CPU cores affect some thread pool settings and default max concurrency in Mule runtime.
For example, a Mule 4.4 runtime uses the following formula in {MULE_HOME}/conf/scheduler-pools.conf to calculate the thread pool size, which relies on the predefined cores parameters.
org.mule.runtime.scheduler.uber.threadPool.maxSize=max(2, cores + ((mem - 245760) / 5120))
Another example, as per the document, the Mule 4.4 runtime Batch Job component limits the default max concurrency to twice the number of available cores.
However, for the Mule app on Runtime Fabric, we can supply a fractional vCPU on Reserved CPU and CPU Limit settings, we need to understand what CPU cores number is used by Mule runtime when it's calculating the thread pool size and the default max concurrency.
Mule Runtime runs on the JVM and it invokes java.lang.Runtime.getRuntime().availableProcessors() to get CPU cores number.
The JVM on RTF is container awareness, it deduces the CPU cores via container CPU settings enforced by container orchestration.
CPU Limit
No, it always rounds up to an integer. The following are some examples:
| Reserved CPU | CPU Limit | CPU Cores |
| 0.1 | 0.2 | 1 |
| 0.1 | 0.9 | 1 |
| 0.1 | 1 | 1 |
| 0.1 | 1.01 | 2 |
| 0.1 | 1.5 | 2 |
No, -XX:-UseContainerSupport JVM setting can end up with deployment failure.
No, -XX:ActiveProcessorCount=xx can end up with failure at running time.
No, the performance depends on the profile of the an app (such as IO, CPU and Memory), setting CPU Limit to 1.01 may or may not improve the app performance, as the performance is still subject to the container computing power. Hence, a throughly performance test is necessary when allocating CPU resource on RTF.
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