Apache Airflow Helm Chart 1.22.0 - Image and Version Bumps

   |   4 minute read

Apache Airflow Helm Chart 1.22.0 was released on June 13, 2026. This version bumps the default Airflow image to 3.2.2 and sets a new minimum requirement for the Helm binary itself.

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Apache Airflow Ctl 0.1.5 - CLI, Dag Run, and API Updates

   |   4 minute read

Apache Airflow Ctl airflow-ctl/0.1.5 was published on June 3, 2026. This release gives airflowctl users more direct Dag and Dag Run operations, cleaner generated command arguments, and fixes a few rough edges that matter when the tool is used in scripts.

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Apache Airflow 3.2.2: SMTP Validation, Triggerer Watchdog, and Prefix Search

   |   4 minute read

Apache Airflow 3.2.2 was published on May 29 2026 with a mix of security tightening, a triggerer reliability fix, and a UI search behavior change that operators of large deployments should know about.

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Apache Airflow this week, multi team triggerer and dags clear CLI

   |   4 minute read

Apache Airflow shipped 143 commits to main in the last seven days, touching 1,210 files across 46,490 insertions and 11,241 deletions. The headline change is multi team triggerer support landing as a schema migration on the trigger table, plus a new airflow dags clear CLI for partition range reprocessing. This post walks the activity that actually matters for operators and DAG authors who follow apache/airflow.

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Data Preparation and Pipeline Orchestration: Step Functions, Airflow, and Glue Workflows

   |   9 minute read

Previous: Data Transformation

Book: AWS Certified Data Engineer Associate Study Guide Authors: Sakti Mishra, Dylan Qu, Anusha Challa Publisher: O’Reilly Media ISBN: 978-1-098-17007-3

Final part of Chapter 4. We move from raw transformation into two topics: data preparation for people who don’t write code, and orchestrating the whole pipeline end to end. Both matter for the exam. Both matter in real life.

Data Preparation for Nontechnical Personas

AWS Glue DataBrew is a low-code, visual tool for data cleaning and preparation. It targets data analysts, data scientists, and business users who need to work with data but don’t want to write PySpark or SQL.

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