New GitHub Workshop Teaches Engineers to Run AI Agents on Dedicated GPUs Without Third-Party APIs

A new GitHub workshop, 'Agents That Own Their Inference,' teaches engineers to build production AI agents on dedicated GPUs using vLLM, covering nine modules on inference optimization and Kubernetes deployment with full open-source control and no vendor lock-in, available for roughly $0.52 per hour on Akamai Cloud.

• A new hands-on workshop called 'Agents That Own Their Inference' is now available on GitHub, teaching engineers how to build and operate production AI agents on dedicated GPUs using vLLM instead of relying on third-party API providers.
• The workshop spans nine modules covering critical inference concepts including KV cache management, quantization, speculative decoding, engine saturation, and Kubernetes deployment, and supports two participation paths: an Akamai-hosted environment or a self-serve setup using any Kubernetes cluster with an NVIDIA GPU.
• The entire workshop stack runs on open-source tools including vLLM, Kubernetes, and Qwen models, giving developers full control over the inference layer with no vendor lock-in, and the infrastructure can be provisioned on Akamai Cloud for approximately $0.52 per hour.