The Noisy Neighbour Problem: Why Cloud Performance Can Be Unpredictable
A virtual machine has eight vCPUs, 32GB of RAM and SSD storage. On paper, it looks more than capable of running a moderately demanding business application. Yet performance varies throughout the day. Database queries that normally complete in milliseconds occasionally take seconds, and users complain about slow responses even though monitoring shows no obvious shortage of CPU or memory inside the guest. One possibility is resource contention elsewhere on the physical infrastructure. It's commonly called the noisy neighbour problem, and it illustrates why virtual machine specifications don't always tell the full story.
What you're allocated isn't always what you receive
Virtualisation allows multiple workloads to share physical computing resources. That's one of its great strengths: it improves hardware utilisation, simplifies management and makes infrastructure more flexible. But sharing resources introduces contention when demand exceeds available capacity. CPU scheduling is one example. A virtual machine can be allocated eight vCPUs without having eight dedicated physical cores continuously available. If the host is heavily oversubscribed, the VM may spend time waiting for physical CPU resources.
The guest operating system might report apparently healthy CPU utilisation while the application experiences scheduling delays. Storage has similar challenges. An SSD-backed virtual disk does not have exclusive access to the underlying storage system, and other workloads can generate substantial I/O demand, increasing queue depth and latency. Memory overcommitment, host swapping, network congestion and shared storage contention can all affect application behaviour. None of these problems is necessarily visible from a simple virtual machine resource allocation screen.
Oversubscription isn't automatically bad
It would be misleading to suggest that resource sharing is inherently wrong. Many workloads have highly variable utilisation patterns. Allocating dedicated physical capacity for every theoretical maximum would leave considerable amounts of expensive hardware idle. Well-managed oversubscription can be perfectly reasonable in the right environment. The issue is transparency: customers should understand whether their resources are dedicated, reserved, shared or subject to contention. Providers should maintain enough operational headroom to deliver the performance expectations established with the customer.
It's a capacity-planning decision, not something that should be hidden behind a marketing description. A lightly used development environment and a heavily loaded production database should not necessarily be treated in the same way, even if the headline virtual machine specifications look similar.
Predictability matters
For production applications, consistency is often more important than occasional bursts of exceptional performance. A business database doesn't become more useful because it performs brilliantly at three in the morning but slows down during the working day. This thinking shapes the KORE VMaaS approach. We favour clearly defined resource allocations, transparent capacity planning and infrastructure designs that don't depend on uncontrolled oversubscription to remain commercially viable.
Performance also needs to be measured where it matters: application response times, storage latency, CPU scheduling and network behaviour. A virtual machine specification is only the beginning of that conversation. The meaningful question is whether the infrastructure can deliver what the application requires, consistently, when the business actually needs it.
