Found this incredibly helpful, went ahead and created some timecodes b/c I can see myself referencing this video 0:40 - Intro 5:00 - Context (Container, Images, Why?) 15:10 - Status (History, Current Status) 21:00 - Internals (Dockerhub, Building, Testing) 35:54 - Usage (Extending Image, Custom a.k.a build from source) 43:40 - Future State 45:24 - Q&A
tremendous presentation, I am starting with airflow in containers and in fact in the organization we seek to make it more productive, this helps me to have another perspective, TYVM!
Hello, I have an airflow running on my machine with Postgresql on the scheduler's backend and LocalExecutor, but when I put my dags to run it consumes a lot of server CPU, how could I solve this high consumption problem?
Found this incredibly helpful, went ahead and created some timecodes b/c I can see myself referencing this video
0:40 - Intro
5:00 - Context (Container, Images, Why?)
15:10 - Status (History, Current Status)
21:00 - Internals (Dockerhub, Building, Testing)
35:54 - Usage (Extending Image, Custom a.k.a build from source)
43:40 - Future State
45:24 - Q&A
Thanks for the timeline hint! It's really helpful :)
tremendous presentation, I am starting with airflow in containers and in fact in the organization we seek to make it more productive, this helps me to have another perspective, TYVM!
very helpful . thanks.
Great content, thank you!
Really interesting
Hello, I have an airflow running on my machine with Postgresql on the scheduler's backend and LocalExecutor, but when I put my dags to run it consumes a lot of server CPU, how could I solve this high consumption problem?
This seems to be the compile run of the DAGs, when these are compiled. This is a one time run. So just wait. You can't avoid thos
whats the difference between AirFlow and DolphinScheduler.. Does Airflow have a visual designer for DAG's ? That's a great value