With Amazon Managed Workflows for Apache Airflow (MWAA) you pay only for what you use. There are no minimum fees or upfront commitments. You pay for the time your Airflow Environment runs plus any additional auto-scaling to provide more worker or web server capacity. Amazon Managed Workflows for Apache Airflow (MWAA) (Amazon MWAA) is a managed service for Apache Airflow that makes it easy for you to build and manage your workflows in the cloud. With Amazon MWAA, you can easily combine data using any of Apache Airflow's open source integrations. You can use the same familiar Apache Airflow platform as you do today to manage their workflows and now enjoy improved scalability, availability, and security without the operational burden of having to manage.
If you are operating a medium Managed Workflows environment in the US East (N. Virginia) region where your variable demand require 10 workers simultaneously for 2 hours a day, and retain 40 GB of data (approximately 200 daily workflows, each with 20 tasks, stored for 6 months), you would pay the following for the month:
Environment charge
Instance usage (in hours) = 31 days x 24 hrs/day = 744 hours
x $0.74 (price per hour for a medium environment in the US East (N. Virginia) region)
= $ 550.56
Instance usage (in hours) = 31 days x 24 hrs/day = 744 hours
x $0.74 (price per hour for a medium environment in the US East (N. Virginia) region)
= $ 550.56
An Apache Airflow UI link is available on the Amazon Managed Workflows for Apache Airflow (MWAA) console after you create an environment. You can use the Amazon MWAA console to view and invoke a DAG in your Apache Airflow UI, or use Amazon MWAA APIs to get a token and invoke a DAG. An Apache Airflow UI link is available on the Amazon Managed Workflows for Apache Airflow (MWAA) console after you create an environment. You can use the Amazon MWAA console to view and invoke a DAG in your Apache Airflow UI, or use Amazon MWAA APIs to get a token and invoke a DAG. This page describes the permissions needed to access the Apache Airflow UI, how to generate a token to make Amazon MWAA API calls directly in your command shell, and the supported commands in the Apache Airflow.
Worker charge
Instance usage (in hours) = 31 days x 2 hrs/day x 9 additional instances (10 less 1 included with environment) = 558 hours
x $0.11 (price per hour for a medium worker in the US East (N. Virginia) region)
= $61.38
Instance usage (in hours) = 31 days x 2 hrs/day x 9 additional instances (10 less 1 included with environment) = 558 hours
x $0.11 (price per hour for a medium worker in the US East (N. Virginia) region)
= $61.38
Meta database charge
40 GB or storage x $0.10 GB-month = $4.00
Total charge = $615.94
40 GB or storage x $0.10 GB-month = $4.00
Total charge = $615.94
If you are operating a small Managed Workflows environment in the US East (N. Virginia) region where each day your system spikes to 50 concurrent workers for an hour, with typical data retention, you would pay the following for the month:
Environment charge
Instance usage (in hours) = 31 days x 24 hrs/day = 744 hours
Product management in practice. x $0.49 (price per hour for a small environment in the US East (N. Virginia) region)
= $364.56
Instance usage (in hours) = 31 days x 24 hrs/day = 744 hours
Product management in practice. x $0.49 (price per hour for a small environment in the US East (N. Virginia) region)
= $364.56
Worker charge
Instance usage (in hours) = 31 days x 1 hrs/day x 49 additional instances (50 less 1 included with environment) = 1519 hours
x $0.055 (price per hour for a small worker in the US East (N. Virginia) region)
= $83.55
Instance usage (in hours) = 31 days x 1 hrs/day x 49 additional instances (50 less 1 included with environment) = 1519 hours
x $0.055 (price per hour for a small worker in the US East (N. Virginia) region)
= $83.55
Apache Airflow Aws Connection
Stone bookends. Meta database charge
10 GB or storage x $0.10 GB-month = $1.00
Total charge = $449.11
10 GB or storage x $0.10 GB-month = $1.00
Total charge = $449.11