Apache Mesos Reviews

Luigi Reviews

Apache Mesos mentions (7)

• Upgrading Hundreds of Kubernetes Clusters

  When we adopted Kubernetes at Criteo, we encountered initial hurdles. In 2018, Kubernetes operators were still new, and there was internal competition from Mesos. We addressed these challenges by validating Kubernetes performance for our specific needs and building custom Chef recipes, StatefulSet hooks, and startup scripts. - Source: dev.to / 2 months ago

• The 2024 Web Hosting Report

  In the beginning, there was docker. In 2013, building on linux internals, docker packaged containers for mass adoption and made it easy to share a complete runtime environment for an application across the network. Check out their first demo at PyCon 2013 (I was there!) At the time, serious workloads ran on something like Mesos, which was not “container-native” and had its own way of packaging and distributing... - Source: dev.to / 4 months ago

• World of Containers: Kubernetes vs. Docker

  Distribution of containers to servers, clusters, and data centers Keeping applications up and running with the required number of instances Upgrading applications without downtime These issues are also known as cloud-native characteristics of modern applications. Therefore, a need for container orchestration systems has arisen. There are three leading container orchestrators on the market: Docker Swarm... - Source: dev.to / 10 months ago

• HelenOS a microkernel-based, multiserver OS from scratch

  Https://mesos.apache.org/ >Apache Mesos abstracts CPU, memory, storage, and other compute resources away from machines. - Source: Hacker News / over 1 year ago

• Machine Learning Pipelines with Spark: Introductory Guide (Part 1)

  Spark works locally on stand-alone clusters and on Hadoop YARN, Apache Mesos, Kubernetes, and other managed Hadoop platforms. - Source: dev.to / over 1 year 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