Tags: kubernetes*

Kubernetes, often referred to as K8s, is an open-source platform for automating the deployment, scaling, and management of containerized applications. It is widely used by developers and organizations for creating and managing containerized applications across a cluster of machines.

Kubernetes provides various tools and functionalities to orchestrate containers, such as managing container deployments, scaling applications, managing network access, and more. It is built on top of Linux containers and operates based on a set of declarative configuration files. These files describe the desired state of the application and Kubernetes ensures that the actual state matches the desired state.

Kubernetes has become popular due to its scalability, portability, and flexibility. It simplifies the complexities of managing distributed applications by providing a unified control plane for multiple containerized applications. Furthermore, Kubernetes has a large ecosystem of tools, plugins, and services that extend its functionalities, making it a powerful platform for modern software development and deployment.

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  1. This article explains why CPU limits are considered harmful on Kubernetes. The author provides three analogies about Kubernetes CPU Limits and discusses the best practices for CPU limits and requests on Kubernetes.
  2. Flux is a set of continuous and progressive delivery solutions for Kubernetes that are open and extensible. The latest version brings many new features, making it more flexible and versatile.
  3. The author explains their decision to build a home lab using Raspberry Pis, Kubernetes, and 3D printing, providing reasons such as gaining exposure, experimenting with complex architectures, becoming a T-shaped engineer, and the cost-effectiveness of DIY projects.
  4. This guide provides an introduction to kubectl, the command-line tool used to communicate with the Kubernetes API. It covers command syntax, useful commands, flags, and tips and tricks. It also discusses the ecosystem of plugins and tools built to expand the functionalities of kubectl and Kubernetes.
  5. Eric Larssen discusses the shortcomings of Terraform in infrastructure as code management, such as bespoke patterns, drift management issues, HCL language complexity, and licensing drama, and suggests the Kubernetes operator pattern as an alternative.
  6. In this article, we explore how to deploy and manage machine learning models using Google Kubernetes Engine (GKE), Google AI Platform, and TensorFlow Serving. We will cover the steps to create a machine learning model and deploy it on a Kubernetes cluster for inference.
  7. • Continuous Integration (CI) and Continuous Deployment (CD) pipelines for Machine Learning (ML) applications
    • Importance of CI/CD in ML lifecycle
    • Designing CI/CD pipelines for ML models
    • Automating model training, deployment, and monitoring
    • Overview of tools and platforms used for CI/CD in ML

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