Thanos Integration (New/Beta)

This Integration is currently in Beta, contact Finout Support to enable.

Overview

Centralized Prometheus Monitoring via Thanos exposes a single, PromQL-compatible API endpoint that aggregates metrics from multiple Prometheus servers across clusters. All metrics are accessible through a single endpoint, allowing Finout to retrieve them without querying each cluster separately for a more efficient approach in large, multi-cluster environments. For a holistic introduction to Prometheus in Finout and alternative topologies, see the Prometheus Integration Overview.

Finout provides a consistent Kubernetes enrichment process across AWS, GCP, and Azure. Metrics are exported to your connected S3 bucket, where Finout automatically reads and uses them to enrich cloud providers data with Kubernetes abstractions.

Note: The Prometheus onboarding flow has been revamped to consider Centralized Monitoring tools and allow you to control which Cloud cost centers are enriched. To use this flow, contact Support at [email protected].

Thanos Setup at a Glance

1. Set Collection Method: Name your integration and select your metrics collection method.

2. Connect S3 Bucket: The destination for Kubernetes metrics.

3. Set cronjob permissions: This allows the cronjob to write the metrics into your S3 bucket.

4. Configure the create cronjob YAML using the template, and deploy it in the cluster.

   1. Select the authentication method.

   2. Set the required environment variables in the YAML and make additional adjustments, then deploy it in your cluster.

5. Select cost centers: This enriches with the integrated Kubernetes metrics.

6. Validate your Kubernetes Integration: Ensure that the Prometheus metrics are exported correctly to S3.

What happens next:

Finout creates a centralized Prometheus Cost Center that connects all clusters monitored by Thanos, links it to your existing AWS Cost Center, and starts enrichment. Kubernetes cost data usually appears in Finout within about two days, reflecting normal cloud billing delays.

Note:

• This flow is very similar to the Per-Cluster integration, with a few YAML adjustments (notably the Mimir endpoint and authentication variables). We’ll link to the Per-Cluster guide and list the specific Mimir auth options and examples later in this doc.

• Linking a Prometheus Cost Center to a non-AWS Cost Center (GCP or Azure) currently requires Support to complete on Finout’s side and cannot be done in-app.

1. Set Collection Method

1. In Finout, navigate to Settings > Cost Centers > Prometheus (Kubernetes). The Set Collection Method step appears.

   
2. Name your Prometheus integration.

3. Set your metrics collection method: Select Centralized Prometheus Monitoring Tool.

   
4. Select Thanos.

   Note: This configuration will affect the following steps; adjust them accordingly.

5. Click Next. The Connect S3 Bucket step appears.

2. Connect S3 Bucket

1. Connect a S3 bucket that contains the Kubernetes metrics collected from Prometheus using this integration. Finout is granted read-only permissions to access the data. Ensure that you have already connected an S3 bucket to Finout for the AWS Cost and Usage Report (CUR). You can reuse the same S3 bucket and IAM role, and Finout will automatically populate the Role ARN, Bucket name, and External ID fields in the console. If you want to use a different S3 bucket or haven’t configured one yet, follow the steps in Grant Finout Access to an S3 Bucket. Fill in the following fields:

   1. External ID - this is taken from your existing AWS Cost Center and is filled in by default. Use this same External ID in the IAM role’s trust policy to grant Finout permissions to read from the S3 bucket that stores your Prometheus metrics.

   2. ARN Role - Provide the ARN of the IAM role that grants Finout read-only access to this S3 bucket. When creating or updating this role, make sure you use the External ID from the Finout console in the role’s trust policy.

   3. Bucket Name - Enter the name of the S3 bucket that stores your Prometheus metrics. Use the bucket name only (no s3:// and no path). It must be in the Region you selected and readable by the Role ARN.

