At which stages of code development or execution can a bottleneck occur in the queue when processing a high-load synchronous process?

Bottlenecks in the queue during the processing of a high-load synchronous process can occur at several stages:

• Data reception in the queue: if the data source generates events faster than the queue can accept them, accumulation occurs.
• Adding to the queue: locks or synchronization when adding elements to the queue (for example, when using thread-safe structures) can slow down the process.
• Processing elements from the queue: if the handler cannot process elements as quickly as they arrive, the queue grows.
• Interaction with external resources: delays in writing to a database, network calls, or input-output operations can slow down processing.

For example, in Python, using queue.Queue with multiple threads, locks during adding/removing elements can become a bottleneck, especially if processing elements takes a significant amount of time.