Bulk Calls Demo

BulkCallsController Documentation

The BulkCallsController in this async demo project showcases the implementation of bulk asynchronous HTTP GET requests to a specified endpoint. By leveraging .NET's async capabilities, this controller demonstrates how to efficiently manage a large number of network requests without overwhelming system resources.

Key Features:

• Concurrent HTTP Requests: Handles multiple HTTP GET requests concurrently using async tasks and `SemaphoreSlim` to limit the number of simultaneous requests, ensuring controlled parallelism and resource usage.
• Thread Safety: Uses locks to ensure thread safety when adding results to the shared list, preventing data corruption in multi-threaded environments.
• Timeouts and Cancellations: Implements `CancellationTokenSource` with a timeout to cancel long-running requests, demonstrating best practices for managing task lifetimes in async workflows.
• Performance Optimization: By using asynchronous task coordination with `Task.WhenAll`, the controller efficiently handles bulk requests, significantly reducing overall execution time compared to sequential processing.

Alternative Approaches:

While the BulkCallsController effectively demonstrates handling bulk requests with `SemaphoreSlim` for concurrency control, other approaches could include:

• Parallel.ForEach: Offers an alternative for concurrent processing but requires careful management of exceptions and concurrency controls.
• TPL Dataflow: Provides advanced options for data buffering and parallel task execution, making it suitable for complex data processing workflows.
• Cloud-Native Solutions: Leveraging Azure Functions or other serverless platforms with built-in scaling can offload concurrency management to cloud infrastructure.

Best Practices:

• Monitor and Log: Use logging and telemetry to monitor the performance and health of bulk async operations, enabling proactive tuning of concurrency levels and timeouts.
• Adjust Concurrency: Optimize the maximum thread count (`maxThreads`) based on system capabilities and endpoint performance to balance resource usage and throughput.
• Handle Failures Gracefully: Implement retry logic or circuit breakers using libraries like Polly to handle transient failures and improve resilience.