Apache Airflow

This document describes how to configure your Google Kubernetes Engine deployment so that you can use Google Cloud Managed Service for Prometheus to collect metrics from StatsD. This document shows you how to do the following:

Set up StatsD to report metrics.
Configure a PodMonitoring resource for Managed Service for Prometheus to collect the exported metrics.
Access a dashboard in Cloud Monitoring to view the metrics.
Configure alerting rules to monitor the metrics.

These instructions apply only if you are using managed collection with Managed Service for Prometheus. If you are using self-deployed collection, then see the Airflow documentation for installation information.

These instructions are provided as an example and are expected to work in most Kubernetes environments. If you are having trouble installing an application or exporter due to restrictive security or organizational policies, we recommend you consult open-source documentation for support.

For information about Airflow, see Airflow.

Prerequisites

To collect metrics from StatsD by using Managed Service for Prometheus and managed collection, your deployment must meet the following requirements:

Your cluster must be running Google Kubernetes Engine version 1.21.4-gke.300 or later.
You must be running Managed Service for Prometheus with managed collection enabled. For more information, see Get started with managed collection.

The official Airflow Helm chart includes a StatsD deployment that exposes Prometheus-format metrics automatically.

To verify that StatsD is emitting metrics on the expected endpoints, do the following:

Set up port forwarding by using the following command:

kubectl -n NAMESPACE_NAME port-forward deploy/AIRFLOW_RELEASE_NAME-statsd 9102

Access the endpoint localhost:9102/metrics by using the browser or the curl utility in another terminal session.

Define a PodMonitoring resource

For target discovery, the Managed Service for Prometheus Operator requires a PodMonitoring resource that corresponds to the Airflow exporter in the same namespace.

You can use the following PodMonitoring configuration:

# Copyright 2022 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

apiVersion: monitoring.googleapis.com/v1
kind: PodMonitoring
metadata:
  name: airflow
  labels:
    app.kubernetes.io/name: airflow
    app.kubernetes.io/part-of: google-cloud-managed-prometheus
spec:
  endpoints:
  - port: 9102
    scheme: http
    interval: 30s
    path: /metrics
  selector:
    matchLabels:
      tier: airflow
      component: statsd
      release: airflow

Ensure that the values of the port and matchLabels fields match those of the StatsD pods you want to monitor. The labels and values shown here are set by default when Airflow is deployed with Helm.

To apply configuration changes from a local file, run the following command:

kubectl apply -n NAMESPACE_NAME -f FILE_NAME

You can also use Terraform to manage your configurations.

Define rules and alerts

You can use the following Rules configuration to define alerts on your Airflow metrics:

# Copyright 2022 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

apiVersion: monitoring.googleapis.com/v1
kind: Rules
metadata:
  name: airflow-rules
  labels:
    app.kubernetes.io/component: rules
    app.kubernetes.io/name: airflow-rules
    app.kubernetes.io/part-of: google-cloud-managed-prometheus
spec:
  groups:
  - name: airflow
    interval: 30s
    rules:
    - alert: AirflowDAGImportErrors
      annotations:
        description: |-
          Airflow dag import errors
            VALUE = {{ $value }}
            LABELS: {{ $labels }}
        summary: Airflow dag import errors (instance {{ $labels.instance }})
      expr: airflow_dag_processing_import_errors > 0
      for: 5m
      labels:
        severity: critical

To apply configuration changes from a local file, run the following command:

kubectl apply -n NAMESPACE_NAME -f FILE_NAME

You can also use Terraform to manage your configurations.

For more information about applying rules to your cluster, see Managed rule evaluation and alerting.

You can adjust the alert thresholds to suit your application.

Verify the configuration

You can use Metrics Explorer to verify that you correctly configured the Airflow exporter. It might take one or two minutes for Cloud Monitoring to ingest your metrics.

To verify the metrics are ingested, do the following:

In the navigation panel of the Google Cloud console, select Monitoring, and then select Metrics explorer:
Go to Metrics explorer
In the toolbar of the query-builder pane, select the button whose name is either MQL or PromQL.
Verify that PromQL is selected in the Language toggle. The language toggle is in the same toolbar that lets you format your query.

Enter and run the following query:

up{job="airflow", cluster="CLUSTER_NAME", namespace="NAMESPACE_NAME"}

View dashboards

The Cloud Monitoring integration includes the Airflow Prometheus Overview dashboard. Dashboards are automatically installed when you configure the integration. You can also view static previews of dashboards without installing the integration.

To view an installed dashboard, do the following:

In the navigation panel of the Google Cloud console, select Monitoring, and then select Dashboards:
Go to Dashboards
Select the Dashboard List tab.
Choose the Integrations category.
Click the name of the dashboard, for example, Airflow Prometheus Overview.

To view a static preview of the dashboard, do the following:

In the navigation panel of the Google Cloud console, select Monitoring, and then select Integrations:
Go to Integrations
Click the Kubernetes Engine deployment-platform filter.
Locate the Apache Airflow integration and click View Details.
Select the Dashboards tab.

Troubleshooting

For information about troubleshooting metric ingestion problems, see Problems with collection from exporters in Troubleshooting ingestion-side problems.