Why is Kubernetes unable to get metrics from KEDA?
If while setting up KEDA, you get an error: (v1beta1.external.metrics.k8s.io) status FailedDiscoveryCheck with a message: no response from https://ip:443: Get https://ip:443: net/http: request canceled while waiting for connection (Client.Timeout exceeded while awaiting headers).
One of the reason for this can be that you are behind a proxy network.
Before you start
Make sure no network policies are blocking traffic
Check the status:
Find the api service name for the service keda/keda-metrics-apiserver:
kubectl get apiservice --all-namespaces
Check for the status of the api service found in previous step:
kubectl get apiservice <apiservicename' -o yaml
kubectl get apiservice v1beta1.external.metrics.k8s.io -o yaml
If the status is False, then there seems to be an issue and proxy network might be the primary reason for it.
Solution for self-managed Kubernetes cluster:
Find the cluster IP for the keda-metrics-apiserver and keda-operator-metrics:
kubectl get services --all-namespaces
In the /etc/kubernetes/manifests/kube-apiserver.yaml - add the cluster IPs found in the previous step in no_proxy variable.
Reload systemd manager configuration:
sudo systemctl daemon-reload
sudo systemctl restart kubelet
Check the API service status and the pods now. Should work!
Solution for managed Kubernetes services:
In managed Kubernetes services you might solve the issue by updating firewall rules in your cluster.
E.g. in GKE private cluster add port 6443 (kube-apiserver) to allowed ports in master node firewall rules.
Why does Google Kubernetes Engine (GKE) 1.16 fail to fetch external metrics?
If you are running Google Kubernetes Engine (GKE) version 1.16, and are receiving the following error:
unable to fetch metrics from external metrics API: <METRIC>.external.metrics.k8s.io is forbidden: User "system:vpa-recommender" cannot list resource "<METRIC>" in API group "external.metrics.k8s.io" in the namespace "<NAMESPACE>": RBAC: clusterrole.rbac.authorization.k8s.io "external-metrics-reader" not found
The GKE team is currently working on a fix that they expect to have out in version >= 1.16.13.
Why does KEDA operator error with NoCredentialProviders
If you are running KEDA on AWS using IRSA or KIAM for pod identity and seeing the following error messages:
Type Reason Age From Message
---- ------ ---- ---- -------
Normal KEDAScalersStarted 31s keda-operator Started scalers watch
Normal KEDAScaleTargetDeactivated 31s keda-operator Deactivated apps/v1.Deployment default/my-event-based-deployment from 1 to 0
Normal ScaledObjectReady 13s (x2 over 31s) keda-operator ScaledObject is ready for scaling
Warning KEDAScalerFailed 1s (x2 over 31s) keda-operator NoCredentialProviders: no valid providers in chain. Deprecated.
For verbose messaging see aws.Config.CredentialsChainVerboseErrors
There is no support at this time for upgrading or deleting CRDs using Helm. This was an explicit decision after much community discussion due to the danger for unintentional data loss. Furthermore, there is currently no community consensus around how to handle CRDs and their lifecycle. As this evolves, Helm will add support for those use cases.
As of v2.2.1 of our Helm chart, we have changed our approach so that we automatically managing the CRDs through our Helm chart.
Due to this transition, it can cause upgrade failures if you started using KEDA before v2.2.1 and will cause errors during upgrades such as the following:
Error: UPGRADE FAILED: rendered manifests contain a resource that already exists. Unable to continue with update: CustomResourceDefinition “scaledobjects.keda.sh” in namespace "” exists and cannot be imported into the current release: invalid ownership metadata; label validation error: missing key “app.kubernetes.io/managed-by”: must be set to “Helm”; annotation validation error: missing key “meta.helm.sh/release-name”: must be set to “keda”; annotation validation error: missing key “meta.helm.sh/release-namespace”: must be set to “keda”
In order to fix this, you will need to manually add the following attributes to our CRDs: