Syself Empowers Hesse.ai's Kubernetes Journey to Success
Introduction
Hesse.ai is a German company building a platform that makes studies easier with AI and machine learning. It's a fast-growing startup that runs its AI and machine learning solutions on Kubernetes. 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. That got them running quickly, so they could spend their time on the product instead of on infrastructure.
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 to find a more cost-effective and efficient solution. This is when they found Syself— a simplified, GDPR-compliant platform that enabled them to run production-grade Kubernetes on Hetzner without needing 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 syself's managed databases, 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, with the ability to run GPU workloads natively in their clusters. Their new environment is much more scalable, while remaining similar in cost to their previously self-managed setup.
Because they skipped most of the usual Kubernetes learning curve, the Hesse.ai team could spend their time improving their educational tools for students.
