Observing hierarchical workloads

Hierarchy Controller gives you better observability into your workloads by using both the hierarchical and abstract namespaces in your cluster. It achieves this by propagating your cluster's tree labels to your Pods, making them available to any system that can ingest Kubernetes labels, including:

For example, consider a workload running in a namespace from the example repository.

Hierarchy Controller lets you select Pods, logs, or usage metering generated by any workload that is a descendant of eng, rnd, or any other abstract namespace. This includes not only the workloads in namespaces located in the Git repository such as gamestore, but also any Hierarchy Controller child namespace that you might create as a descendant of those namespaces.

Enabling hierarchical observability

Hierarchical observability is provided by Hierarchy Controller. To enable hierarchical observability, do the following:

  1. Install Hierarchy Controller.

  2. In the configuration file for the Config Sync Operator, in the spec.hierarchyController object, set the value of enablePodTreeLabels to true:

    # config-management.yaml

apiVersion: configmanagement.gke.io/v1
kind: ConfigManagement
metadata:
  name: config-management
spec:
  hierarchyController:
    enabled: true
    # Set to true to enable hierarchical observability:
    enablePodTreeLabels: true
  # ...other fields...

  3. Apply the configuration:

    kubectl apply -f config-management.yaml

    After about a minute, Hierarchy Controller and hierarchical observability become usable on your cluster.

When hierarchical observability is enabled, Hierarchy Controller installs a mutating admission webhook to add the tree labels onto the Pods. To verify that this webhook is working correctly:

  1. Start a workload in any namespace, such as the following:

    kubectl run websvr --image=nginx --namespace default --generator=run-pod/v1

  2. Inspect the Pod and verify that it contains the default.tree.hnc.x-k8s.io/depth label:

    kubectl describe pod --namespace default websvr

    Output:

    Name:         websvr
Namespace:    default
# ...other fields...
Labels:       default.tree.hnc.x-k8s.io/depth=0 # This is the Pod tree label
              # ...other labels...
# ...other fields...

  3. Clean up the workload:

    kubectl delete pod --namespace default websvr

Existing Pods do not receive the Pod tree labels; these labels are only added to new Pods. For more information, see Limitations, later in this document.

Using hierarchical workload observability

After Pod tree labels are enabled, they can be used to improve hierarchical workload observability both inside clusters and in other Google Cloud products.

Querying Pods by hierarchy

Any Kubernetes operation that includes a label selector can be used to query Pod tree labels. For example, to view all Pods in all namespaces that are running in a descendant of the default namespace, use the following query:

kubectl get pods --all-namespaces -l default.tree.hnc.x-k8s.io/depth

Output based on the sample workload that we created to verify the installation:

NAMESPACE   NAME     READY   STATUS    RESTARTS   AGE
default     websvr   1/1     Running   0          70s

Querying Cloud Logging by hierarchy

Cloud Logging supports a slightly different format for labels than Kubernetes. For example, to search for any workload running in a descendant of the default namespace, instead of searching for the Kubernetes label default.tree.hnc.x-k8s.io/depth, Cloud Logging expects a query similar to the following in the Google Cloud Console:

resource.type="k8s_container" labels.k8s-pod/default_tree_hnc_x-k8s_io/depth!=""

Alternatively, you can use a similar filter in the gcloud command-line tool:

gcloud logging read "resource.type=k8s_container AND labels.k8s-pod/default_tree_hnc_x-k8s_io/depth!=''"

Querying GKE usage metering by hierarchy

You can use Pod tree labels to attribute requests and usages from GKE usage metering to namespace trees. To enable hierarchical usage metering:

  1. Enable regular GKE usage metering on your cluster.

  2. Confirm that the data is being ingested to BigQuery. In the Cloud Console, go to BigQuery.

    Go to BigQuery

  3. Look for gke_cluster_resource_consumption.

  4. Follow the prerequisites for enabling GKE cluster usage metering section to enable visualization for GKE usage metering.

