Syself Powers Kubernetes From Zero to Production With Hesse.ai
Introduction
Hesse.ai is a German company building a platform that makes studies easier with AI and machine learning. Their goal is to enable students to learn any subject of their choice.
The Challenge
Following their launch, Hesse.ai quickly realized the need for a robust and scalable infrastructure to keep up with their platform’s growing success.
Hesse.ai's platform relies on a modern Python microservices architecture, unstructured.io, and a vector database to handle their complex requirements.
Initially, their applications were deployed on Hetzner virtual machines using Docker Swarm. This allowed them to get up and running quickly and not waste time on infrastructure issues that could instead be invested in their product.
However, maintaining their infrastructure was harder and more time-consuming than expected. Motivated by that, as well as the lack of traction in the Docker Swarm community, they decided to migrate to Kubernetes —the gold standard for modern cloud infrastructure.
Recognizing the need for a managed Kubernetes solution, they opted to migrate to Azure AKS to streamline infrastructure management and scale effectively. While the transition provided the operational benefits they were looking for, it also highlighted a stark difference in cloud costs compared to the previous Hetzner setup.
The Solution
They decided to return to Hetzner and find a more cost-effective and efficient solution. This is when they found Syself— a simplified, GDPR-compliant platform that would allow them to have production-grade Kubernetes on Hetzner without the need to hire a dedicated team of experts.
With Syself Autopilot, the Hesse.ai team was able to quickly and effectively transition to Kubernetes. Syself provided a simplified experience, from installing kubectl to provisioning a fully optimized Kubernetes cluster, all tailored to their specific workload. The transition was smooth, and their platform was up and running in production with minimal overhead.
Furthermore, Syself helped them with migrating their databases to Kubernetes. By leveraging bare metal servers' local storage, they now have a performant and cost-efficient solution. And with the use of operators, they can have all the benefits of managed databases, like configurable automated backups and load distribution.
Results
Hesse.ai now operates on a robust and reliable infrastructure that supports their advanced AI-driven platform. Their new environment is much more scalable, while remaining similar in cost to their previously self-managed setup.
By avoiding the steep learning curve typically associated with Kubernetes, the Hesse.ai team could focus on enhancing their educational tools, delivering a superior product to their users.
