Every industry has its obsessions. In finance, it is yield. In marketing, engagement. In cloud computing, it is latency, the modern equivalent of chasing the sound barrier. We talk about it endlessly, measure it obsessively, and promise to “reduce” it as though it were a form of personal guilt.
Yet for all this talk, latency remains widely misunderstood. It is not a disease to cure or a villain to defeat. It is a fact of life. A side effect of time, distance, and the human insistence on putting servers in one country and users in another.
When people say, “We’ve solved latency,” they are usually lying. What they’ve done is relocate the problem somewhere else.
The Distance Between Desire and Data
The internet’s great strength, its ability to connect everyone, is also its flaw. The further apart those connections stretch, the slower they become. A request that leaves your phone in Bristol, travels through a regional edge node, and ends up on a server in Dublin does not move at the speed of thought. It moves at the speed of light in fibre, slowed by routers, handshakes, and the occasional poorly written function.
For most workloads, those milliseconds mean nothing. But in others, such as gaming, industrial monitoring, and financial trading, they decide who wins and who loses. That is where the myth of “zero latency” was born. It sounds impressive until you realise that even physics refuses to cooperate.
The only real solution is not to fight distance but to reduce it. Hence, the rise of the edge.
The Edge as the New Centre
The idea of putting computing power closer to the user is not new. What has changed is the scale. Sensors, gateways, and micro data centres are now scattered across cities like modern lighthouses, each guiding packets of data home with slightly less delay than before.
Edge computing is the elegant compromise between centralisation and chaos. It brings responsiveness without abandoning control. In practice, it is messier. Once you distribute workloads, you also distribute your problems: patching, compliance, and cost.
Still, it is progress. Better a complex system that works locally than a simple one that fails globally.
Hybrid Thinking
“Hybrid cloud” used to mean running half your servers in someone else’s building and calling it innovation. Today, the term has matured. It now describes a continuum between on-premises, cloud, and edge. Each layer exists for a reason: control, scale, and proximity.
The most innovative organisations are not asking whether to use one or the other. They are asking what belongs where. Real-time decision logic may live on the edge, while analytics and storage live in the cloud. The trick lies in orchestration, making it all behave as one.
That orchestration is where many strategies collapse. Without visibility, workloads wander. Costs blur. Data sovereignty turns into a guessing game. It takes discipline to manage systems that are designed to move constantly.
But then again, discipline is what separates engineering from improvisation.
Redefining Performance
Performance once meant speed. Now it means appropriateness. The right system responds quickly enough, but it also scales, recovers, and stays affordable. Those goals sometimes contradict one another.
I often meet teams who treat latency like a competition, as though shaving off two milliseconds justifies any expense. In reality, most applications gain nothing from such zealotry. For most users, “fast enough” is indistinguishable from “instant.” The rest is ego.
The better question to ask is not “how fast can we go?” but “how smartly can we run?” Intelligent architecture, not hardware horsepower, wins the modern latency race.
The Economics of Delay
Once, reducing latency meant private lines and dedicated infrastructure, luxuries only telecoms giants could afford. The cloud has democratised it. Containerisation, serverless frameworks, and distributed message queues let any developer position compute power exactly where it matters.
This shift has turned latency into an economic factor, not just a technical one. Faster services retain users. Slower ones leak revenue. Providers now compete on regional reach and edge presence with the same fervour they once reserved for uptime.
The result is a quiet truth: latency is no longer an IT metric. It is a business metric in disguise.
Visibility Is the Real Accelerator
You cannot improve what you cannot see. Modern observability tools finally expose latency in all its awkward layers. They trace the path from browser to backend, pinpointing where requests pause, retry, or fail.
The difference this makes to operations is enormous. Teams no longer argue about “where the problem might be.” They can prove it. When you measure precisely, you make better choices about caching, routing, or refactoring.
In many ways, observability has replaced instinct as the engineer’s primary tool. There is no longer any excuse for ignorance, only for inaction.
Regulation and Reality
For those of us in Europe, latency sometimes has less to do with fibre and more to do with law. Data protection requirements dictate where workloads can live, even when the fastest option sits across a border.
This is why technical design and legal compliance must share the same table. The two are no longer separate discussions. Good architecture anticipates regulatory constraints, using hybrid or regional models to balance speed with certainty.
When compliance is built into the map, you move faster, not slower. You know where the boundaries lie, and that clarity saves time later.
Artificial Intelligence, Real Proximity
Machine learning has added a new dimension to latency. Training models still requires heavy computing, but once trained, they must operate close to their data. No one wants to wait half a second for a prediction that should take ten milliseconds.
Running inference at the edge changes the dynamic. Fraud detection, quality control, and voice recognition can happen locally while updates and retraining flow from the cloud. The architecture becomes cyclical rather than hierarchical.
It is a small but vital detail in the broader story of computing’s decentralisation. Intelligence is no longer housed in one place; it is distributed, learning at the edge and teaching in the cloud.
The Human Side of Speed
All this talk of networks and nodes hides a simple truth: latency is experienced by people. A slow checkout page frustrates a shopper. A delayed sensor reading worries an engineer. A lagging video call makes a conversation feel less human.
Performance is empathy in disguise. It’s the recognition that time has value. Engineers who remember this tend to build better systems, not because they write better code, but because they understand what delay feels like.
That awareness is the quiet skill that separates functional software from great software.
The Final Millisecond
Chasing low latency is like chasing enlightenment. You never quite reach it, but the pursuit itself teaches you discipline.
The goal is not to eliminate delay entirely but to make it irrelevant. When systems are designed with intelligence, placing workloads where they belong, measuring what matters, and treating time as a shared responsibility, latency stops being the enemy. It becomes part of the design language.
The future of the cloud is not further away; it is closer, distributed, and quietly aware of its own limits. The companies that grasp that truth first will move faster than anyone else, not because their servers are nearer, but because their thinking is.
Andrew McLean is the Studio Director at Disruptive Live, a Compare the Cloud brand. He is an experienced leader in the technology industry, with a background in delivering innovative & engaging live events. Andrew has a wealth of experience in producing engaging content, from live shows and webinars to roundtables and panel discussions. He has a passion for helping businesses understand the latest trends and technologies, and how they can be applied to drive growth and innovation.
