Based on our record, Apache Airflow should be more popular than Drupal. It has been mentiond 68 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I would be interested in some good migration tools, paid ones are also ok. I found a post about this on drupal.org, but it didn't seem like an easy process. It is a multilanguage site with many content types, and a totally custom theme. Source: over 1 year ago
You got already good advice, but wanted to point the guide of drupal.org where you can see some tools listed with instructions and channels https://www.drupal.org/community/contributor-guide/reference-information/talk/tools. Source: over 1 year ago
There is a service call GitPod that provides a temporary container Drupal environment. If you are familiar with what is going on around the future of how Drupal modules will eventually be offered up, you will likely have seen the "Project Browser" module as a contrib demo of the approach. It is used for people to give feedback to the developers. So they set up the typical 'SimplyTestMe' but also a GitPod... Source: almost 2 years ago
For reviews, it depends entirely on what you mean by "review". I believe core has a simple comment module, although it may have been deprecated for D9? There are likely many review-style modules on drupal.org that might work, or if you just want to link out to third-party reviews then it could just be a repeating-value link field on the Product content type. Source: almost 2 years ago
They should also use standards tools like Github. The drupal.org platform was certainly impressive 10 years ago, today it's a pain to use it. They ducktape it with gitlab, but really it sucks to have to read documentation to simply do a pull request. Source: almost 2 years ago
Instead of the custom orchestrator I used, a proper orchestration tool should replace it like Apache Airflow, Dagster, ..., etc. - Source: dev.to / 9 days ago
An integral part of an ML project is data acquisition and data transformation into the required format. This involves creating ETL (extract, transform, load) pipelines and running them periodically. Airflow is an open source platform that helps engineers create and manage complex data pipelines. Furthermore, the support for Python programming language makes it easy for ML teams to adopt Airflow. - Source: dev.to / 20 days ago
Level 1 of MLOps is when you've put each lifecycle stage and their intefaces in an automated pipeline. The pipeline could be a python or bash script, or it could be a directed acyclic graph run by some orchestration framework like Airflow, dagster or one of the cloud-provider offerings. AI- or data-specific platforms like MLflow, ClearML and dvc also feature pipeline capabilities. - Source: dev.to / about 2 months ago
For the third, examples here might be analytics plugins in specialized databases like Clickhouse, data-transformations in places like your ETL pipeline using Airflow or Fivetran, or special integrations in your authentication workflow with Auth0 hooks and rules. - Source: dev.to / 4 months ago
Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows. The platform features a web-based user interface and a command-line interface for managing and triggering workflows. Source: 8 months ago
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