This product has charges associated with it for the build, maintenance, and support of the Amazon Machine Image (AMI). Apache Airflow is a tool that allows users to programmatically create, schedule, and monitor workflows. It's a popular tool for data engineers and other data professionals to automate the management of data pipelines and other complex workflows. You can easily visualize your data pipelines, dependencies, progress, logs, code, trigger tasks, and success status.
This is a repackaged open-source software product wherein additional charges apply for support and for providing it in a simple consumable AMI. Apache Airflow is a tool that allows users to programmatically create, schedule, and monitor workflows. With Airflow, users can author workflows as Directed Acyclic Graphs (DAGs) of tasks. 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 is completed or fails. Airflow is distributed, scalable, and flexible, making it well-suited to handle the orchestration of complex business logic. It is highly scalable and extensible, making it a good choice for automating complex data pipelines.
Highlights
- The web server provides a user interface for managing Airflow workflows.
- Can automate a wide range of tasks.
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
You pay by the hour based on the EC2 instance size you launch this Apache Airflow image on. All eight options run the same pre-packaged software stack; they differ only in compute capacity. The t3 options (nano, small, medium, large) are burstable instances suited to lighter or variable workloads. The m6a, m7a, and m7i options (medium and large) are general-purpose instances for steadier processing needs. Hourly rates scale with the size and family you choose. Billing is usage-based, so you pay only for the hours each instance runs, added to your AWS bill.
Top-of-mind questions for buyers
What do I actually get when I launch one of these hourly instances?
You get a ready-to-run Apache Airflow stack on Ubuntu, installed as containers. It includes the API server, DAG processor, scheduler, triggerer, worker, a metadata database, and a message broker. A sample workflow comes pre-installed so you can confirm everything runs after launch.
Am I charged when my instance is stopped or paused?
The software fee meters running hours only, so a fully stopped instance stops accruing that charge. But underlying AWS resources, such as storage attached to a stopped instance, may still bill separately through AWS. You pay the hourly software rate only while the instance is running.
If I need a bigger instance later, how does switching sizes affect my bill?
Each size bills at its own hourly rate, so your cost changes when you switch. Moving to a different family or size is a manual step you control by launching that instance type. You pay the rate matching whichever instance is currently running, added to your AWS bill.
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An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
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This product has charges associated with it for the build, maintenance, and support of the Amazon Machine Image (AMI). Apache Airflow is a tool that allows users to programmatically create, schedule, and monitor workflows. It's a popular tool for data engineers and other data professionals to automate the management of data pipelines and other complex workflows. You can easily visualize your data pipelines, dependencies, progress, logs, code, trigger tasks, and success status.
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