Intelligent Apps with Azure Container Apps (ACA)

3:30 午後 - 3:45 午後 (UTC)

Learn how you can use ACA to build a music recommendation service. During this demo you will see how ACA can serve as a platform for AI engineers to process data, and hand off to application engineers to utilize and develop applications around. Learn how to leverage ACA’s Qdrant vector database add-on to ingest and create embeddings for a library of songs. This serves as a backend for a series of polyglot microservices written in Python and Java to develop a recommendation service for music. Explore how ACA’s code to cloud pipeline allows container novices to deploy applications without the use of dockerfiles. If you want to learn more about vector databases, embeddings or how to build microservice applications leveraging AI, then this is for you.

3:30 午後 - 3:45 午後 (UTC)

In this demo, explore how to leverage GPU workload profiles in ACA to run your own model backend, and easily switch, compare, and speed up your inference times. You will also explore how to leverage LlamaIndex (https://github.com/run-llama/llama_index) to ingest data on-demand, and host models using Ollama (https://github.com/ollama/ollama). Then finally, decompose the application as a set of microservices written in Python, deployed on ACA.