across a combination of private infrastructure, public cloud platforms, and, where required, existing on-premise systems. It is typically adopted when a single environment does not meet operational, regulatory, performance, or continuity requirements. This FAQ explains how hybrid cloud computing works, how it compares with cloud computing vs on-premise infrastructure, and how cloud computing hosting providers and managed services support hybrid environments.
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Why does location matter when choosing a data centre?
Cloud services and digital platforms still depend on physical infrastructure hosted in data centres. Where that infrastructure is located affects how applications connect to users, how networks are routed, and how organisations manage resilience across sites. This FAQ explains why location matters when choosing a UK data centre, how regional data centres support infrastructure strategy, and why many organisations look for facilities close to their operations when placing critical workloads.
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Business benefits of colocation
Colocation allows organisations to place their own servers and IT equipment in a secure, professionally managed data centre environment. Instead of maintaining infrastructure on-site, businesses use a specialist facility that provides power, cooling, connectivity and physical security.
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Colocation data centre pricing: UK cost and ROI
Colocation pricing depends on how infrastructure is deployed, how much power it consumes, and how it is connected. Rather than a single fixed cost, organisations typically assess pricing alongside total cost of ownership (TCO) and return on investment (ROI) to understand long-term value. This FAQ explains how colocation pricing works in the UK, what drives costs, and how organisations evaluate ROI when comparing colocation with other infrastructure options.
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Cloud service models explained: IaaS vs PaaS vs SaaS
Cloud computing services are typically delivered through three main service models. Each model defines which parts of the technology stack are operated by the provider and which remain under the customer’s control. This FAQ explains the differences between infrastructure, platform and software services, and how organisations choose between IaaS, PaaS and SaaS when planning cloud environments.
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What is cloud Infrastructure as a Service (IaaS)?
Cloud infrastructure as a service (IaaS) provides on-demand compute, storage and networking, while leaving you in control of the operating system and application layer. For UK organisations, IaaS decisions often come down to operational ownership, audit readiness and where infrastructure is hosted. This FAQ sets out what IaaS includes, who it suits, how responsibility is typically split, and what to look for when comparing IaaS cloud solutions.
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What is a Tier 1–4 data centre?
Data centre tiers are used to classify infrastructure based on resilience, redundancy and expected uptime. The most widely referenced framework is the tier classification model, which defines four levels of data centre design from basic capacity to highly resilient environments. This FAQ explains how data centre tier classification works, what distinguishes each tier, and how organisations use these classifications when selecting infrastructure.
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Is colocation right for my business?
Colocation is used by organisations that need reliable infrastructure without operating their own data centre facilities. The most geographically diverse colocation provider in the UK, Pulsant offers purpose-built data centre environments where businesses can place equipment while retaining control over systems, configuration and performance. This FAQ explains why businesses use colocation, when it makes sense, and how to assess whether it fits your infrastructure and operational requirements.
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Edge Data Centres vs Traditional Data Centres: What's the Difference?
The distinction between edge data centres and traditional data centres matters more as businesses move away from centralised infrastructure toward models that prioritise speed, proximity and flexibility. Our platformEDGE network brings together 14 interconnected UK edge data centres, connected by a private 100Gbps network and accessible from every major UK region. This FAQ covers the key differences and how they affect infrastructure decisions.
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How AI and Cloud Computing work together
AI workloads place demands on infrastructure that traditional cloud environments were not originally designed to meet. As UK organisations move from AI experimentation into production, the relationship between AI and cloud computing, where workloads run, how data moves, and how performance and compliance are maintained, becomes a practical infrastructure question. This FAQ covers how AI and cloud computing work together, and what that means for how infrastructure needs to be designed and placed.
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How to choose a UK colocation provider
Choosing the right colocation provider affects how your infrastructure performs, scales and is governed over time. With a range of data centre colocation providers across the UK, the decision comes down to more than price. Location, connectivity, resilience, certifications and the provider's ability to grow with your business all play a role. Pulsant operates 14 interconnected data centres across the UK, making it the most geographically diverse colocation provider in the UK. This FAQ covers what to look for and how to evaluate your options.
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What security should a data centre provide?
Data centre security covers everything from who can walk through the door to how the facility responds to a power failure at 3am. For organisations housing critical infrastructure, understanding what security a data centre should provide is as important as evaluating connectivity or pricing. Pulsant operates 14 UK data centres built to enterprise security standards, holding ISO 27001, PCI DSS and Cyber Essentials accreditations across the estate. This FAQ covers the security layers you should expect from a well-run facility
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Colocation data centre pricing: UK cost and ROI
Colocation pricing depends on how infrastructure is deployed, how much power it consumes, and how it is connected. Rather than a single fixed cost, organisations typically assess pricing alongside total cost of ownership (TCO) and return on investment (ROI) to understand long-term value. This FAQ explains how colocation pricing works in the UK, what drives costs, and how organisations evaluate ROI when comparing colocation with other infrastructure options.
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Preventing data breaches in cloud & colocation
Preventing data breaches in cloud and colocation environments takes more than adding another security product. Risk often builds through weak access controls, inconsistent settings, poor visibility across platforms, or gaps in the way sensitive data is handled. Those issues become harder to manage when workloads are spread across cloud, colocation, and hybrid estates. These FAQs look at practical ways to reduce breach risk across modern infrastructure. They cover common threat areas, stronger security controls, and how resilient UK-based environments can support governance, containment, and recovery.