   4. S3 prefix - S3 prefix (folder path) in the bucket used to store Prometheus metrics (default is k8s/prometheus).

   5. Region - AWS region of the bucket (e.g., us-east-1). Must match the bucket’s actual region.

2. Click Next.

Note: Finout supports enriching AWS (EKS), GCP (GKE), and Azure (AKS) Kubernetes costs using Kubernetes metrics. However, this integration currently requires the Kubernetes metrics to be uploaded to an AWS S3 bucket. To connect other cost centers, contact Finout Support at [email protected].

Important:

• If you want to integrate Finout with more than one cluster, repeat Step 3 (Set CronJob Permissions) and Step 4 (Configure and Create the Cronjob) for each cluster. If the clusters belong to the same Cost Center, make sure they all use the same S3_PREFIX.

• The values BUCKET_NAME and S3_PREFIX across steps 3 and 4 need to be identical to the values added in this step.

3. Set CronJob Permissions

In this step, you will grant the cronjob permissions to write the Kubernetes metrics into the bucket you configured in the previous step.

1. Configure Policy: Attach this policy to the Kubernetes node role, or to the IAM role used by your CronJob, so the CronJob has the S3 access it needs:

   • Write to store exported metrics in your bucket.

   • Read to check its saved state in the bucket and know from which timestamp to continue.

   • Delete to remove files from the bucket older than the retention period (30 days by default, configurable).

   {
     "Version": "2012-10-17",
     "Statement": [
       {
         "Sid": "FinoutBucketPermissions",
         "Effect": "Allow",
         "Action": "s3:ListBucket",
         "Resource": "arn:aws:s3:::<BUCKET_NAME>",
         "Condition": {
           "StringEquals": {
             "s3:delimiter": "/"
           },
           "StringLike": {
             "s3:prefix": "<S3_PREFIX>*"
           }
         }
       },
       {
         "Sid": "FinoutMetricFilesPermissions",
         "Effect": "Allow",
         "Action": [
           "s3:PutObject",
           "s3:GetObject",
           "s3:DeleteObject"
         ],
         "Resource": "arn:aws:s3:::<BUCKET_NAME>/<S3_PREFIX>/*"
       }
     ]
   }
   

2. Prepare kube-state-metrics (Prerequisite): Use kube-state-metrics version 2.0.0 or later. If your cluster uses the prometheus-kube-state-metrics DaemonSet, add the flag below so kube-state-metrics exports all required labels to your Prometheus endpoint (you can adjust the pattern to match your setup):

   --metric-labels-allowlist=pods=[*],nodes=[*] ​Do this by adding an arg to the kube-state-metrics container, for example:

   spec:
   containers:
     args:
      --port=8080
      --metric-labels-allowlist=pods=[*],nodes=[*]

3. Click Next.

4. Configure and Create the CronJob

1. Identify your authentication method: Select the authentication method you use to access the API from the options listed below. After selecting your method, you’ll add the corresponding environment variables and their values to the CronJob YAML in the next step.

   1. No authentication - For self-managed methods. No required environment variable.

   2. API Token authentication - Static token sent as a token header (with Content-Type: application/json) on Prometheus requests. PROMETHEUS_AUTH_TOKEN

   3. Bearer Token authentication -Bearer token placed in the Authorization: Bearer header for Prometheus calls. PROMETHEUS_BEARER_AUTH_TOKEN.

   4. Username and Password authentication

      1. PROMETHEUS_USERNAME

      2. PROMETHEUS_PASSWORD

         • Basic Auth credentials sent on Prometheus requests.

   5. Tenant ID - PROMETHEUS_X_SCOPE_ORGID

      • Tenant ID sent in X-Scope-OrgID header, for multi-tenant setups.

2. Copy the CronJob configuration below to a file (for example, cronjob.yaml), make sure to include the relevant authentication environment variable you selected at the previous step:

Example YAML:

Note: Add your relevant authentication method environment variables and values from the previous step.

apiVersion: batch/v1
kind: CronJob
metadata:
 name: finout-prometheus-exporter-job
spec:
 successfulJobsHistoryLimit: 1
 failedJobsHistoryLimit: 1
 concurrencyPolicy: Forbid
 schedule: "*/30 * * * *"
 jobTemplate:
   spec:
     template:
       spec:
         containers:
           - name: finout-prometheus-exporter
             image: finout/finout-metrics-exporter:2.0.0
             imagePullPolicy: Always
             env:
               - name: S3_BUCKET
                 value: "<BUCKET_NAME>"
               - name: S3_PREFIX
                 value: "<S3_PREFIX>"
               - name: CLUSTER_NAME
                 value: "<CLUSTER_NAME>"
               - name: HOSTNAME
                 value: "<PROMETHEUS_SERVICE>.<NAMESPACE>.svc.cluster.local"
               - name: PORT
                 value: 9090
               - name: SCHEME
                 value: "https"
               - name: PATH_PREFIX
                 value: "< Optional path prefix appended to the Prometheus base URL when the API is served under a subpath or reverse proxy (e.g., data/metrics).>"
               - name: CLUSTER_LABEL_NAME
                 value: “<the label name in your metrics indicates the origin cluster>"
         restartPolicy: OnFailure

• This is an example of a CronJob that schedules a Job every 30 minutes.

• The job queries Prometheus with a 5-second delay between queries so as not to overload your Prometheus stack.

1. Modify the suggested YAML file above, if needed.

Thanos YAML Environment Variables:

Category	Variable	Description	Required / Optional	Default Value	Notes
Scope & Multi-Cluster Behavior	CLUSTER_LABEL_NAME	The cluster label name defines the label whose values represent cluster names in your metrics , allowing Finout to identify and group metrics by cluster from the single metrics endpoint.	Required	cluster	The value is "cluster" by default.
Endpoint & Connectivity	METRICS_READINESS_PATH	Allows Finout’s exporter to perform readiness validation, ensuring the Thanos API is fully available before scraping begins, using a custom readiness endpoint to change the default config.	Optional	/-/ready	This is unique for Thanos.
Scope & Multi-Cluster Behavior	CLUSTER_NAME	The cluster name defines the folder where metrics are stored in S3 and also appears as the cluster name within the Finout app.	Required	None	Cluster names are extracted directly from the metric data. However, this environment variable is still required and determines the folder name under which all centralized metrics will be temporarily stored. It is recommendedto set it to the name of the cluster where the cronjob is deployed.

Auth & Identity	PROMETHEUS_AUTH_TOKEN	Static token sent as a token header (with Content-Type: application/json) on Prometheus requests.	Optional	None	-----
Auth & Identity	PROMETHEUS_BEARER_AUTH_TOKEN	Bearer token placed in the Authorization: Bearer header for Prometheus calls.	Optional	None	-----
Auth & Identity	PROMETHEUS_USERNAME	The Prometheus username. It is recommended to use with the password.	Optional	None	-----
Auth & Identity	PROMETHEUS_PASSWORD	Basic Auth credentials sent on Prometheus requests.	Optional	None	-----
Auth & Identity	PROMETHEUS_X_SCOPE_ORGID	Tenant ID sent in X-Scope-OrgID header, for multi-tenant setups.	Optional	None	-----

