🎉 29 Days of #Airflow 2.9: Day 27

🧩 Today's feature: Logical Operators for dataset conditional logic. Enables complex, precise triggers to start workflows based on dataset states, ensuring execution only under specific conditions. #29daysofairflow29

🔗 bit.ly/4bPhHeB

Bridge the gap between #GenAI 's potential and real business value.

The secret? Effective #dataorchestration with #Airflow .

Learn its critical role in deploying #GenerativeAI at scale, with real-world use cases and steps to get started.

Read the blog ⬇️ bit.ly/3VjGzoH

🎉 29 Days of #Airflow 2.9: Day 27

🕒 New feature: DatasetOrTimeSchedule. Trigger #DAGs based on dataset updates or at scheduled time intervals, offering flexibility for both time-sensitive and data-driven workflows.

🔗 bit.ly/3Kl2w0y

#29daysofairflow29

🎉 29 Days of #Airflow 2.9: Day 26

🌐 New: queuedEvent endpoint for managing DatasetDagRunQueue. Retrieve or delete entries to enhance control, streamline dataset-triggered #DAG runs, and optimize queue management.

🔗 Explore: bit.ly/3WORd8e

#29daysofairflow29

Dive into Snowflake's #DataCloudDevDay with us! ❄️ Join Astronomer in San Francisco on June 6th to level-up your #AIdata skills, see how to build 🏗️ end-to-end #MLPipelines with #Snowflake and #ApacheAirflow , mingle with fellow builders, and more! bit.ly/4ao3yU5

🎉 29 Days of #Airflow 2.9: Day 26

🔀 New feature: Conditional logic for dataset-triggered #DAG runs. Define conditions to control task execution and optimize resource use by activating tasks only as needed.

🔗 Learn how: bit.ly/3KdXFy7

#29daysofairflow29

🎉 29 Days of Airflow 2.9: Day 25

🔍 New Feature: Datasets are now #hashable ! This update lets you use datasets as keys in #Python dictionaries and sets, greatly enhancing workflow efficiency and data management in #Airflow .

🔗 bit.ly/3K8QGGy

#29daysofairflow29

Join our May 29th webinar with #AI / #ML experts from Amazon Web Services and Astronomer as they dive into real-world applications powered by #Airflow . Discover insights on #ConversationalAI , Code Generation, AI Model Deployment & operational #LLMs .

💻 Register now👇 bit.ly/4az2vAC

🎉 29 Days of Airflow 2.9: Day 24

🔧 Introducing a configuration variable to control DAG processor output to stdout. Toggle this in the #Airflow settings for better logging & output management, keeping consoles clean in production.

🔗 bit.ly/3K8QGGy

#29daysofairflow29

Tune in on May 30th as resident #AI / #ML expert from Astronomer covers best practices around #GenAI #datapipelines for content generation with #Airflow . 💨

Save your virtual seat 👉 bit.ly/4b0MPY4

🎉 29 Days of #Airflow 2.9: Day 23

📈 New: Datasets now appear in the visual #DAG graph in the #Airflow UI. This feature shows how #datasets connect to tasks, enhancing your understanding of data flow and its impact on #workflows .

🔗 bit.ly/458xvqh

#29daysofairflow29

🌁 Visit us at Booth #2126A at Snowflake #DataCloudSummit , San Francisco for Dev Day!

🌐 Explore cutting-edge #AI & #ML tech
💸 Optimize #Snowflake spending
🌀 Try our managed #Airflow solution

📆 Schedule an onsite demo: bit.ly/3V5KvcK

#Snowflake Summit2023

🎉 29 Days of #Airflow 2.9: Day 22

🔄 Today's feature: Mutable display names for #DAGs and tasks. Adapt display names as your workflows evolve, keeping your #Airflow environment intuitive and up-to-date.

🔗 bit.ly/3UQbdV9

#29daysofairflow29

🎉 29 Days of #Airflow 2.9: Day 21

🖥️ Feature: Custom instance names for mapped tasks in the UI. Easily assign and view custom names for each task instance to streamline identification and tracking, particularly in dynamic #workflows . bit.ly/3UQhy2Y

#29daysofairflow29

Join our #webinar tomorrow to explore the fundamentals of using #CI /CD with #Airflow . Discover new features like our quick, easy, and efficient #GitHub integration, and gain expert tip for efficient data pipeline management.💡

RSVP here: bit.ly/4bAHruy

Need to sync tasks across deployments?

🌐 Explore our latest guide on implementing Cross-Deployment Dependencies. Learn how to use #Astro Alerts and #Airflow Datasets to create dynamic, efficient workflows across teams.

Dive in now ➡️ bit.ly/4bjBTVC

#DataOps

🎉 29 Days of #Airflow 2.9: Day 20

🌐 New: a POST endpoint for dataset events, enabling external systems to integrate and communicate with Airflow for real-time data event handling. Crucial for #workflows requiring fast updates.

🔗 bit.ly/4bFwjwn

#29daysofairflow29

🎉 29 Days of Airflow 2.9: Day 19

🛠️ New: Auto-ingest custom airflow.cfg at startup. #Airflow automatically applies settings from custom configs at startup, cutting manual setup, reducing errors, and saving time during upgrades.

🔗 bit.ly/3QSN27t

#29daysofairflow29

Because #Airflow pipelines are defined as #Python code, they can be treated like any other piece of software, allowing you to leverage #CICD to automate key parts of your dev lifecycle. 🪄

Learn best practices for more efficient #datapipelines 👉 bit.ly/44FmCf9

🎉 29 Days of #Airflow 2.9: Day 18

🖥️ New: Task.bash TaskFlow decorator! Easily define #DAGs tasks with Bash in Python's TaskFlow API. Ideal for users skilled in shell scripting but new to #Python .

🔗 bit.ly/4beDNXj
🔗 bit.ly/4bCuzUu

#29daysofairflow29