Requirements

Imagine you're building a task scheduler, similar to cron but designed for a specific application. This scheduler needs to efficiently manage and execute a batch of scheduling requests at a time. The system should be robust, scalable, and maintainable, allowing for easy addition of new task types and scheduling strategies. Think about how to handle concurrency, prioritize tasks, and deal with potential failures. We aim to create a design that allows a system to accept 10 scheduling requests concurrently, and then execute them respecting configurable constraints, dependencies and priorities. # Requirements ## Functional Requirements 1. **Request Submission:** The system must accept scheduling requests. Each request should contain information about the task to be executed, the schedule (e.g., cron expression, fixed delay, specific time), and any necessary metadata. The system should be able to handle at least 10 concurrent requests. 2. **Task Execution:** The scheduler must execute tasks according to their defined schedules. This includes correctly interpreting schedule expressions (e.g., cron) and triggering task execution at the appropriate times. 3. **Task Types:** Support different types of tasks (e.g., HTTP requests, database updates, script executions). The system must be easily extensible to support new task types without modifying core scheduler logic. 4. **Concurrency Control:** The scheduler must manage concurrent task executions, preventing race conditions or resource contention. Allow configuration to restrict the maximum number of concurrent tasks. 5. **Error Handling:** The system must gracefully handle task execution failures. This includes logging errors, retrying failed tasks (with configurable retry policies), and potentially notifying administrators. 6. **Prioritization:** Implement a prioritization mechanism for tasks. Higher priority tasks should be executed before lower priority tasks, even if they are submitted later. 7. **Dependencies:** Support task dependencies, where one task can only be executed after another task has completed successfully. The scheduler should manage these dependencies and ensure tasks are executed in the correct order. 8. **Batch Submission:** Ability to submit up to 10 scheduling requests at once. The system should handle this efficiently. 9. **Metrics & Monitoring:** Collect and expose metrics about task execution, such as the number of tasks executed, the number of failures, and average execution time. 10. **Configuration:** Provide a mechanism for configuring the scheduler, including parameters like the maximum number of concurrent tasks, retry policies, and logging levels. 11. **Task Cancellation:** Allow for cancelling scheduled tasks before they are executed. ## Non-Functional Requirements 1. **Thread Safety:** The scheduler must be thread-safe to handle concurrent requests and task executions. Use appropriate synchronization mechanisms to prevent data corruption and race conditions. 2. **Extensibility:** The design must be extensible to support new task types, scheduling strategies, and error handling mechanisms without requiring significant code changes. Leverage design patterns like Strategy, Factory, and Observer to achieve this. 3. **Modularity:** The system should be composed of loosely coupled modules with well-defined interfaces. This will improve maintainability and testability. 4. **Testability:** The code should be designed to be easily testable, with clear separation of concerns and minimal dependencies. Employ dependency injection to facilitate unit testing. 5. **Error Handling:** Implement robust error handling and logging. Exceptions should be caught and handled gracefully, and relevant information should be logged for debugging and monitoring. 6. **Resource Management:** Efficiently manage resources such as threads, memory, and network connections. Avoid resource leaks and ensure that resources are released promptly after use. 7. **Configuration Management:** Implement a flexible configuration management system that allows for easy modification of scheduler parameters without requiring code changes. 8. **Observability:** Provide mechanisms for monitoring the scheduler's performance and health. This includes collecting metrics, logging events, and providing a health endpoint that can be used to check the scheduler's status. 9. **Performance:** While not a hard real-time system, the scheduler should efficiently manage and execute tasks with minimal overhead. Consider the performance implications of different data structures and algorithms. ## Core Entities 1. **`Task`:** Represents a unit of work to be executed. It should have properties such as task ID, task type, execution parameters, and status. 2. **`Schedule`:** Defines when and how often a task should be executed. This could be a cron expression, a fixed delay, or a specific time. 3. **`Scheduler`:** The core component responsible for managing tasks and schedules. It accepts scheduling requests, triggers task executions, and handles errors. 4. **`TaskExecutor`:** An interface for executing tasks. Concrete implementations would handle different task types (e.g., `HttpRequestTaskExecutor`, `DatabaseUpdateTaskExecutor`). Implement the Strategy pattern. 5. **`TaskExecutionContext`:** Contains information about the task execution context, such as the task ID, execution parameters, and execution status. 6. **`TaskQueue`:** A queue used to store tasks waiting for execution. 7. **`RetryPolicy`:** Defines how failed tasks should be retried (e.g., number of retries, delay between retries). 8. **`TaskListener`:** An interface for listening to task execution events (e.g., task started, task completed, task failed). Used for monitoring and logging. Implement the Observer pattern. 9. **`BatchScheduler`:** Responsible for taking up to 10 scheduling requests concurrently.

Design a scheduler, that takes in 10 scheduling requests at a time and can execute 100 jobs at a time.(The scheduler executes http requests.)

Requirements

Think like an Architect

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