Slow asynchronous microflow execution time in Google Kubernetes Engine

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I deployed my mendix app (mendix for private cloud standalone)  in gke with cpu limit and memory limit of 2 cpu and 6GB ram. I have microflow that kept on time outing after 3 minutes on synchronous, while It took around 1 minute in local. I decided to make it asynchronous, but it only use around 200m cpu and 500MB memory.   How do i Increase the cpu and memory usage for asynchronous microflow?   More information: - database (GCP postgresql) uses around 50 % of cpu and 4 out of 12 GB memory - DB connection increased from 50 to 400 (maximum number of connection for GCP postgresql) - local uses 30% cpu from 4 core 8 thread cpu, while ram is around 500 MB and it's faster than in gke.
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