Project Description
Leverage Go's efficiency for handling high throughput and Python's strength in data processing or machine learning.
• Go Microservice:
o Data Ingestion Service: Collects data (e.g., IoT sensor data, stock market ticks) using gRPC's server streaming or bi-directional streaming features and stores it (e.g., in a time-series database).
• Python Client/Service:
o Analytics Service: A Python service acts as a client to the Go data ingestion service, reading the stream of data to perform real-time analysis, generate reports, or run machine learning models.
Key Technologies to Incorporate:
• gRPC and Protocol Buffers: Use .proto files to define a clear, strongly-typed service contract that ensures seamless communication between the Go and Python components.
• Docker & Docker Compose: Containerize all services for easy deployment and local orchestration, making the polyglot environment manageable.
• Database: Integrate PostgreSQL, MySQL, or a NoSQL solution for data persistence.
• Observability (Optional but Recommended): Add logging, monitoring, and tracing using tools like Prometheus, Grafana, and Jaeger to understand how your microservices are performing.
PROJECT 1) E-commerce Backend System
• Containerized: Docker
• Project tracker: Jira
• Logging system: Grafana
• Messaging & task queuing: RabbitMQ, Celery
• Programming language: Python Django, AngularJS, Golang
• Microservice: Apache Kafka, gRPC
• CI/CD pipeline:
• Automation:
• Database: PostgreSQL