Docker Model Runner simplifies AI chatbot development by integrating LLM execution into familiar Docker workflows. The tutorial demonstrates building a production-ready chatbot with React frontend, Go backend, and comprehensive observability using Prometheus, Grafana, and Jaeger. Key benefits include local model execution for privacy and cost control, streaming responses, real-time metrics collection, and simplified deployment through Docker Compose. The architecture treats AI models as first-class services, eliminating complex setup while providing detailed performance insights including tokens per second, memory usage, and response latency.
Table of contents
The current challenges with GenAI developmentHow Docker is solving these challengesHow to create an AI chatbot with DockerCategories of metricsDocker Compose: LLM as a first-class serviceConclusionSort: