Komodor Reviews

Apache Airflow Reviews

Komodor mentions (5)

• If You're Using Helm, Why Not Give It a Pretty UI As Well?

  Helm Dashboard is an open-source project by Komodor that offers a visual and user-friendly way to manage and visualize all the Helm charts installed in your clusters. Instead of using the terminal, you can leverage the Helm Dashboard's intuitive UI to perform a variety of tasks that make working with Helm a breeze. Here are some of its key features:. - Source: dev.to / 9 months ago

• 7 Kubernetes Companies to Watch in 2022

  Speaking of tools that I think I could talk an employer into buying, how about something to help with troubleshooting Kubernetes? Komodor is an observability tool that gives you insight into what’s happening with your clusters and workloads. As distributed applications have become more complex, they’ve become more difficult to troubleshoot, and Komodor gives you an integrated view of your Kubernetes resources. Not... - Source: dev.to / almost 2 years ago

• 4 Trends to Look Out For at KubeCon 2021

  Monitoring changes in the entire Kubernetes stack requires specialized skills particularly in the effective analysis of ripple effects and context-based approach in troubleshooting problems. A K8s-native troubleshooting solution like Komodor ensures that the troubleshooting process is undertaken in an independent and efficient manner. It institutes systematization to address the chaos that is usually present when... - Source: dev.to / over 2 years ago

• k8s based platform

  You can find more info on https://komodor.com or DM me (full disclosure: I work for Komodor at the moment). Source: almost 3 years ago

• Migrating to Kubernetes: 6 Enterprise Tools to Ensure a Smooth Start

  For Troubleshooting: Komodor Komodor is a troubleshooting tool that has been gaining popularity in the Kubernetes dev community. What Komodor offers is the ability to gain a full view of all changes across the entire k8s stack - and their ripple effects - to streamline the usually laborious task of understanding what went wrong, when something goes wrong. - Source: dev.to / almost 3 years ago

Apache Airflow mentions (66)

• 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 / 24 days 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

• Share Your favorite python related software!

  AIRFLOW This is more of a library in my opinion, but Airflow has become an essential tool for scheduling in my work. All our ML training pipelines are ordered and scheduled with Airflow and it works seamlessly. The dashboard provided is also fantastic! Source: 8 months ago