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Airflow
fully managed by OctaByte

When workflows are defined as code, they become more maintainable, versionable, testable, and collaborative. Use Apache Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Apache Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command line utilities make performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress, and troubleshoot issues when needed.

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Benefits of Airflow fully managed by OctaByte

Deploy a fully managed instance of Airflow in just $9. You can relax knowing that we are taking care of installation, configuration, encryption, security, backups, live monitoring, software & OS updates.

Simple no-tricks pricing
Enjoy transparent and straightforward pricing with no hidden fees or complex terms.
No vendor lock-in
You can migrate your software and data to any where any time you want. With OctaByte you are totally free and in control.
Automated Updates
Let's save your business a lot of hassle, whilst ensuring that you get the performance and security benefits of regularly updated software and systems.
Encrypted Everything
All connections between your computer, the dashboard and your services are encrypted end-to-end with TLS, and all data is encrypted at rest.

Airflow screenshots

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Airflow features Highlight

Pure Python
No more command-line or XML black-magic! Use standard Python features to create your workflows, including date time formats for scheduling and loops to dynamically generate tasks. This allows you to maintain full flexibility when building your workflows.
Useful UI
Monitor, schedule and manage your workflows via a robust and modern web application. No need to learn old, cron-like interfaces. You always have full insight into the status and logs of completed and ongoing tasks.
Robust Integrations
Apache Airflow provides many plug-and-play operators that are ready to execute your tasks on Google Cloud Platform, Amazon Web Services, Microsoft Azure and many other third-party services. This makes Apache Airflow easy to apply to current infrastructure and extend to next-gen technologies.
Easy to Use
Anyone with Python knowledge can deploy a workflow. Apache Airflow does not limit the scope of your pipelines; you can use it to build ML models, transfer data, manage your infrastructure, and more.

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