Here is my configuration in the helm chart :
- name: JOB_MAIN_CONTAINER_CPU_REQUEST
value: "2"
- name: JOB_MAIN_CONTAINER_CPU_LIMIT
value: "2"
- name: JOB_MAIN_CONTAINER_MEMORY_REQUEST
value: 4Gi
- name: JOB_MAIN_CONTAINER_MEMORY_LIMIT
value: 4Gi
When I check the resources used by the pod in GKE I see
airbyte | source-hubspot-read-8-0-dyiam | main | 51.7 MiB
So maybe my question is more how can I speed up my job to reduce the processing time ?
I have way more memory available for the job (and same story for the CPU)