AWS Batch Reviews

Apache Airflow Reviews

AWS Batch mentions (14)

• Looking for a decent (self hostable) program to orchestrate scripts, notify on failures, etc

  After moving off Jenkins, I moved everything to AWS Batch with Fargate. This works quite well, but it is proving to be a little expensive, as I have to pay for:. Source: 12 months ago

• Hosting strategy suggestions

  If you're looking for more control over your infrastructure and want to run a full computing environment, EC2 might be the right choice for you. With EC2, you have complete control over the operating system, network, and storage, which can be useful if you need to install custom software or use specific hardware configurations. Additionally, EC2 + Batch processing provide a wider range of instance types, including... Source: about 1 year ago

• Questions for bioinformatics researchers that use AWS

  AWS Batch is the equivalent of a university cluster you submit to with slurm/sge/lsf/etc. But does not use those schedulers as AWS has their own. Source: over 1 year ago

• Scheduling "Fetch & Run" Batch Jobs with AWS Batch and CloudWatch Rules

  Developers frequently use batch computing to access significant amounts of processing power. You may perform batch computing workloads in the AWS Cloud with the aid of AWS Batch, a fully managed service provided by AWS. It is a powerful solution that can plan, schedule, and execute containerized batch or machine learning workloads across the entire spectrum of AWS compute capabilities, including Amazon ECS, Amazon... - Source: dev.to / over 1 year ago

• can you run OS applications in lambda layers?

  As others mentioned, you *can*. It might be easier with AWS Batch (https://aws.amazon.com/batch/) depending on what you're trying to do. Source: over 1 year 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 / 10 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 / 8 months ago