Systems | Development | Analytics | API | Testing

At Koyeb, we run a serverless platform for deploying production-grade applications on high-performance infrastructure—GPUs, CPUs, and accelerators. You push code or containers; we handle everything from build to global deployment, running workloads in secure, lightweight virtual machines on bare-metal servers around the world.

Do you know that moment when your old on-prem systems creak under pressure? Apps are slow, updates are a nightmare, costs are ballooning, and innovation is bottlenecked by outdated infrastructure? Many organizations are waking up to the fact that keeping things as they are is no longer viable. Application migration to Azure isn’t just a tech upgrade; it’s a strategic move.

As an application developer integrating analytics into your application, your users expect a scalable, flexible solution that adapts to changing business needs. While organizations strive to capitalize on new AI tools, they’re also still wrestling with big data: massive, fast-moving datasets that traditional tools can’t handle easily.

Trinny London, Nando’s, and Katkin unified data to cut costs, enhance customer experience, and drive smarter decisions.

Imagine your enterprise app testing runs smoothly under normal traffic, but during a flash sale, it crashes under the sudden surge of users. The root cause? The cloud application testing failed to uncover critical scalability gaps. This is happening more and more in 2025 as companies are moving to the cloud, but are underestimating the complexity of testing at scale. With cloud adoption accelerating, traditional testing can’t keep up with modern app demands.

It's 3 AM, and during the testing process, your mobile app crashed in the middle of high traffic. Your outdated test infrastructure is unable to mirror real-life scenarios fast enough, and serious problems go undetected. On the other hand, a competitor provides a seamless user experience as they embrace Cloud-Based Testing and gain unmatched flexibility of open devices, speed of finding defects with their rapid scalability.