delayed_job Reviews

Apache Airflow Reviews

delayed_job mentions (6)

• It’s Time For Active Job

  It is hard to imagine any big and complex Rails project without background jobs processing. There are many gems for this task: **Delayed Job, Sidekiq, Resque, SuckerPunch** and more. And Active Job has arrived here to rule them all. - Source: dev.to / 7 days ago

• DelayedJob and PG Error No Connection to Server

  Obviously, that is not what I’ve expected from Delayed::Job workers. So I took the shovel and started digging into git history. Since the last release the only significant modification has been made in the internationalization. We’ve moved to I18n-active_record backend to grant the privilege to modify translations not only to developers but also to highly-educated mere mortals. - Source: dev.to / 7 days ago

• How to run a really long task from a Rails web request

  So how do we trigger such a long-running process from a Rails request? The first option that comes to mind is a background job run by some of the queuing back-ends such as Sidekiq, Resque or DelayedJob, possibly governed by ActiveJob. While this would surely work, the problem with all these solutions is that they usually have a limited number of workers available on the server and we didn’t want to potentially... - Source: dev.to / about 2 years ago

• Delayed Job vs. Sidekiq: Which Is Better?

  Several gems support job queues and background processing in the Rails world — Delayed Job and Sidekiq being the two most popular ones. - Source: dev.to / over 2 years ago

• Why does rails have a tradition of queuing background jobs in a separate NoSQL store, when both the queueing controller and the job class tend to hammer the main database anyway?

  Back in the day, before Sidekiq and such, we used Delayed Job https://github.com/collectiveidea/delayed_job. Source: over 2 years ago

Apache Airflow mentions (67)

• 10 Open Source Tools for Building MLOps Pipelines

  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 / 8 days ago

• AI Strategy Guide: How to Scale AI Across Your Business

  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 1 month ago

• The 2024 Web Hosting Report

  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

• Best ETL Tools And Why To Choose

  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: 7 months ago

• Simplifying Data Transformation in Redshift: An Approach with DBT and Airflow

  Airflow is the most widely used and well-known tool for orchestrating data workflows. It allows for efficient pipeline construction, scheduling, and monitoring. - Source: dev.to / 7 months ago