Resque Reviews

Apache Airflow Reviews

Resque mentions (7)

• 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 / 8 days ago

• How to Setup a Project That Can Host Up to 1000 Users for Free

  Rollbar is a great error-tracking service. It alerts us on exceptions and errors, provides analysis tools and dashboard, so we can see, reproduce, and fix bugs quickly when something went wrong. This service has a possibility to log not only uncaught exceptions but any messages. By default, the messages are reported synchronously, but you can enable asynchronous reporting using Sidekiq, girl_friday, or Resque.... - Source: dev.to / 10 days ago

• Add web scraping data into the database at regular intervals [ruby & ror]

  You can use a background job queue like Resque to scrape and process data in the background, and a scheduler like resque-scheduler to schedule jobs to run your scraper periodically. Source: almost 2 years 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

• Building a dynamic staging platform

  Background jobs are another limitation. Since only the Aha! Web service runs in a dynamic staging, the host environment's workers would process any Resque jobs that were sent to the shared Redis instance. If your branch hadn't updated any background-able methods, this would be no big deal. But if you were hoping to test changes to these methods, you would be out of luck. - Source: dev.to / about 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 / 9 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