11 Running Tasks in Containers

 

This chapter covers:

  • Identifying some challenges involved in managing Airflow deployments that use many different operators, complex dependencies, etc.
  • Examining how containerized approaches can help simplify Airflow deployments by providing a uniform way of building and running tasks, whilst also simplifying dependency management.
  • Running containerized tasks in Airflow on Docker using the DockerOperator and on Kubernetes clusters using the KubernetesPodOperator.
  • Establishing a high-level overview of the workflows involved in developing containerized DAGs based on Docker and Kubernetes.

In previous chapters, we have implemented several DAGs using different Airflow operators, each specialized to perform a specific type of task. In this chapter, we touch upon some of the drawbacks of using many different operators, especially with an eye on creating Airflow DAGs that are easy to build, deploy and maintain. In light of these issues, we take a look at how we can use Airflow to run tasks in containers using Docker and Kubernetes and some of the benefits that this containerized approach can bring.

11.1  Challenges of many different operators

Operators are arguably one of the strong features of Airflow, as they provide great flexibility to coordinate jobs across many different types of systems. However, creating and managing DAGs with many different operators can be quite challenging due to the complexity involved.

11.1.1    Operator interfaces and implementations

11.1.2    Complex and conflicting dependencies

11.1.3    Moving towards a generic operator

11.2  Introducing containers

11.2.1    What are containers?

11.2.2    Running our first Docker container

11.2.3    Creating a Docker image

11.2.4    Persisting data using volumes

11.3  Containers and Airflow

11.3.1    Tasks in containers

11.3.2    Why use containers?

11.4  Running tasks in Docker

11.4.1    Introducing the DockerOperator

11.4.2    Creating container images for tasks

11.4.3    Building a DAG with dockerized tasks

11.4.4    Docker-based workflow

11.5  Running tasks in Kubernetes

11.5.1    Introducing Kubernetes

11.5.2    Setting up Kubernetes

11.5.3    Using the KubernetesPodOperator

11.5.4    Diagnosing Kubernetes-related issues

11.5.5    Differences with Docker-based workflows

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