This project aims to build a distributed task queue and scheduler system. It will manage tasks, execute them on various worker nodes, and provide a rich API for users to interact with. By building this system, you will tackle various challenges, such as scalability, fault tolerance, and concurrency.
Here's a high-level overview of the components you'll need to build:
Design and implement a RESTful API server that allows users to submit tasks, query their status, and manage their execution. The server should handle a high volume of requests and provide features like authentication and rate limiting.
Implement a distributed task queue that can store and manage tasks. This should support features like task prioritization, retries, and timeouts. You can use existing message brokers like RabbitMQ or Kafka or design your own custom solution.
Create a scheduler responsible for distributing tasks to worker nodes based on their availability, priority, and other factors. The scheduler should ensure that tasks are executed efficiently and should be able to handle node failures.
Implement worker nodes that can execute tasks. These nodes should register themselves with the scheduler, receive tasks, and report their status. Worker nodes should be able to handle different types of tasks and execute them concurrently.
Build a monitoring and logging system that keeps track of the system's health, performance, and logs. This will help you diagnose issues and optimize the system's performance.
Develop a deployment strategy to easily deploy and scale the system. You can use containerization technologies like Docker and orchestration tools like Kubernetes for this purpose.