Google Kubernetes Engine Reviews

Luigi Reviews

Google Kubernetes Engine mentions (43)

• Using Cloud Monitoring to Monitor IRIS-Based Applications Deployed in GKE

  In this article, we’ll look at one of the ways to monitor the InterSystems IRIS data platform (IRIS) deployed in the Google Kubernetes Engine (GKE). The GKE integrates easily with Cloud Monitoring, simplifying our task. As a bonus, the article shows how to display metrics from Cloud Monitoring in Grafana. - Source: dev.to / 13 days ago

• Using NetBird for Kubernetes Access

  Set up a remote Kubernetes cluster. For this tutorial, Google Kubernetes Engine (GKE) was chosen; however, feel free to use any remote Kubernetes cluster. - Source: dev.to / about 1 month ago

• The 2024 Web Hosting Report

  Docker swarm still exists, it still works, and some of these other container orchestrators are still hanging on, but for the most part, you’re using Kubernetes if you’re doing this stuff at work. Generally it's well-understood that kubernetes is hard to get right, and so most people use it via a managed provider like Elastic Kubernetes Service from AWS, Azure Kubernetes Service from MSFT, or Google Kubernetes... - Source: dev.to / 4 months ago

• 15 Options To Build A Kubernetes Playground (with Pros and Cons)

  Google Kubernetes Engine (GKE) Google Kubernetes Engine (GKE) is a managed Kubernetes service on the Google Cloud Platform (GCP). It offers a fully managed, scalable, and secure environment for running containerized applications with Kubernetes. GKE provides seamless integration with other GCP services like Google Cloud Storage, Stackdriver Logging, and Cloud IAM, making it easy to build and deploy applications on... - Source: dev.to / 4 months ago

• Creating Kubernetes Operators with operator-sdk

  Kubernetes is a project created by Google in mid-2015 that quickly became the standard for managing container execution. You can host it on your machines or use a solution delivered by one of the big cloud players like AWS, Google, and DigitalOcean. - Source: dev.to / 9 months ago

Luigi mentions (9)

• Ask HN: What is the correct way to deal with pipelines?

  I agree there are many options in this space. Two others to consider: - https://airflow.apache.org/ - https://github.com/spotify/luigi There are also many Kubernetes based options out there. For the specific use case you specified, you might even consider a plain old Makefile and incrond if you expect these all to run on a single host and be triggered by a new file... - Source: Hacker News / 9 months ago

• In the context of Python what is a Bob Job?

  Maybe if your use case is “smallish” and doesn’t require the whole studio suite you could check out apscheduler for doing python “tasks” on a schedule and luigi to build pipelines. Source: almost 2 years ago

• Lessons Learned from Running Apache Airflow at Scale

  What are you trying to do? Distributed scheduler with a single instance? No database? Are you sure you don't just mean "a scheduler" ala Luigi? https://github.com/spotify/luigi. - Source: Hacker News / about 2 years ago

• Apache Airflow. How to make the complex workflow as an easy job

  It's good to know what Airflow is not the only one on the market. There are Dagster and Spotify Luigi and others. But they have different pros and cons, be sure that you did a good investigation on the market to choose the best suitable tool for your tasks. - Source: dev.to / over 2 years ago

• DevOps Fundamentals for Deep Learning Engineers

  MLOps is a HUGE area to explore, and not surprisingly, there are many startups showing up in this space. If you want to get it on the latest trends, then I would look at workflow orchestration frameworks such as Metaflow (started off at Netflix, is now spinning off into its own enterprise business, https://metaflow.org/), Kubeflow (used at Google, https://www.kubeflow.org/), Airflow (used at Airbnb,... Source: over 2 years ago