You can trigger the pipeline manually or using an external trigger (e.g. This has to do with the lack of versioning for Airflow pipelines.Īirflow is best at handling workflows that run at a specified time or every specified time interval. In this context, slow change means that once the pipeline is deployed, it is expected to change from time to time (once every several days or weeks, not hours or minutes). However, it is most suitable for pipelines that change slowly, are related to a specific time interval, or are pre-scheduled. Airflow can run ad hoc workloads not related to any interval or schedule. This is part of our series of articles about machine learning operations.Īpache Airflow's versatility allows you to set up any type of workflow. Graphical UI-monitor and manage workflows, check the status of ongoing and completed tasks.Coding with standard Python-you can create flexible workflows using Python with no knowledge of additional technologies or frameworks.Integrations-ready-to-use operators allow you to integrate Airflow with cloud platforms (Google, AWS, Azure, etc). ![]() Open-source community-Airflow is free and has a large community of active users.Ease of use-you only need a little python knowledge to get started.Airflow can run anything-it is completely agnostic to what you are running. ![]() Airflow uses Python to create workflows that can be easily scheduled and monitored. First developed by Airbnb, it is now under the Apache Software Foundation. Apache Airflow is an open-source platform for authoring, scheduling and monitoring data and computing workflows.
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