Airflow kubernetes
![airflow kubernetes airflow kubernetes](https://miro.medium.com/max/624/0*vW7olQLHnqpyUaXL.png)
or set of tasks within that DAG to execute and be completed from start to. However, this could be a disadvantage depending on the latency needs, since a task takes longer to start using the Kubernetes Executor, since it now includes the Pod startup time.Ĭonsistent with the regular Airflow architecture, the Workers need access to the DAG files to execute the tasks within those DAGs and interact with the Metadata repository. If youre new to Apache Airflow the world of Executors is difficult to navigate. The Kubernetes Executor has an advantage over the Celery Executor in that Pods are only spun up when required for task execution compared to the Celery Executor where the workers are statically configured and are running all the time, regardless of workloads. One example of an Airflow deployment running on a distributed set of five nodes in a Kubernetes cluster is shown below. In contrast to the Celery Executor, the Kubernetes Executor does not require additional components such as Redis and Flower, but does require the Kubernetes infrastructure. Using Airflow to schedule jobs on Kubernetes Running Airflow itself on Kubernetes Do both at the same time You can actually replace Airflow with X, and you will see this pattern all the time.
![airflow kubernetes airflow kubernetes](https://i.pinimg.com/736x/87/2b/d4/872bd44d5bbb8805c48bc47df209f20a.jpg)
The worker pod then runs the task, reports the result, and terminates. When a DAG submits a task, the KubernetesExecutor requests a worker pod from the Kubernetes API. The KubernetesExecutor requires a non-sqlite database in the backend, but there are no external brokers or persistent workers needed.įor these reasons, we recommend the KubernetesExecutor for deployments have long periods of dormancy between DAG execution. The KubernetesExecutor runs as a process in the Scheduler that only requires access to the Kubernetes API (it does not need to run inside of a Kubernetes cluster).