# Get Running with Apache Flink on Kubernetes, part 1 of 2

DevFeed: [Get Running with Apache Flink on Kubernetes, part 1 of 2](<https://devfeed.tech/articles/get-running-with-apache-flink-on-kubernetes-part-1-of-2-18822.md>)

Original publisher: [Read original article](<https://www.morling.dev/blog/get-running-with-apache-flink-on-kubernetes-1/>)

Published: 2025-01-21T00:00:00Z

Content type: tutorial

Language: en

Sources: [Gunnar Morling](<https://devfeed.tech/sources/gunnar-morling.md>)

Topics: [apache-flink](<https://devfeed.tech/topics/apache-flink.md>), [Kubernetes](<https://devfeed.tech/topics/kubernetes.md>), [Deployment](<https://devfeed.tech/topics/deployment.md>), [Provisioning](<https://devfeed.tech/topics/provisioning.md>), [container images](<https://devfeed.tech/topics/container-images.md>)

Tags: [apache-flink](<https://devfeed.tech/tags/apache-flink.md>), [container-images](<https://devfeed.tech/tags/container-images.md>), [deployment](<https://devfeed.tech/tags/deployment.md>), [installation](<https://devfeed.tech/tags/installation.md>), [kubernetes](<https://devfeed.tech/tags/kubernetes.md>), [operator](<https://devfeed.tech/tags/operator.md>), [provisioning](<https://devfeed.tech/tags/provisioning.md>)

## AI overview

A two-part tutorial on deploying Apache Flink jobs on Kubernetes using the upstream Flink Kubernetes Operator. Part one covers installation, setup, custom-resource deployment, and building container images; part two addresses fault tolerance, high availability, savepoints, observability, and UI access.

## Source excerpt

Table of Contents Installation and Setup Deployment Types Deploying Your First Flink Job on Kubernetes Building Custom Job Images This post originally appeared on the Decodable blog. All rights reserved. Kubernetes is a widely used deployment platform for Apache Flink. While Flink has had native support for Kubernetes for quite a while, it is in particular the operator pattern which makes deploying Flink jobs onto Kubernetes clusters a compelling option: you define jobs in a declarative resource, and a control loop running in a component called a Kubernetes operator takes care of provisioning and maintaining (e.g. scaling, updating) all the required resources. Automation is the keyword here, significantly reducing the manual effort required for running Flink jobs in production.