  5. Open Google Data Studio, click Blank Report, and then select BigQuery as the data source.

  6. Select Custom query and search for your project ID. In the text box on the right, enter your customized query. For examples of the custom queries, see the following sections.

Example: total usage of every subtree

This query returns the usage for every regular, abstract, and hierarchical namespace in the cluster, including all their descendants:

SELECT
  REGEXP_EXTRACT(label.key, r"^[a-zA-Z0-9\-]+") as subtree,
  resource_name,
  usage.unit,
  SUM(usage.amount) AS usage_amount
FROM
  `PROJECT_NAME.DATASET_NAME.TABLE_NAME`,
  UNNEST(labels) AS label
WHERE
  regexp_contains(label.key, "tree.hnc.x-k8s.io/depth")
GROUP BY
  subtree,
  resource_name,
  usage.unit
ORDER BY
  resource_name ASC,
  subtree ASC

Partial sample output:

subtree resource_name unit usage_amount
a cpu seconds 0.09
a1 cpu seconds 0.09
a2 cpu seconds 0
a memory byte-seconds 6,315,303,690,240
a1 memory byte-seconds 1,355,268,587,520
a2 memory byte-seconds 4,960,035,102,720

In this example, the usage attributed to namespace a includes the usage of its descendant namespaces a1 and a2, which are also shown.

Example: usage of a single subtree

This query displays the total amount of usage under namespace a and all its descendant namespaces:

SELECT
  resource_name,
  usage.unit,
  SUM(usage.amount) AS usage_amount
FROM
  `PROJECT_NAME.DATASET_NAME.TABLE_NAME`,
  UNNEST(labels) AS label
WHERE
  label.key="SUBTREE_NAME.tree.hnc.x-k8s.io/depth"
GROUP BY
  resource_name,
  usage.unit

Sample output for namespace a:

resource_name unit usage_amount
cpu seconds 0.09
memory byte-seconds 6,315,303,690,240

Example: usage of all namespaces in a subtree

This query displays the individual usage of every namespace in a given subtree:

SELECT
  namespace,
  resource_name,
  SUM(usage.amount) AS usage_amount
FROM
  `PROJECT_NAME.DATASET_NAME.TABLE_NAME`,
  UNNEST(labels) AS label
WHERE
  label.key="SUBTREE_NAME.tree.hnc.x-k8s.io/depth"
GROUP BY
  namespace,
  resource_name

Sample output for namespace a:

namespace resource_name usage_amount
a2 memory 4,960,035,102,720
a1 memory 1,355,268,587,520
a2 cpu 0
a1 cpu 0.09

Namespace a itself contains no usage, so it is not listed in the results of this query.

Limitations of hierarchical monitoring

The following are limitations of hierarchical monitoring.

Changes to the hierarchy are ignored

Pod tree labels are added to Pods when they are created and are not modified after the Pod starts running. This means that Pods that were started before hierarchical monitoring was enabled do not receive Pod tree labels.

In addition, any Pod whose hierarchy changes after the Pod was started—for example, by using Hierarchy Controller to change the parent of a namespace—does not have its labels updated. While hierarchy modifications are typically quite rare, if this situation occurs and is causing a problem, ensure that you restart all affected Pods after modifying the hierarchy.

Pods are still created even if labels cannot be applied

Hierarchical monitoring does not apply to Pods running in key system namespaces such as kube-system or hnc-system. However, the webhook configuration itself has no way to exclude these namespaces. Therefore, if Hierarchy Controller encounters a problem, Pod creation in all namespaces could be impacted.

As a result, rather than risk a cluster-wide outage, if Hierarchy Controller cannot process a Pod within two seconds, the webhook fails and allows the Pod to be created without the labels. Such webhook failures can be monitored via the Kubernetes API server by looking for failures of the podlabel.hierarchycontroller.configmanagement.gke.io mutating admission webhook.

What's next