These days, everyone and their grandma are using Kubernetes and one important
aspect of Kubernetes is scaling your workloads. With KEDA, it is extremely
simple to scale your workloads! Let’s have a look.
repository: https://github.com/djamaile/keda-demo
Introduction
Straight from the website of KEDA:
KEDA is a Kubernetes-based Event Driven
Autoscaler. With KEDA, you can drive the scaling of any container in Kubernetes
based on the number of events needing to be processed.
KEDA provides many 'triggers' on which your application can scale on. For
example, Prometheus, PubSub, Postgres and many more. In this blog post we will
focus on Prometheus.
Starting up
First let's spin up a cluster! I am using kind but
you are free to use minikube if you prefer that :).
$ kind create cluster
Create the namespace
$ kubectl create ns keda-demo
Switch to the namespace
$ kubectl config set-context --current --namespace=keda-demo
If the cluster is spun up, we can start deploying our Prometheus. For this, I
have already written a prometheus manifest so you won’t have to do it.
prometheus.yaml
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
name: prometheus
rules:
- apiGroups: [""]
resources:
- services
verbs: ["get", "list", "watch"]
- nonResourceURLs: ["/metrics"]
verbs: ["get"]
---
apiVersion: v1
kind: ServiceAccount
metadata:
name: keda-demo
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
name: prometheus
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: prometheus
subjects:
- kind: ServiceAccount
name: keda-demo
namespace: keda-demo
--------
apiVersion: v1
kind: ConfigMap
metadata:
name: prom-conf
labels:
name: prom-conf
data:
prometheus.yml: |-
global:
scrape_interval: 5s
evaluation_interval: 5s
scrape_configs:
- job_name: 'go-prom-job'
kubernetes_sd_configs:
- role: service
relabel_configs:
- source_labels: [__meta_kubernetes_service_label_run]
regex: go-prom-app-service
action: keep
--------
apiVersion: apps/v1
kind: Deployment
metadata:
name: prometheus-deployment
spec:
replicas: 1
selector:
matchLabels:
app: prometheus-server
template:
metadata:
labels:
app: prometheus-server
spec:
serviceAccountName: keda-demo
containers:
- name: prometheus
image: prom/prometheus
args:
- "--config.file=/etc/prometheus/prometheus.yml"
- "--storage.tsdb.path=/prometheus/"
ports:
- containerPort: 9090
volumeMounts:
- name: prometheus-config-volume
mountPath: /etc/prometheus/
- name: prometheus-storage-volume
mountPath: /prometheus/
volumes:
- name: prometheus-config-volume
configMap:
defaultMode: 420
name: prom-conf
- name: prometheus-storage-volume
emptyDir: {}
--------
apiVersion: v1
kind: Service
metadata:
name: prometheus-service
spec:
ports:
- port: 9090
protocol: TCP
selector:
app: prometheus-server
The Prometheus manifest is really simple. Just a Prometheus workload with a
clusterrole and a clusterrolebinding. Don't forget to apply the manifest:
$ kubectl apply -f prometheus.yaml
Once the pod is up and running, let's see if it also works:
$ kubectl port-forward svc/prometheus-service 9090
Now visit http://localhost:9090 and you should see the user interface of
Prometheus.
Deploying Keda
We can now deploy the KEDA operator. KEDA provides multiple ways to deploy their
operator, but for now we will use the k8s manifest.
$ kubectl apply -f https://github.com/kedacore/keda/releases/download/v2.4.0/keda-2.4.0.yaml
Now there should be two pods in the namespace keda you can check it with the
following command:
$ kubectl get pods -n keda
As you can see there are two pods being spinned up:
on 🤠 kind-kind (keda) Desktop/projects/keda-prometheus ☁️ default
🕙[ 07:35:40 ] ❯ kubectl get pods 335ms
NAME READY STATUS RESTARTS AGE
keda-metrics-apiserver-66b8c68649-2mwf8 0/1 ContainerCreating 0 5s
keda-operator-574c6d4769-q9mlc 0/1 ContainerCreating 0 5s
The metrics-apiserver exposes data to the Horizontal Pod Autoscaler, which gets
consumed by a deployment. The operator pod activates Kubernetes deployments to
scale to and from zero on no events.
Creating the application (Optional)
The application is a simple go application that increments the metric
http_requests when you visit it. This section is optional because you are also
free to use my docker image.
in your folder execute the following:
go mod init github.com/djamaile/keda-demo
Then in your main.go you can put in the following code:
package main
import (
"fmt"
"log"
"net/http"
"github.com/prometheus/client_golang/prometheus"
"github.com/prometheus/client_golang/prometheus/promhttp"
)
type Labels map[string]string
var (
httpRequestsCounter = prometheus.NewCounter(prometheus.CounterOpts{
Name: "http_requests",
Help: "number of http requests",
})
)
func init() {
// Metrics have to be registered to be exposed:
prometheus.MustRegister(httpRequestsCounter)
}
func main() {
http.Handle("/metrics", promhttp.Handler())
http.HandleFunc("/", func(w http.ResponseWriter, r *http.Request) {
defer httpRequestsCounter.Inc()
fmt.Fprintf(w, "Hello, you've requested: %s\n", r.URL.Path)
})
log.Fatal(http.ListenAndServe(":8080", nil))
}
Now build the go application with:
$ go mod tidy
Let's then make a simple Dockerfile for it:
FROM golang as build-stage
COPY go.mod /
COPY go.sum /
COPY main.go /
RUN cd / && CGO_ENABLED=0 GOOS=linux go build -a -installsuffix cgo -o go-prom-app
FROM alpine
COPY --from=build-stage /go-prom-app /
EXPOSE 8080
CMD ["/go-prom-app"]
Only thing left is to build and push the image:
$ docker build -t <your_username>/keda .
