Resource Consumer is a tool which allows to generate cpu/memory utilization in a container. The reason why it was created is testing kubernetes autoscaling. Resource Consumer can help with autoscaling tests for:
Resource Consumer starts an HTTP server and handle sent requests. It listens on port given as a flag (default 8080). Action of consuming resources is send to the container by a POST http request. Each http request creates new process. Http request handler is in file resource_consumer_handler.go
The container consumes specified amount of resources:
Consumes specified amount of millicores for durationSec seconds. Consume CPU uses “./consume-cpu/consume-cpu” binary (file consume-cpu/consume_cpu.go). When CPU consumption is too low this binary uses cpu by calculating math.sqrt(0) 10^7 times and if consumption is too high binary sleeps for 10 millisecond. One replica of Resource Consumer cannot consume more that 1 cpu.
Consumes specified amount of megabytes for durationSec seconds. Consume Memory uses stress tool (stress -m 1 --vm-bytes megabytes --vm-hang 0 -t durationSec). Request leading to consuming more memory then container limit will be ignored.
Bumps metric with given name by delta for durationSec seconds. Custom metrics in Prometheus format are exposed on “/metrics” endpoint.
$ kubectl run resource-consumer --image=gcr.io/kubernetes-e2e-test-images/resource-consumer:1.4 --expose --service-overrides='{ "spec": { "type": "LoadBalancer" } }' --port 8080 --requests='cpu=500m,memory=256Mi' $ kubectl get services resource-consumer
There are two IPs. The first one is internal, while the second one is the external load-balanced IP. Both serve port 8080. (Use second one)
$ curl --data "millicores=300&durationSec=600" http://<EXTERNAL-IP>:8080/ConsumeCPU
300 millicores will be consumed for 600 seconds.
Docker image of Resource Consumer can be found in Google Container Registry as gcr.io/kubernetes-e2e-test-images/resource-consumer:1.4