HOW WE SAVED 10S OF THOUSANDS OF DOLLARS DEPLOYING LOW COST OPEN SOURCE AI TECHNOLOGIES AT SCALE WITH KUBERNETES
This author successfully replaced OpenAI's API with an open-source alternative to reduce the cost of running large-scale AI applications. They tried using Ollama on a local machine to generate text summaries, but limitations with concurrent processing led to them using vLLM (a fast inference runner). To handle large volumes of requests, the author used a Kubernetes cluster to deploy and load balance vLLM.