$ docker push <your_username>/keda
Running the application
If you don’t have a Docker account or don’t want to use it, that’s fine. You can
use my docker image! Let’s get our go application running in our cluster, for
that we need some k8s manifests. Not to worry because I already wrote them:
go-deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: go-prom-app
namespace: keda-demo
spec:
selector:
matchLabels:
app: go-prom-app
template:
metadata:
labels:
app: go-prom-app
spec:
containers:
- name: go-prom-app
image: djam97/keda
imagePullPolicy: Always
ports:
- containerPort: 8080
--------
apiVersion: v1
kind: Service
metadata:
name: go-prom-app-service
namespace: keda-demo
labels:
run: go-prom-app-service
spec:
ports:
- port: 8080
protocol: TCP
selector:
app: go-prom-app
You can replace the image name with your own image if you prefer that.
Let's apply the manifest:
$ kubectl apply -f go-deployment.yaml
If the pod is up verify if it is working
$ kubectl port-forward svc/go-prom-app-service 8080
If you visit http://localhost:8080 you should see Hello, you've requested: /.
Scaling the application
Now that we have our go application up we can write a manifest that will scale
our application. Keda offers many triggers that can scale our application, but
of course we will use the Prometheus
trigger.
In a new file called scaled-object.yaml add the following content:
apiVersion: keda.sh/v1alpha1
# Custom CRD provisioned by the Keda operator
kind: ScaledObject
metadata:
name: prometheus-scaledobject
spec:
scaleTargetRef:
# target our deployment
name: go-prom-app
# Interval to when to query Prometheus
pollingInterval: 15
# The period to wait after the last trigger reported active
# before scaling the deployment back to 1
cooldownPeriod: 30
# min replicas keda will scale to
# if you have an app that has an dependency on pubsub
# this would be a good use case to set it to zero
# why keep your app running if your topic has no messages?
minReplicaCount: 1
# max replicas keda will scale to
maxReplicaCount: 20
advanced:
# HPA config
# Read about it here: https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale/
horizontalPodAutoscalerConfig:
behavior:
scaleDown:
stabilizationWindowSeconds: 30
policies:
- type: Percent
value: 50
periodSeconds: 30
scaleUp:
stabilizationWindowSeconds: 0
policies:
- type: Percent
value: 50
periodSeconds: 10
triggers:
- type: prometheus
metadata:
# address where keda can reach our prometheus on
serverAddress: http://prometheus-service.keda-demo.svc.cluster.local:9090
# metric on what we want to scale
metricName: http_requests_total
# if treshold is reached then Keda will scale our deployment
threshold: "100"
query: sum(rate(http_requests[1m]))
Read the yaml manifest and it’s comments to understand what is going on. One
important note as well is in
advanced.horizontalPodAutoscalerConfig.scaleUp.policies you can see I have
specified 50%, that means our pod will scale up with 50% of it’s current amount
of pods. 1 -> 2 -> 3 -> 5 -> 8 -> 12 -> 18 -> 20 it will stop at 20 pods because
that is the limit we specified.
Let's apply the manifest:
$ kubectl apply -f scaled-object.yaml
This will provision an HPA in your namespace which you can check with:
$ kubectl get hpa
but because this is a custom CRD you can also query the custom CRD with kubectl:
$ kubectl get scaledobject.keda.sh/prometheus-scaledobject
NAME SCALETARGETKIND SCALETARGETNAME MIN MAX TRIGGERS AUTHENTICATION READY ACTIVE FALLBACK AGE
prometheus-scaledobject apps/v1.Deployment go-prom-app 1 20 prometheus True False False 64s
We can see that our prometheus-scaledobject is ready so let’s scale our
application! Remember our application scales on the metric
http_requests_total
and our threshold is only 100 so we should be able reach that threshold. For
this we can use a simple tool called hey.
Run the application
$ kubectl port-forward svc/go-prom-app-service 8080
In another terminal watch the pods
$ kubectl get pods -w -n keda-demo
Put load on the application (Do this continuously, until there are 20 pods)
$ hey -n 10000 -m GET http://localhost:8080
It can take a minute before the application actually starts scaling. After a
while you should have 20 pods up and running! Now let’s also look at the scale
down process. Stop putting load on the application and let’s just watch the
pods. This process should go from 20 -> 10 -> 5 - > 2 -> 1. This is basically
how KEDA goes to work!
If you like KEDA please check out their docs for more examples and what type of
different triggers they provide. Happy auto-scaling!
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