Answer some production-ready questions that came up in private threads

docs/examples/production-ready/README.md

@@ -1,20 +1,58 @@
 # Production Example
 
-This is an example of a good starting point for a production RabbitMQ deployment. It deploys a 3-node cluster with enough resources to handle reasonable traffic.
+This is an example of a good starting point for a production RabbitMQ deployment.
+It deploys a 3-node cluster with sufficient resources to handle 1 billion messages per day at 8kB payload and a replication factor of three.
+The rest of the workload details are outlined in the monthly cost savings calculator on https://rabbitmq.com/tanzu
 
 Please keep in mind that:
 
-1. It may not be suitable for YOUR production deployment. Please go through the [Production Checklist](https://www.rabbitmq.com/production-checklist.html) to learn more about production deployment considerations.
+1. It may not be suitable for **your** production deployment.
+   The official [RabbitMQ Production Checklist](https://www.rabbitmq.com/production-checklist.html) will help you with some of these considerations.
 
-2. While it is important to correctly deploy RabbitMQ cluster for production deployment, it is even more important to correctly use RabbitMQ from your applications. [Production Checklist](https://www.rabbitmq.com/production-checklist.html) covers some of the common issues such as connection churn and polling consumers. Please also consider using [Quorum Queues](https://www.rabbitmq.com/quorum-queues.html) since they provide better data safety.
+2. While it is important to correctly deploy RabbitMQ cluster for production workloads, it is equally important for your applications to use RabbitMQ correctly.
+   [Production Checklist](https://www.rabbitmq.com/production-checklist.html) covers some of the common issues such as connection churn and polling consumers.
+   This example was tested with [Quorum Queues](https://www.rabbitmq.com/quorum-queues.html) which provide excellent data safety for workloads that require message replication.
 
-You can deploy this example like this:
+Before you can deploy this RabbitMQ cluster, you will need a multi-zone Kubernetes cluster with at least 3 nodes, 12 CPUs, 30Gi RAM and 1.5Ti disk space available.
+A `storageClass` named `ssd` will need to be defined too.
+We have [a GKE-specific example](ssd-gke.yaml) included in this example.
+Read more about the expected disk performance [in Google Cloud Documentation](https://cloud.google.com/compute/docs/disks/performance#ssd_persistent_disk).
+For what it's worth, disk write throughput is the limiting factor for persistent messages with a payload of 8kB.
+
+To deploy this RabbitMQ cluster, run the following:
 
 ```shell
 kubectl apply -f rabbitmq.yaml
 kubectl apply -f pod-disruption-budget.yaml
 ```
 
-Please keep in mind that you need a multi-zone Kubernetes cluster with 3 nodes, 12 CPUs, 30Gi RAM, 1.5Ti disk space available as well as a `storageClass` called `ssd` to deploy this example as-is. Of course you can adjust these values to your environment if needed.
+## Q & A
+
+### Is 4 CPUs per RabbitMQ node the minimum?
+
+No. The absolute minimum is 2 CPUs.
+
+For our workload - 1 billion messages per day at 8kB payload and a replication factor of three - 4 CPUs is the minimum.
+
+### Will RabbitMQ work with 1 CPU?
+
+Yes. It will work, but poorly, which is why we cannot recommend it for production workloads.
+A RabbitMQ with less than 2 full CPUs cannot be considered production.
+
+
+### Can I assign less than 1 CPU to RabbitMQ?
+
+Yes, this is entirely possible within Kubernetes.
+Be prepared for unresponsiveness that cannot be explained.
+The kernel will work against RabbitMQ's runtime optimisations, and anything can happen.
+A RabbitMQ with less than 2 full CPUs cannot be considered production.
+
+### Does CPU clock speed matter for message throughput?
+
+Yes. Queues are single threaded, and CPUs with higher clock speeds can run more cycles, which means that the queue process can perform more operations per second.
+This will not the case when disks or network are the limiting factor, but in benchmarks with sufficient network and disk capacity, faster CPUs translate to higher message throughhput.
+
+### Are vCPUs (virtual CPUs) OK?
 
-An SSD storage class can be defined using [the example](ssd-gke.yaml) (which is GKE-specific and needs to be adjusted for other environments). Read more about the expected disk performance [in Google Cloud Documentation](https://cloud.google.com/compute/docs/disks/performance#ssd_persistent_disk).
+Yes. The workload that was used for this production configuration starting point ran on Google Cloud and used 2 real CPU cores with 2 hyper-threads each, meaning 4 vCPUs.
+While we would recommend real CPUs and no hyper-threading, we also operate in the cloud and default to using vCPUs, including for our benchmarks.