1# Resource Consumer
2
3## Overview
4Resource Consumer is a tool which allows to generate cpu/memory utilization in a container.
5The reason why it was created is testing kubernetes autoscaling.
6Resource Consumer can help with autoscaling tests for:
7- cluster size autoscaling,
8- horizontal autoscaling of pod - changing the size of replication controller,
9- vertical autoscaling of pod - changing its resource limits.
10
11## Usage
12Resource Consumer starts an HTTP server and handle sent requests.
13It listens on port given as a flag (default 8080).
14Action of consuming resources is send to the container by a POST http request.
15Each http request creates new process.
16Http request handler is in file resource_consumer_handler.go
17
18The container consumes specified amount of resources:
19
20- CPU in millicores,
21- Memory in megabytes,
22- Fake custom metrics.
23
24### Consume CPU http request
25- suffix "ConsumeCPU",
26- parameters "millicores" and "durationSec".
27
28Consumes specified amount of millicores for durationSec seconds.
29Consume CPU uses "./consume-cpu/consume-cpu" binary (file consume-cpu/consume_cpu.go).
30When CPU consumption is too low this binary uses cpu by calculating math.sqrt(0) 10^7 times
31and if consumption is too high binary sleeps for 10 millisecond.
32One replica of Resource Consumer cannot consume more that 1 cpu.
33
34### Consume Memory http request
35- suffix "ConsumeMem",
36- parameters "megabytes" and "durationSec".
37
38Consumes specified amount of megabytes for durationSec seconds.
39Consume Memory uses stress tool (stress -m 1 --vm-bytes megabytes --vm-hang 0 -t durationSec).
40Request leading to consuming more memory then container limit will be ignored.
41
42### Bump value of a fake custom metric
43- suffix "BumpMetric",
44- parameters "metric", "delta" and "durationSec".
45
46Bumps metric with given name by delta for durationSec seconds.
47Custom metrics in Prometheus format are exposed on "/metrics" endpoint.
48
49### CURL example
50```console
51kubectl run resource-consumer --image=gcr.io/k8s-staging-e2e-test-images/resource-consumer:1.9 --expose --service-overrides='{ "spec": { "type": "LoadBalancer" } }' --port 8080 --requests='cpu=500m,memory=256Mi'
52kubectl get services resource-consumer
53```
54
55There 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)
56
57```console
58curl --data "millicores=300&durationSec=600" http://<EXTERNAL-IP>:8080/ConsumeCPU
59```
60
61300 millicores will be consumed for 600 seconds.
62
63## Image
64
65Docker image of Resource Consumer can be found in Google Container Registry as gcr.io/k8s-staging-e2e-test-images/resource-consumer:1.9
66
67## Use cases
68
69### Cluster size autoscaling
701. Consume more resources on each node that is specified for autoscaler
712. Observe that cluster size increased
72
73### Horizontal autoscaling of pod
741. Create consuming RC and start consuming appropriate amount of resources
752. Observe that RC has been resized
763. Observe that usage on each replica decreased
77
78### Vertical autoscaling of pod
791. Create consuming pod and start consuming appropriate amount of resources
802. Observed that limits has been increased
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