As incoming traffic increases, it becomes crucial to scale up your applications based on the demand.
In the following tutorial, we explain how you can use Application Gateway's AvgRequestCountPerHealthyHost
metric to scale up your application. AvgRequestCountPerHealthyHost
is measure of average request that are sent to a specific backend pool and backend http setting combination.
We are going to use following two components:
Azure K8S Metric Adapter
- We will using the metric adapter to expose Application Gateway metrics through the metric server.Horizontal Pod Autoscaler
- We will use HPA to use Application Gateway metrics and target a deployment for scaling.
-
We will first create an Azure AAD service principal and assign it
Monitoring Reader
access over Application Gateway's resource group. Paste the following lines in your Azure Cloud Shell:applicationGatewayGroupName="<application-gateway-group-id>" applicationGatewayGroupId=$(az group show -g $applicationGatewayGroupName -o tsv --query "id") az ad sp create-for-rbac -n "azure-k8s-metric-adapter-sp" --role "Monitoring Reader" --scopes applicationGatewayGroupId
-
Now, We will deploy the
Azure K8S Metric Adapter
using the AAD service principal created above.kubectl create namespace custom-metrics # use values from service principle created above to create secret kubectl create secret generic azure-k8s-metrics-adapter -n custom-metrics \ --from-literal=azure-tenant-id=<tenantid> \ --from-literal=azure-client-id=<clientid> \ --from-literal=azure-client-secret=<secret> kubectl apply -f kubectl apply -f https://raw.githubusercontent.com/Azure/azure-k8s-metrics-adapter/master/deploy/adapter.yaml -n custom-metrics
-
We will create an
ExternalMetric
resource with nameappgw-request-count-metric
. This will instruct the metric adapter to exposeAvgRequestCountPerHealthyHost
metric formyApplicationGateway
resource inmyResourceGroup
resource group. You can use thefilter
field to target a specific backend pool and backend http setting in the Application Gateway. Copy paste this YAML content inexternal-metric.yaml
and apply withkubectl apply -f external-metric.yaml
.apiVersion: azure.com/v1alpha2 kind: ExternalMetric metadata: name: appgw-request-count-metric spec: type: azuremonitor azure: resourceGroup: myResourceGroup # replace with your application gateway's resource group name resourceName: myApplicationGateway # replace with your application gateway's name resourceProviderNamespace: Microsoft.Network resourceType: applicationGateways metric: metricName: AvgRequestCountPerHealthyHost aggregation: Average filter: BackendSettingsPool eq '<backend-pool-name>~<backend-http-setting-name>' # optional
You can now make a request to the metric server to see if our new metric is getting exposed:
kubectl get --raw "/apis/external.metrics.k8s.io/v1beta1/namespaces/default/appgw-request-count-metric"
# Sample Output
# {
# "kind": "ExternalMetricValueList",
# "apiVersion": "external.metrics.k8s.io/v1beta1",
# "metadata":
# {
# "selfLink": "/apis/external.metrics.k8s.io/v1beta1/namespaces/default/appgw-request-count-metric",
# },
# "items":
# [
# {
# "metricName": "appgw-request-count-metric",
# "metricLabels": null,
# "timestamp": "2019-11-05T00:18:51Z",
# "value": "30",
# },
# ],
# }
Once we are able to expose appgw-request-count-metric
through the metric server, We are ready to use Horizontal Pod Autoscaler
to scale up our target deployment.
In following example, we will target a sample deployment aspnet
. We will scale up Pods when appgw-request-count-metric
> 200 per Pod upto a max of 10
Pods.
Replace your target deployment name and apply the following auto scale configuration. Copy paste this YAML content in autoscale-config.yaml
and apply with kubectl apply -f autoscale-config.yaml
.
apiVersion: autoscaling/v2beta1
kind: HorizontalPodAutoscaler
metadata:
name: deployment-scaler
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: aspnet # replace with your deployment's name
minReplicas: 1
maxReplicas: 10
metrics:
- type: External
external:
metricName: appgw-request-count-metric
targetAverageValue: 200
Test your configuration by using a load test tools like apache bench:
ab -n10000 http://<application-gateway-ip-address>/