Amazon Managed Workflows for Apache Airflow
Task SchedulingWhat is Amazon Managed Workflows for Apache Airflow?
It is a managed orchestration service for Apache Airflow1 that makes it easier to set up and operate end-to-end data pipelines in the cloud at scale. With Managed Workflows, you can use Airflow and Python to create workflows without having to manage the underlying infrastructure for scalability, availability, and security. Managed Workflows automatically scales its workflow execution capacity to meet your needs, and is integrated with AWS security services to help provide you with fast and secure access to data.
Amazon Managed Workflows for Apache Airflow is a tool in the Task Scheduling category of a tech stack.
Key Features
Deploy Airflow rapidly at scaleRun Airflow with built-in securityReduce operational costsUse a pre-existing plugin or use your own
Amazon Managed Workflows for Apache Airflow Pros & Cons
Pros of Amazon Managed Workflows for Apache Airflow
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Cons of Amazon Managed Workflows for Apache Airflow
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Amazon Managed Workflows for Apache Airflow Alternatives & Comparisons
What are some alternatives to Amazon Managed Workflows for Apache Airflow?
Airflow
Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command lines utilities makes 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.
AWS Step Functions
AWS Step Functions makes it easy to coordinate the components of distributed applications and microservices using visual workflows. Building applications from individual components that each perform a discrete function lets you scale and change applications quickly.
Evernote
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