Async Python Microservices with gRPC

Describe monolithic architecture and its layered structure, using a restaurant kitchen analogy.

Analyze team scaling challenges (e.g., cognitive load, code ownership) in large monolithic projects.

Describe the modular monolith pattern as a strategic intermediate architecture.

Identify real-world business scenarios where migrating from a monolith to microservices is justified.

State the CAP theorem and explain its implications for system design choices between consistency, availability, and partition tolerance.

Differentiate between strong consistency and eventual consistency with practical examples (e.g., banking vs. social media feed).

Decompose a sample monolithic e-commerce application into candidate microservices based on business capabilities.

Explain the database-per-service pattern and its implications for data consistency and transactions.

Distinguish between concurrency and parallelism, identifying use cases for each in Python.

Create and manage asyncio Tasks to run and control multiple coroutines concurrently.

Compare Protobuf binary serialization with JSON in terms of performance, size, and schema enforcement.

Describe the end-to-end gRPC request/response lifecycle, from client stub to server implementation.

Build an async gRPC client that makes concurrent calls to a service.

Build a FastAPI service that acts as a REST-to-gRPC gateway for internal microservices.

Implement health check (`/healthz`) and readiness (`/readyz`) endpoints for Kubernetes probes.

Implement a simple publish-subscribe pattern for inter-service notifications using Redis Pub/Sub.

Compare the roles of Redis, RabbitMQ, and Kafka in event-driven architectures.

Implement task retries with exponential backoff in Celery to handle transient failures.

Implement a cache-aside strategy using Redis to reduce database load on read-heavy services.

Implement a 'User Service' with gRPC endpoints and JWT-based authentication.

Implement an 'Order Service' that coordinates with other services via synchronous gRPC calls.

Containerize all services and orchestrate the complete system using Docker Compose.