https://store-images.s-microsoft.com/image/apps.65458.d4a26836-a50a-4eee-ad23-3a181bc47b60.94b8c4ad-6c48-42c6-8584-73495166f1d0.dd1bdd9c-5496-421b-8978-6657d71e7ed4

Apache Airflow container Image

Kockpit Analytics Pvt. Ltd

(1 valutazioni)

Apache Airflow container Image

Kockpit Analytics Pvt. Ltd

(1 valutazioni)

Experience the ease and speed of setting up your workspaces with Kockpit’s pre-configured images. Airflow, a virtual machine image (VMI), enables you

About the Airflow Container:

Now you can enjoy the quick and hassle-free configuration of your workspaces with Kockpit’s pre-configured images. Airflow is a virtual machine image (VMI) that allows you to set up your machines within minutes.

In this Azure MarketPlace Image, we have packed an airflow container inside the virtual machine. The Airflow Dags are stored in the /usr/local directory. Here, You can create and modify your dags.

You don't need to execute a script in order to access Airflow Image. To utilize Airflow, all you have to do is build a virtual machine (VM) from the marketplace.

Airflow’s rich user interface makes it easy to visualize pipelines running in production, monitor progress, and troubleshoot issues when needed. It connects with multiple data sources and can send an alert via email or Slack when a task completes or fails. Airflow is distributed, scalable, and flexible, making it well-suited to handle the orchestration of complex business logic.

The distribution of Airflow is based on Linux and is provided by Kockpit Analytics Pvt. Ltd. Airflow Container is designed for Production Environments on Azure.

Benefits of using Airflow Container VMI

  • Low code strategy: Set your workspace without typing a single line of code. Kockpit has a packed airflow container in a VM, allowing you to set up your workspace without complex coding.
  • Simple to use: While manual setup can be complex and time-consuming, with the Airflow container image, You just need your VM IP and Port 8181 to connect with your Airflow UI and manage your dags.
  • Require less time: No Hassle to deploy airflow in an open environment because it takes a lot of time and effort to deploy airflow in a normal environment or consider a container.
  • Complexity: Kockpit follows a low code approach, making it less complex to use airflow containers and dags. It might be challenging to write complicated airflows yaml’s and create a container out of them.

How to Use the Image:

    1. To use the image, click on the “Get it now” button located beneath the Kockpit logo.
    2. Fill out the necessary details, and then you will be redirected to the Azure portal.
    3. Then, click on the create button to create your virtual machine.
    4. Fill out the details such as VM Name, region, username, and password, and click on review + create.

And that’s it! Your VM is now created. To know how to deploy Airflow, refer to our Documentation located in the Usage Information + Support section.

VM Configuration:

This VM contains an up-to-date Container version of Apache Airflow.

Disclaimer: Kockpit does not offer commercial licenses for any of the products mentioned above. The products come with open-source licenses.

Note: Apache Airflow, Apache, Airflow, the Airflow logo, and the Apache feather logo are either registered trademarks or trademarks of The Apache Software Foundation. All other products or name brands are trademarks of their respective holders, including The Apache Software Foundation.

The software is licensed under Apache License 2.0

https://store-images.s-microsoft.com/image/apps.5055.d4a26836-a50a-4eee-ad23-3a181bc47b60.8ae60cdb-3c6b-42b4-a288-d4d99fd17e1c.74247c62-92a0-4e12-9287-31efda16f2c8
https://store-images.s-microsoft.com/image/apps.5055.d4a26836-a50a-4eee-ad23-3a181bc47b60.8ae60cdb-3c6b-42b4-a288-d4d99fd17e1c.74247c62-92a0-4e12-9287-31efda16f2c8
https://store-images.s-microsoft.com/image/apps.33268.d4a26836-a50a-4eee-ad23-3a181bc47b60.8ae60cdb-3c6b-42b4-a288-d4d99fd17e1c.54e6c17a-2dcf-436f-b89d-6302cd4766b0
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https://store-images.s-microsoft.com/image/apps.4822.d4a26836-a50a-4eee-ad23-3a181bc47b60.8ae60cdb-3c6b-42b4-a288-d4d99fd17e1c.f18f9129-b761-4226-a0ad-b7beb2b794d8