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https://issues.apache.org/jira/browse/AIRFLOW-6440?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17098794#comment-17098794
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ASF GitHub Bot commented on AIRFLOW-6440:
-----------------------------------------
feluelle commented on pull request #7030:
URL: https://github.com/apache/airflow/pull/7030#issuecomment-623350479
> For now, I'll make this Executor an optional plugin for Airflow. Thank you
all for contributing and your suggestions.
Do I understand it correctly that you want to publish it in your repo rather
than apache/airflow? Then we can close this PR, correct? Just want to be sure
so that the stale bot does not close it if you still want to work on it here :)
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> AWS Fargate Executor (AIP-29) (WIP)
> -----------------------------------
>
> Key: AIRFLOW-6440
> URL: https://issues.apache.org/jira/browse/AIRFLOW-6440
> Project: Apache Airflow
> Issue Type: Improvement
> Components: aws, executors
> Affects Versions: 1.10.8
> Environment: AWS Cloud
> Reporter: Ahmed Elzeiny
> Assignee: Ahmed Elzeiny
> Priority: Minor
> Labels: AWS, Executor, autoscaling
> Original Estimate: 336h
> Remaining Estimate: 336h
>
> h1. Links
> AIP -
> [https://cwiki.apache.org/confluence/display/AIRFLOW/AIP-29%3A+AWS+Fargate+Executor]
> PR - [https://github.com/apache/airflow/pull/7030]
> h1. Airflow on AWS Fargate
> {color:#707070}We propose the creation of a new Airflow Executor, called the
> FargateExecutor, that runs tasks asynchronously on AWS Fargate. The Airflow
> Scheduler comes up with a command that needs to be executed in some shell. A
> Docker container parameterized with the command is passed in as an ARG, and
> AWS Fargate provisions a new instance with . The container then completes or
> fails the job, causing the container to die along with the Fargate instance.
> The executor is responsible for keeping track what happened to the task with
> an airflow task id and AWS ARN number, and based off of the instance exit
> code we either say that the task succeeded or failed.{color}
> h1. Proposed Implementation
> As you could probably deduce, the underlying mechanism to launch, track, and
> stop Fargate instances is AWS' Boto3 Library.
> To accomplish this we create a FargateExecutor under the "airflow.executors"
> module. This class will extend from BaseExecutor and override 5 methods:
> {{start()}}, {{{color:#3366ff}sync(){color}}},{{{color:#3366ff}
> execute_async(){color}}}, {{{color:#3366ff}end(){color}}}, and
> {{{color:#3366ff}terminate(){color}}}. Internally, the FargateExecutor uses
> boto3 for monitoring and deployment purposes.
> {color:#707070}The three major Boto3 API calls are:{color}
> * {color:#707070}The {color:#0747a6}{{execute_async()}}{color} function
> calls boto3's {{{color:#0747a6}run_task(){color}}} function.{color}
> * {color:#707070}The {{{color:#0747a6}sync(){color}}} function calls boto3's
> {{{color:#0747a6}describe_tasks(){color}}} function.{color}
> * {color:#707070}The {{{color:#0747a6}terminate(){color}}} function calls
> boto3's {{{color:#0747a6}stop_task(){color}}} function.{color}
> h1. Maintenance
> The executor itself is nothing special since it mostly relies on overriding
> the proper methods from .
> In general, AWS is fairly committed to keeping their APIs in service. Fargate
> is rather new and I've personally perceived a lot more features added as
> optional parameters over the course of the past year. However, the required
> parameters for the three Boto3 calls that are used have remained the same.
> I've also written test-cases that ensures that the Boto3 calls made are
> complaint to the most current version of their APIs.
> We've also introduced a callback hook (very similar to the Celery Executor)
> that allows users to launch tasks with their own parameters. Therefore if a
> user doesn't like the default parameter options used in Boto3's
> \{{run_task(),}}then they can call it themselves with whatever parameters
> they want. This means that Airflow doesn't have to add a new configuration
> everytime AWS makes an addition to AWS Fargate. It's just one configuration
> to cover them all.
> h1. {color:#707070}Proposed Configuration{color}
>
> {code:java}
> [fargate]
> # For more information on any of these execution parameters, see the link
> below:
> #
> https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/ecs.html#ECS.Client.run_task
> # For boto3 credential management, see
> #
> https://boto3.amazonaws.com/v1/documentation/api/latest/guide/configuration.html
> ### MANDATORY CONFIGS:
> # Name of region
> region = us-west-2
> # Name of cluster
> cluster = test-airflow
> ### EITHER POPULATE THESE:
> # Name of task definition with a bootable-container. Note that this container
> will receive an airflow CLI
> # command as an additional parameter to its entrypoint. It's job is to
> boot-up and run this command
> task_definition = test-airflow-worker
> # name of registered container within your AWS cluster
> container_name = airflow-worker
> # security group ids for task to run in (comma-separated)
> security_groups = sg-xxxxxxxxxxxxxx
> # Subnets for task to run in.
> subnets = subnet-yyyyyyyyyy,subnet-zzzzzzzzz
> # FARGATE platform version. Defaults to Latest.
> platform_version = LATEST
> # Launch type can either be 'FARGATE' OR 'ECS'. Defaults to Fargate.
> launch_type = FARGATE
> # Assign public ip can either be 'ENABLED' or 'DISABLED'. Defaults to
> 'ENABLED'.
> assign_public_ip = DISABLED
> ### OR POPULATE THIS:
> # This is a function which returns a function. The outer function takes no
> arguments, and returns the inner function.
> # The inner function takes in an airflow CLI command an outputs a json
> compatible with the boto3 run_task API
> # linked above. In other words, if you don't like the way I call the fargate
> API then call it yourself
> execution_config_function =
> airflow.executors.fargate_executor.default_task_id_to_fargate_options_function
> {code}
>
>
>
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