Project Description
This project demonstrates a chain of microservices working together to provide a personalized recommendation, as detailed in a CNCF blog post.
• Services:
o Movie Controller (API Gateway): External service using HTTP/REST that triggers a recommendation request.
o Movie Store Service: Holds a database of movie records; communicates via gRPC with the Recommender Service.
o User Preferences Service: Tracks user watch history and preferences; communicates via gRPC.
o Recommender Service: The core logic, which makes gRPC calls to the Movie Store and User Preferences services to generate a recommendation. This service could also leverage Kafka Streams to process user behavior data asynchronously for model training/updates.
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• Containerized: Docker
• Project tracker: Jira
• APM Logging system: Grafana
• Messaging & task queuing:
• Programming language: Java Spring Boot, Golang,
• Microservice: Apache Kafka, gRPC
• CI/CD pipeline:
• Automation:
• Database: PostgreSQL