0 Comments

Rolled out auto-scaling Kubernetes architecture for better audio file processing

Analysing our customer’s audio files is quite intensive, requiring quite a lot of CPU and RAM resources to generate a report within a reasonable period of time.

With our new architecture, more worker machines get added when more work needs doing and then they are terminated (switched off when not in use). We use Kubernetes as our container orchestrator running on Google Cloud using their Autopilot feature. Traditionally you would have to fix the size of your Kubernetes cluster upfront but Autopilot gives us the flexibility and simplicity we need as they deal with adding more node machines to the cluster as we increase the number of pod replicas in our specification.