Autoscaling with KEDA¶
This feature is still experimental.
KEDA stands for Kubernetes Event Driven Autoscaling.
KEDA is a custom controller that
allows users to create custom bindings to the Kubernetes Horizontal Pod
Autoscaler.
The autoscaler will adjust the number of active celery workers based on the number
of tasks in queued
or running
state.
helm repo add kedacore https://kedacore.github.io/charts
helm repo update
kubectl create namespace keda
helm install keda kedacore/keda \
--namespace keda \
--version "v2.0.0"
Enable for the airflow instance by setting workers.keda.enabled=true
in your
helm command or in the values.yaml
.
kubectl create namespace airflow
helm repo add apache-airflow https://airflow.apache.org
helm install airflow apache-airflow/airflow \
--namespace airflow \
--set executor=CeleryExecutor \
--set workers.keda.enabled=true \
A ScaledObject
and an hpa
will be created in the airflow namespace.
KEDA will derive the desired number of celery workers by querying Airflow metadata database:
SELECT
ceil(COUNT(*)::decimal / {{ .Values.config.celery.worker_concurrency }})
FROM task_instance
WHERE state='running' OR state='queued'
Note
Set celery worker concurrency through the helm value
config.celery.worker_concurrency
(i.e. instead of airflow.cfg or
environment variables) so that the KEDA trigger will be consistent with
the worker concurrency setting.