Pipeline Orchestration

What is Apache Airflow, and How to Deploy It in an Enterprise Data Stack?

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What is Apache Airflow?

Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows. It is designed to be dynamic, extensible, and scalable, allowing users to easily define and orchestrate complex workflows as directed acyclic graphs (DAGs) of tasks. Airflow is often used in data engineering and machine learning pipelines, and has a large and active community of developers and users.

Read more about Apache Airflow

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Use cases for Apache Airflow

Generate Real-World Evidence for Healthcare Decisions

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Why is Apache Airflow better on Shakudo?

Instant scalability

Shakudo Platform serves Apache Airflow on Kubernetes. Data engineers and developers can unlock increased stability and autoscaling capabilities of a Kubernetes cluster without taking time to setup.

Maintenance free

Every tool your team use on top of the Shakudo platform is connected to be compatible with each other.

End-to-end

You can develop code in Python push it to your git repository and set up your Directed Acryclic Graph (DAGs)

Why is Apache Airflow better on Shakudo?

Core Shakudo Features

Secure infrastructure

Deploy Shakudo easily on your VPC, on-premise, or on our managed infrastructure, and use the best data and AI tools the next day.
integrate

Integrate with everything

Empower your team with seamless integration to the most popular data & AI framework and tools they want to use.

Streamlined Workflow

Automate your DevOps completely with Shakudo, so that you can focus on building and launching solutions.

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Neal Gilmore