The article delves into essential asynchronous patterns for building a Python service, emphasizing the importance of avoiding common pitfalls such as unresponsive shutdowns, task explosions, and excessive memory usage. It discusses how services, like those interfacing with Elasticsearch, can benefit from a global async task that enters an idle state when not in use, and how graceful shutdowns can be achieved by employing a cancellable sleep pattern. The piece introduces the concept of task pooling to manage task concurrency effectively, preventing tasks from overwhelming system resources. It also highlights the significance of controlling memory usage through innovative techniques like the MemQueue class, which is built upon Python's asyncio.Queue to limit the memory footprint of queued items. The article concludes by encouraging contributions and discussions on these implementations within the open-source connectors-python project.