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# airflow-operator
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// TODO(user): Add simple overview of use/purpose
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# Kubedoop Operator for Apache Airflow
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## Description
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// TODO(user): An in-depth paragraph about your project and overview of use
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[![Build](https://github.com/zncdatadev/airflow-operator/actions/workflows/publish.yml/badge.svg)](https://github.com/zncdatadev/airflow-operator/actions/workflows/publish.yml)
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[![LICENSE](https://img.shields.io/badge/license-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
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[![Go Report Card](https://goreportcard.com/badge/github.com/zncdatadev/airflow-operator)](https://goreportcard.com/report/github.com/zncdatadev/airflow-operator)
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[![Artifact HUB](https://img.shields.io/endpoint?url=https://artifacthub.io/badge/repository/airflow-operator)](https://artifacthub.io/packages/helm/kubedoop/airflow-operator)
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## Getting Started
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This is a Kubernetes operator to manage [Apache Airflow](https://airflow.apache.org/) ensembles.
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### Prerequisites
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- go version v1.22.0+
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- docker version 17.03+.
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- kubectl version v1.11.3+.
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- Access to a Kubernetes v1.11.3+ cluster.
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It's part of the Kubedoop Data Platform, a modular open source data platform built on Kubernetes that provides Kubernetes native deployment
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and management of popular open source data apps like Apache Kafka, Apache Doris, Trino or Apache Spark, all working
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together seamlessly. Based on Kubernetes, it runs everywhere – on prem or in the cloud.
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### To Deploy on the cluster
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**Build and push your image to the location specified by `IMG`:**
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## Quick Start
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```sh
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make docker-build docker-push IMG=<some-registry>/airflow-operator:tag
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```
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**NOTE:** This image ought to be published in the personal registry you specified.
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And it is required to have access to pull the image from the working environment.
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Make sure you have the proper permission to the registry if the above commands don’t work.
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**Install the CRDs into the cluster:**
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```sh
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make install
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```
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### Add helm repository
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**Deploy the Manager to the cluster with the image specified by `IMG`:**
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> Please make sure helm version is v3.0.0+
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```sh
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make deploy IMG=<some-registry>/airflow-operator:tag
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```bash
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helm repo add kubedoop https://zncdatadev.github.io/kubedoop-helm-charts/
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```
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> **NOTE**: If you encounter RBAC errors, you may need to grant yourself cluster-admin
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privileges or be logged in as admin.
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**Create instances of your solution**
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You can apply the samples (examples) from the config/sample:
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```sh
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kubectl apply -k config/samples/
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```
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>**NOTE**: Ensure that the samples has default values to test it out.
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### To Uninstall
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**Delete the instances (CRs) from the cluster:**
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### Add required dependencies
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```sh
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kubectl delete -k config/samples/
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```bash
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helm install commons-operator kubedoop/commons-operator
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helm install listener-operator kubedoop/listener-operator
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helm install secret-operator kubedoop/secret-operator
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```
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**Delete the APIs(CRDs) from the cluster:**
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### Add airflow-operator
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```sh
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make uninstall
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```bash
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helm install airflow-operator kubedoop/airflow-operator
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```
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**UnDeploy the controller from the cluster:**
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### Deploy Airflow cluster
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```sh
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make undeploy
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```bash
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kubectl apply -f config/samples
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```
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## Project Distribution
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## Kubedoop Data Platform Operators
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Following are the steps to build the installer and distribute this project to users.
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These are the operators that are currently part of the Kubedoop Data Platform:
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1. Build the installer for the image built and published in the registry:
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- [Kubedoop Operator for Apache Airflow](https://github.com/zncdatadev/airflow-operator)
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- [Kubedoop Operator for Apache DolphinScheduler](https://github.com/zncdatadev/dolphinscheduler-operator)
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- [Kubedoop Operator for Apache Doris](https://github.com/zncdatadev/doris-operator)
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- [Kubedoop Operator for Apache Hadoop HDFS](https://github.com/zncdatadev/hdfs-operator)
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- [Kubedoop Operator for Apache HBase](https://github.com/zncdatadev/hbase-operator)
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- [Kubedoop Operator for Apache Hive](https://github.com/zncdatadev/hive-operator)
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- [Kubedoop Operator for Apache Kafka](https://github.com/zncdatadev/kafka-operator)
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- [Kubedoop Operator for Apache Kyuubi](https://github.com/zncdatadev/kyuubi-operator)
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- [Kubedoop Operator for Apache Nifi](https://github.com/zncdatadev/nifi-operator)
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- [Kubedoop Operator for Apache Spark](https://github.com/zncdatadev/spark-k8s-operator)
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- [Kubedoop Operator for Apache Superset](https://github.com/zncdatadev/superset-operator)
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- [Kubedoop Operator for Trino](https://github.com/zncdatadev/trino-operator)
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- [Kubedoop Operator for Apache Zookeeper](https://github.com/zncdatadev/zookeeper-operator)
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```sh
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make build-installer IMG=<some-registry>/airflow-operator:tag
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```
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NOTE: The makefile target mentioned above generates an 'install.yaml'
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file in the dist directory. This file contains all the resources built
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with Kustomize, which are necessary to install this project without
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its dependencies.
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2. Using the installer
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And our internal operators: :
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Users can just run kubectl apply -f <URL for YAML BUNDLE> to install the project, i.e.:
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```sh
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kubectl apply -f https://raw.githubusercontent.com/<org>/airflow-operator/<tag or branch>/dist/install.yaml
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```
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- [Commons Operator](https://github.com/zncdatadev/commons-operator)
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- [Listener Operator](https://github.com/zncdatadev/listener-operator)
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- [Secret Operator](https://github.com/zncdatadev/secret-operator)
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## Contributing
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// TODO(user): Add detailed information on how you would like others to contribute to this project
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**NOTE:** Run `make help` for more information on all potential `make` targets
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More information can be found via the [Kubebuilder Documentation](https://book.kubebuilder.io/introduction.html)
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If you'd like to contribute to Kubedoop, please refer to our [Contributing Guide](https://kubedoop.dev/docs/developer-manual/collaboration) for more information.
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We welcome contributions of all kinds, including but not limited to code, documentation, and use cases.
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## License
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Copyright 2024 ZNCDataDev.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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Kubedoop is under the Apache 2.0 license. See the [LICENSE](./LICENSE) file for details.

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