ceph-csi/vendor/k8s.io/kubernetes/test/images/resource-consumer/README.md

# Resource Consumer

## Overview
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:
- cluster size autoscaling,
- horizontal autoscaling of pod - changing the size of replication controller,
- vertical autoscaling of pod - changing its resource limits.

## Usage
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:

- CPU in millicores,
- Memory in megabytes,
- Fake custom metrics.

### Consume CPU http request
- suffix "ConsumeCPU",
- parameters "millicores" and "durationSec".

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.

### Consume Memory http request
- suffix "ConsumeMem",
- parameters "megabytes" and "durationSec".

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.

### Bump value of a fake custom metric
- suffix "BumpMetric",
- parameters "metric", "delta" and "durationSec".

Bumps metric with given name by delta for durationSec seconds.
Custom metrics in Prometheus format are exposed on "/metrics" endpoint.

### CURL example
```console
$ kubectl run resource-consumer --image=k8s.gcr.io/resource_consumer:beta --expose --service-overrides='{ "spec": { "type": "LoadBalancer" } }' --port 8080
$ 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)

```console
$ curl --data "millicores=300&durationSec=600" http://<EXTERNAL-IP>:8080/ConsumeCPU
```

300 millicores will be consumed for 600 seconds.

## Image

Docker image of Resource Consumer can be found in Google Container Registry as k8s.gcr.io/resource_consumer:beta

## Use cases

### Cluster size autoscaling
1. Consume more resources on each node that is specified for autoscaler
2. Observe that cluster size increased

### Horizontal autoscaling of pod
1. Create consuming RC and start consuming appropriate amount of resources
2. Observe that RC has been resized
3. Observe that usage on each replica decreased

### Vertical autoscaling of pod
1. Create consuming pod and start consuming appropriate amount of resources
2. Observed that limits has been increased


[![Analytics](https://kubernetes-site.appspot.com/UA-36037335-10/GitHub/test/images/resource-consumer/README.md?pixel)]()