This project is a distributed system built using multiple services including a .NET Server, RabbitMQ, MS SQL Server, Prometheus, and Grafana. The system performs reliable asynchronous processing using RabbitMQ and exposes a REST API and gRPC services. The project is designed to process a series of requests related to "addition" and maintain the sum, integrating monitoring and observability tools like Prometheus and Grafana.

• RabbitMQ: Messaging broker that handles asynchronous communication between services.
• MSSQLSERVER (db): Database for storing application data.
• .NET gRPC: Implements gRPC service for adding values and communicates with RabbitMQ.
• .NET REST API: REST API service that gets the sum via HTTP requests.
• Prometheus: Collects and stores metrics from the services for monitoring.
• Grafana: Provides a dashboard for visualizing the metrics stored in Prometheus.

• gRPC-based Addition Service: Built a gRPC service in .NET for addition operations, where messages are processed asynchronously with RabbitMQ.
• RabbitMQ Integration: RabbitMQ is used for decoupling communication between services and ensuring reliable message processing.
• MSSQLSERVER: Database used for storing the state, with gRPC background server that read the data and publish them to rabbitMQ
• Outbox Pattern: Implemented the Outbox Pattern to ensure reliable message delivery by storing the message in a separate table (outboxMessages) within the database, which is later picked up by the message consumer (RabbitMQ).
• Prometheus + Grafana: Integrated Prometheus for monitoring request durations, and system health, and Grafana for visualizing metrics in real-time.
• Docker Compose: Used Docker Compose to run all services locally and manage dependencies between them.

• .NET for implementing the gRPC service and the REST API service.
• RabbitMQ for messaging.
• MSSQLSERVER as the primary database.
• Outbox Pattern for reliable message delivery.
• Prometheus for metrics collection and monitoring.
• Grafana for visualization of Prometheus metrics.
• Docker Compose for local development and orchestration of services.

Docker Compose was used to define services such as RabbitMQ, MSSQLSERVER, .NET server, Prometheus, and Grafana.

• Integrated Prometheus for tracking service metrics like request durations, CPU usage, and queue times.
• Set up Grafana to visualize metrics collected by Prometheus.
• Custom Prometheus metrics were created, such as queue_waiting_time_seconds to measure queue waiting time, and whole_request_time_soconds to whole request time

1. Install Docker (if not already installed):

   • Follow the instructions for your operating system to install Docker from the official Docker website.

2. Start the Services:

   • Navigate to the project directory.
   • Run the following command to start all services:

     docker-compose up -d

3. Verify the Services:

   • RabbitMQ will be available at http://localhost:15672.
   • grpc server will be available at http://localhost:50051.
   • REST server will be accessible at http://localhost:3001.
   • Prometheus will be available at http://localhost:9090.
   • Grafana will be available at http://localhost:3000 (default login: admin/admin).

• gRPC Server Load Testing: Used K6 to simulate load for gRPC calls to the Add endpoint, ramping up users to 15000

  docker-compose run --rm k6 run grpc-test.js

• Queue Waiting Time: Measured the time between receiving a message in the RabbitMQ queue and processing it.
• Whole Request Duration: Monitored the duration of gRPC and HTTP requests.
• CPU Usage: Used Prometheus to track CPU usage and system performance.
• Processed Message: Findout the number of processed messages