> For the complete documentation index, see [llms.txt](https://docs.onelens.cloud/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.onelens.cloud/integrations/kubernetes/enable-cost-allocation-for-gke.md).

# Enable Cost Allocation for GKE

To view pod-level GKE costs in OneLens, you need to enable **GKE cost allocation** on each cluster and make sure your Cloud Billing data reaches OneLens through the **detailed BigQuery export**:

1. **GKE cost allocation**: a per-cluster flag that stamps Kubernetes identity (cluster, namespace, workload, pod labels) onto your billing rows.
2. **Detailed Cloud Billing export to BigQuery**: the only export that carries these labels. The *standard* export does not.

GKE cost allocation is **off by default and set per cluster**. Every cluster you want split must be enabled individually.

{% hint style="warning" %}
**There is no backfill.** Labels only exist on usage generated *after* enablement, so any period before that date is permanently un-splittable. Enable this early.
{% endhint %}

## Step-by-Step Guide

{% stepper %}
{% step %}

### Enable GKE Cost Allocation

Enable it per cluster using any of the following.

**gcloud CLI:**

```bash
gcloud container clusters update CLUSTER_NAME \
  --enable-cost-allocation
```

**Google Cloud Console:**

1. Go to **Kubernetes Engine → Clusters** and click the cluster name to open its details page.
2. On the **Details** tab, scroll to the **Features** section and click the edit (pencil) icon next to **Cost allocation**.
3. Tick **Enable GKE cost allocation**, then **Save changes**.

{% hint style="info" %}
Enabling causes no node recreation, restart, or disruption. It is a control-plane metadata flag.
{% endhint %}
{% endstep %}

{% step %}

### Ensure the Detailed BigQuery Billing Export Is Configured

The Kubernetes labels are written **only** to the Cloud Billing **detailed** usage cost export. If you are on the *standard* export, the labels will appear to be missing.

1. In the Cloud Console, go to **Billing → Billing export → BigQuery export**.
2. Confirm **Detailed usage cost** is enabled and pointed at a BigQuery dataset.
3. Verify the export table name contains the `_resource_` infix, e.g.:

   `PROJECT.DATASET.gcp_billing_export_resource_v1_XXXXXX_XXXXXX_XXXXXX`

This is the same detailed export OneLens ingests, so no additional OneLens configuration is required once cost allocation is on.
{% endstep %}

{% step %}

### Verify Cost Allocation Is Active

**gcloud CLI:**

```bash
gcloud container clusters describe CLUSTER_NAME \
  --region REGION \
  --format="value(costManagementConfig.enabled)"
```

Expect `True`.

**Console:** the state shows next to **Cost allocation** in the cluster's **Features** list.
{% endstep %}
{% endstepper %}

## What OneLens Uses

Once enabled, GKE adds these Google-generated keys to the `labels` array of each billing row. OneLens reads them to attribute cluster spend below the node:

| Label key               | Value                     | Purpose                                                                               |
| ----------------------- | ------------------------- | ------------------------------------------------------------------------------------- |
| `goog-k8s-cluster-name` | Cluster name              | Attribute costs by cluster (pair with project ID, since names aren't globally unique) |
| `k8s-namespace`         | Namespace                 | Split costs by namespace                                                              |
| `k8s-workload-name`     | Workload name             | Attribute to a specific workload                                                      |
| `k8s-workload-type`     | e.g. `apps/v1-Deployment` | Identify the controller (fully-qualified `apiVersion-Kind`)                           |
| `k8s-label/${key}`      | Pod label value           | Your own pod labels (team, env, service) propagate to billing                         |

## Notes & Limitations

* **Request-based allocation:** costs reflect resource *requests*, not consumption. A pod requesting 4 vCPU and using 0.1 is charged for 4.
* **Up to 3 days latency** before data appears in Cloud Billing after enabling.
* **Standard clusters** are the documented/tested target. On Autopilot the flag can be set but unsupported resources won't accrue (expect `goog-k8s-unsupported-sku` / `goog-k8s-unknown` / blanks).
* **Supported SKUs:** vCPU, RAM, GPU, Persistent Disks, Cloud TPU v4+. A4/A4X instances and externally-managed nodes are not tracked.
* **Persistent Disks** are attributed only when dynamically provisioned (PVC/ephemeral), access mode RWO/RWOP, and alive for at least 30 minutes.
* **Shared-CUD costs** may land in `goog-k8s-unsupported-sku` instead of a real namespace.
* **50-label cap:** pods with more than 50 Kubernetes labels surface none in billing.
* **BigQuery cost:** enabling increases label/namespace cardinality, modestly raising BigQuery storage and query costs.


---

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