Add idempotency section to asynchronism
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@ -161,6 +161,7 @@ Review the [Contributing Guidelines](CONTRIBUTING.md).
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* [Message queues](#message-queues)
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* [Task queues](#task-queues)
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* [Back pressure](#back-pressure)
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* [Idempotent operations](#idempotent-operations)
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* [Communication](#communication)
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* [Transmission control protocol (TCP)](#transmission-control-protocol-tcp)
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* [User datagram protocol (UDP)](#user-datagram-protocol-udp)
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@ -1356,6 +1357,12 @@ Tasks queues receive tasks and their related data, runs them, then delivers thei
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If queues start to grow significantly, the queue size can become larger than memory, resulting in cache misses, disk reads, and even slower performance. [Back pressure](http://mechanical-sympathy.blogspot.com/2012/05/apply-back-pressure-when-overloaded.html) can help by limiting the queue size, thereby maintaining a high throughput rate and good response times for jobs already in the queue. Once the queue fills up, clients get a server busy or HTTP 503 status code to try again later. Clients can retry the request at a later time, perhaps with [exponential backoff](https://en.wikipedia.org/wiki/Exponential_backoff).
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### Idempotent operations
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It is important to understand the benefits of [idempotent](https://en.wikipedia.org/wiki/Idempotence#Computer_science_meaning) operations, especially when using message or task queues that do not guarantee *exactly once* processing. Many queueing systems guarantee *at least once* message delivery or processing. These systems are not completely synchronized, for instance, across geographic regions, which simplifies some aspects of their implemntation or design. Designing the operations that a task queue executes to be idempotent allows one to use a queueing system that has accepted this design trade-off.
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**[Google Pub/Sub](https://cloud.google.com/pubsub)** is a highly scalable, reliable, hosted messaging platform, but, on its own, does not guarantee *exactly once* delivery.
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### Disadvantage(s): asynchronism
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* Use cases such as inexpensive calculations and realtime workflows might be better suited for synchronous operations, as introducing queues can add delays and complexity.
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