Troubleshoot Google Distributed Cloud observability issues

This document helps you troubleshoot observability issues in Google Distributed Cloud. If you experience any of these issues, review the suggested fixes and workarounds.

If you need additional assistance, reach out to Google Support.

Cloud Audit Logs aren't collected

Check if Cloud Audit Logs are enabled in the cloudAuditLogging section of the cluster config. Verify that the project ID, location, and service account key are properly configured. The project ID has to be the same as the project ID under gkeConnect.

If Cloud Audit Logs are enabled, permissions are the most common reason that logs aren't collected. In this scenario, permission denied error messages are displayed in the Cloud Audit Logs proxy container.

The Cloud Audit Logs proxy container runs as one of the following:

  • A static Pod in the admin or standalone cluster.
  • As a sidecar container in kube-apiserver Pod.

If you see permission errors, follow the steps to troubleshoot and resolve permission issues.

kube-state-metrics metrics aren't collected

kube-state-metrics (KSM) runs as a single replica Deployment in the cluster and generates metrics on almost all resources in the cluster. When KSM and the gke-metrics-agent run on the same node, there's a greater risk of outage among metrics agents on all nodes.

KSM metrics have names that follow the pattern of kube_<ResourceKind>, like kube_pod_container_info. Metrics that start with kube_onpremusercluster_ are from the on-premises cluster controller, not from KSM.

If KSM metrics are missing, review the following troubleshooting steps:

  • In Cloud Monitoring, check the CPU, memory, and restart count of KSM using the summary API metrics like kubernetes.io/anthos/container/... . This is a separate pipeline with KSM. Confirm that the KSM Pod isn't limited by not enough resources.
    • If these summary API metrics aren't available for KSM, gke-metrics-agent on the same node probably also has the same issue.
  • In the cluster, check the status and logs of the KSM Pod and the gke-metrics-agent Pod on the same node with KSM.

kube-state-metrics crash looping

Symptom

No metrics from kube-state-metrics (KSM) are available from Cloud Monitoring.

Cause

This scenario is more likely to occur in large clusters, or clusters with large amounts of resources. KSM runs as a single replica Deployment and lists almost all resources in the cluster like Pods, Deployments, DaemonSets, ConfigMaps, Secrets, and PersistentVolumes. Metrics are generated on each of these resource objects. If any of the resources has many objects, like a cluster with over 10,000 Pods, KSM potentially runs out of memory.

Affected versions

This issue could be experienced in any version of Google Distributed Cloud.

The default CPU and memory limit have been increased in the last few Google Distributed Cloud versions, so these resource issues should be less common.

Fix and workaround

To check if your problem is because of out of memory problems, review the following steps:

  • Use kubectl describe pod or kubectl get pod -o yaml and check the error status message.
  • Check the memory consumption and utilization metric for KSM and confirm if it's reaching the limit before getting restarted.

If you confirm that out of memory problems are the issue, use either one of the following solutions:

  • Increase the memory request and limit for KSM.

    To adjust the CPU and memory of KSM:

    1. For Google Distributed Cloud versions 1.9 and earlier, 1.10.6 or earlier, 1.11.2 or earlier, and 1.12.1 or earlier:

      1. No good long-term solution - if you edit the KSM related resource, changes are automatically reverted by monitoring-operator.

      2. You can scale down monitoring-operator to 0 replicas, then edit the KSM Deployment to adjust its resource limit. However, the cluster won't receive vulnerability patches delivered by new patch releases using monitoring-operator.

        Remember to scale monitoring-operator back up after the cluster is upgraded to a later version with fix.

    2. For Google Distributed Cloud versions 1.10.7 or later, 1.11.3 or later, 1.12.2 or later, and 1.13 and later, create a ConfigMap named kube-state-metrics-resizer-config in the kube-system namespace (gke-managed-metrics-server for 1.13 or later) with the following definition. Adjust the CPU and memory numbers as desired:

      apiVersion: v1
kind: ConfigMap
metadata:
  name: kube-state-metrics-resizer-config
  namespace: kube-system
data:
  NannyConfiguration: |-
  apiVersion: nannyconfig/v1alpha1
  kind: NannyConfiguration
  baseCPU: 200m
  baseMemory: 1Gi
  cpuPerNode: 3m
  memoryPerNode: 20Mi

      1. After creating the ConfigMap, restart the KSM Deployment by deleting the KSM Pod using the following command:

          kubectl -n kube-system rollout restart deployment kube-state-metrics
  ```

  • Reduce the number of metrics from KSM.

    For Google Distributed Cloud 1.13, KSM only exposes a smaller number of metrics called Core Metrics by default. This behavior means that resource usage is smaller than previous versions, but the same procedure can be followed to further reduce the number of KSM metrics.

    For Google Distributed Cloud versions earlier than 1.13, KSM uses the default flags. This configuration exposes a large number of metrics.

gke-metrics-agent crash looping

If gke-metrics-agent only experiences out of memory issues on the node where kube-state-metrics exists, the cause is a large number of kube-state-metrics metrics. To mitigate this issue, scale down stackdriver-operator and modify KSM to expose a small set of needed metrics as detailed in the previous section. Remember to scale back up stackdriver-operator after the cluster is upgraded to Google Distributed Cloud 1.13 where KSM by default exposes a smaller number of Core Metrics.

For issues that aren't related to out of memory events, check the Pods logs of gke-metric-agent. You can adjust CPU and memory for all gke-metrics-agent Pods by adding the resourceAttrOverride field to the Stackdriver custom resource.

stackdriver-metadata-agent crash looping

Symptom

No system metadata label is available when filtering metrics in Cloud Monitoring.

Cause

The most common case of stackdriver-metadata-agent crash looping is because of out of memory events. This event is similar to kube-state-metrics. Although stackdriver-metadata-agent isn't listing all resources, it still lists all objects for the relevant resource types like Pods, Deployments, and NetworkPolicy. The agent runs as a single replica Deployment, which increases the risk of out of memory events if the number of objects is too great.

Affected version

This issue could be experienced in any version of Google Distributed Cloud.

The default CPU and memory limit has been increased in the last few Google Distributed Cloud versions, so these resource issues should be less common.

Fix and workaround

To check if your problem is because of out of memory problems, review the following steps:

  • Use kubectl describe pod or kubectl get pod -o yaml and check the error status message.
  • Check the memory consumption and utilization metric for stackdriver-metadata-agent and confirm if it's reaching the limit before getting restarted.
If you confirm that out of memory issues are causing problems, increase the memory limit in the resourceAttrOverride field of the Stackdriver custom resource.

metrics-server crash looping

Symptom

Horizontal Pod Autoscaler and kubectl top don't work in your cluster.

Cause and affected versions

This issue isn't very common, but is caused by out of memory errors in large clusters or in clusters with high Pod density.

This issue could be experienced in any version of Google Distributed Cloud.

Fix and workaround

Increase metrics server resource limits. In Google Distributed Cloud version 1.13 and later, the namespace of metrics-server and its config has been moved from kube-system to gke-managed-metrics-server.

What's next

If you need additional assistance, reach out to Google Support.