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What is managed IaaS
Managed IaaS sits between self-managed public cloud and fully hands-on infrastructure. It gives organisations on-demand infrastructure with operational support around the service, which is why it often comes into the conversation when teams are reassessing cost, performance, or control. These FAQs explain what managed IaaS includes, how it differs from DIY cloud, and why cloud repatriation has become a more active strategy for some workloads. They also show how UK-hosted infrastructure can support sovereignty, compliance, and more predictable operations.
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What are the biggest data centre security threats today?
Data centre security threats are increasingly driven by highly interconnected infrastructure. Security risks now extend beyond traditional firewalls to include APIs, cloud integrations, remote management tools, and building systems. The most significant threats fall into two categories: cybersecurity attacks (such as DDoS and API exploitation) and physical security risks (such as unauthorised access and compromised building management systems). Even small configuration errors can now create serious vulnerabilities due to system interdependence.
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Choosing the best cloud service for enterprise AI workloads
Choosing a cloud service for AI workloads at enterprise scale involves more than comparing GPU availability or price per hour. Data location, network performance, security architecture and how a workload will actually run in production all shape whether a platform holds up once AI moves from pilot to live use. Pulsant supports enterprise AI workloads across cloud services hosted in UK data centres, with private connectivity between sites through Edge Fabric. This FAQ covers what to look for when evaluating cloud based AI platforms and how infrastructure decisions affect performance, security and cost.
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What is managed cloud?
Managed cloud combines cloud infrastructure with day-to-day operational support delivered by the provider. Patching, monitoring, capacity planning and incident response sit with the provider, so internal teams are not carrying the full weight of running the environment themselves. Pulsant delivers managed cloud through UK-hosted cloud services, backed by connectivity across 14 UK data centres. This FAQ covers what managed cloud includes, how to choose a provider, and why it suits organisations with strict operational or compliance requirements.
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Q: What makes a cloud service suitable for enterprise AI workloads?
A: An enterprise AI workload needs infrastructure that can handle variable compute demand, move large volumes of data without bottlenecks, and keep latency low between the model and the systems it depends on. Beyond raw compute, the platform needs security controls, data governance and network architecture built for scale, not just a GPU instance with a billing model attached.
Q: What is the difference between training and inference infrastructure requirements?
A: Training workloads are compute-intensive and can often run in large centralised environments where proximity to users matters less. Inference is different. It typically needs to sit closer to where data is generated and where users interact with the application, because latency has a direct effect on response times and user experience. Enterprises increasingly need infrastructure that supports both models rather than defaulting everything to one environment.
Q: How does data location affect AI cloud platform choice?
A: Where data is processed and stored determines which legal jurisdiction applies and how easily an organisation can evidence compliance. For AI workloads handling sensitive, regulated or customer data, UK based infrastructure keeps that data under UK jurisdiction and simplifies audit and governance requirements. This becomes more significant as AI systems draw on larger and more sensitive data sets.
Q: What role does AI play in cloud security?
A: AI for cloud security typically means using machine learning to detect anomalous behaviour, flag unusual access patterns and identify threats faster than manual monitoring allows. It supports existing security controls such as access management and network monitoring rather than replacing them. The underlying infrastructure still needs strong baseline security, since AI-driven detection is only as effective as the environment it is monitoring.
Q: Does running AI workloads change an organisation's cloud security requirements?
A: Yes. AI workloads often process larger and more varied data sets than traditional applications, which widens the attack surface. Model access, training data and inference outputs all need their own access controls and monitoring, in addition to the security measures applied to the rest of the infrastructure. Providers offering AI and cloud solutions should be able to show how their security model accounts for this.
Q: Should AI workloads run in public cloud, colocation, or a hybrid setup?
A: It depends on the workload. Public cloud suits workloads with unpredictable or bursty compute demand, such as periodic training runs. Inference workloads with strict latency requirements, or those processing regulated data, often perform better in an environment with tighter control over placement, such as colocation or managed infrastructure. Many enterprises run a hybrid model, matching each workload to the environment it actually needs.
Q: How does network connectivity affect AI workload performance?
A: AI workloads frequently need to move large data sets between storage, compute and the applications consuming model outputs. Slow or inconsistent connectivity between these points creates bottlenecks that undermine performance regardless of how powerful the compute layer is. Private, high-bandwidth connectivity between sites and cloud platforms, such as Pulsant's Edge Fabric, keeps that data moving without relying on the public internet.
Q: What should organisations look for in an AI and cloud infrastructure provider?
A: Assess whether the provider can support both training and inference requirements, what data residency options are available, how connectivity between environments is managed, and what security and compliance credentials are in place. Ask for evidence rather than headline claims, particularly around latency, data location and how workloads are isolated from other tenants.
Q: How does UK data sovereignty apply to AI workloads?
A: AI workloads often draw on larger volumes of data than traditional applications, which raises the stakes on where that data sits and who can access it. UK data sovereignty means data used in AI systems stays within UK jurisdiction, subject to UK law. For regulated sectors, this reduces ambiguity around compliance and makes it easier to evidence data handling to auditors. All of Pulsant's 14 UK data centres are UK owned and operated.
Q: Can existing infrastructure be adapted for AI workloads, or does it require a new environment?
A: Many organisations can extend existing infrastructure rather than starting from scratch, particularly where colocation or managed IaaS is already in place. The key considerations are whether current connectivity can handle AI data volumes, whether compute can be scaled for training and inference, and whether security and governance controls extend to cover new AI-specific risks. A phased approach, adding AI-specific capacity where it is needed, is often more practical than a full infrastructure rebuild.
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