Auth & Identity	ROLE_ARN	ARN for IAM role to assume for authorization.	Optional	None	Used if assuming a role instead of direct access.
Auth & Identity	ROLE_EXTERNAL_ID	External ID for assumed role.	Optional	None	Only needed if the IAM role requires an external ID.
Storage & Paths	S3_BUCKET	Customer’s S3 bucket to store the exported metrics.	Required	None	Must exist in customer’s environment.
Storage & Paths	S3_PREFIX	S3 prefix where metrics will be stored.	Required	None	For example, k8s/prometheus has to be the same s3_prefix if multiple per cluster integrations within the same cost center config.
Endpoint & Connectivity	SCHEME	The protocol used when calling the Prometheus metrics endpoint: either https or http	Optional	http	-----
Endpoint & Connectivity	PATH_PREFIX	Optional sub-path between host/port and the Prometheus metrics API.	Optional	None	-----
Endpoint & Connectivity	HOSTNAME	The Prometheus compatible API endpoint.	Optional	localhost	Must be reachable from the pod running the Finout exporter cronjob.
Endpoint & Connectivity	PORT	API port	Optional	9090	Standard Prometheus port.
Query Window & Data Volume	TIME_FRAME	Time range per query in seconds.	Optional	3600	Lower values reduce query load and risk of OOM.
Query Window & Data Volume	BACKFILL_DAYS	Days of historical data to fetch on first run.	Optional	3d	Large values increase load and risk of slow queries.
Query Window & Data Volume	INITIAL_BACKFILL_DATE	Defines the initial backfill start date	Optional	None	Available starting from the Exporter’s v2.0.0 value should be in YYYY-MM-DD format. limited to maximum 3 days.
Query Window & Data Volume	QUERIES_BATCH_SIZE	Controls how many queries are processed per batch to manage memory usage.	Optional	5	Available starting from the Exporter’s v2.0.0 Default is 5. Lowering it reduces memory usage but may increase overall runtime. Minimum is 1 If a customer sees OOM kills / memory pressure, recommend reducing QUERIES_BATCH_SIZE before changing anything else.

To configure these fields, add them to the configuration file under the env section and use the name/value format for each desired field.

For example:

env:
  - name: TIME_FRAME
    value: "3600"
  - name: BACKFILL_DAYS
    value: "3d"

Ensure that the field names and the corresponding values are correctly specified to apply the desired configuration.

1. Run the command in a namespace of your choice, preferably the one where the Prometheus stack is deployed: ​kubectl create -f <filename>

2. Trigger the job (instead of waiting for it to start): kubectl create job --from=cronjob/finout-prometheus-exporter-job finout-prometheus-exporter-job -n <namespace>

   The job automatically fetches Prometheus data from 3 days ago up to the current time.

   Note: This can be changed by modifying your BACKFILL_DAYS variable.

3. Click Save. The Prometheus cost center is created.

5. Select Cost Centers

1. Select the cost centers that this integration will enrich with Kubernetes metrics. These cost centers can then attribute Kubernetes costs for supported services (EKS, GKE, and AKS) by namespace, workload, and label.

2. Click Complete Integration. The cost center will be created in about 48 hours.

   

Note:

• If this cost center is already enriched by a Kubernetes integration, ensure there are no overlapping nodes between the integrations to avoid duplicated costs and resources.

• You can hover over every created cloud cost center and see all the Kubernetes cost centers that enrich it.

  

6. Validate Your Kubernetes Integration

Confirm that your Prometheus Integration is working correctly:

S3 Validation

To confirm that Prometheus metrics are being exported correctly to your S3 bucket:

1. Navigate to the S3 path, for example: s3://cur-bucket/k8s/prometheus/prod-cluster/end=20251101/day=5/ You should see a list of metric folders, such as: metric=cpu_requests/

2. Open a metric folder and verify that .json.gz files are uploaded. Each file should have a timestamp prefix, for example: s3://cur-bucket/k8s/prometheus/prod-cluster/end=20251101/day=5/metric=cpu_requests/1759622400_cpu_requests.json.gz If these files appear, the CronJob ran successfully, and Prometheus metric files were generated and stored in the correct S3 structure.

Data Availability

Kubernetes cost and usage data will appear across Finout within 48 hours, matching the standard cloud billing data delivery window.

Note: If any issues occur, share your exporter logs with Finout support at [email protected] for further investigation.

For more information, please see the FAQs and Troubleshooting section. For new updates to the Prometheus Exporter introduced between versions and their impact on cost calculation, refer to the release notes.