#kubernetes kubectl

[codeonedigest]

Kubernetes kubectl Tutorial with Examples for Devops Beginners and Students

Hi, a new #video on #kubernetes #kubectl is published on #codeonedigest #youtube channel. Learn #kubernetes #api #kubectlcommands #node #docker #container #cloud #aws #azure #programming #coding with #codeonedigest

@java #java #awscloud @awscloud #aws @AWSCloudIndia #Cloud #CloudComputing @YouTube #youtube #azure #msazure #microsoftazure  #kubectl #kubectlcommands #kubectlinstall #kubectlport-forward #kubectlbasiccommands #kubectlproxy #kubectlconfig #kubectlgetpods #kubectlexeccommand #kubectllogs #kubectlinstalllinux #kubectlapply #kuberneteskubectl #kuberneteskubectltutorial #kuberneteskubectlcommands #kuberneteskubectl #kuberneteskubectlinstall #kuberneteskubectlgithub #kuberneteskubectlconfig #kuberneteskubectllogs #kuberneteskubectlpatch #kuberneteskubectlversion #kubernetes #kubernetestutorial #kubernetestutorialforbeginners #kubernetesinstallation #kubernetesinterviewquestions #kubernetesexplained #kubernetesorchestrationtutorial #kubernetesoperator #kubernetesoverview  #containernetworkinterfaceaws #azure #aws #azurecloud #awscloud #orchestration #kubernetesapi #Kubernetesapiserver #Kubernetesapigateway #Kubernetesapipython #Kubernetesapiauthentication #Kubernetesapiversion #Kubernetesapijavaclient #Kubernetesapiclient

[dgruploads]

AWS EKS | Episode 12 | Minikube and Kubectl | Introduction | Setup | hands-on demo

[sapientsapiens]

Just wrapped up the assignments on the final chapter of the #mlzoomcamp on model deployment in Kubernetes clusters. Got foundational hands-on experience with Tensorflow Serving, gRPC, Protobuf data format, docker compose, kubectl, kind and actual Kubernetes clusters on EKS.

[techdirectarchive]

How to Install Kubectl on Windows 11

Kubernetes is an open-source system for automating containerized application deployment, scaling, and management. You can run commands against Kubernetes clusters using the kubectl command-line tool. kubectl can be used to deploy applications, inspect and manage cluster resources, and inspect logs. You can install Kubectl on various Linux platforms, macOS, and Windows. The choice of your…

[aravikumar48]

PODs in Kubernetes Explained | Tech Arkit

In Kubernetes, a pod is the smallest and simplest unit in the deployment model. It represents a single instance of a running process in a cluster and is the basic building block for deploying and managing containerized applications. A pod encapsulates one or more containers, storage resources, a unique network IP, and configuration options. The primary purpose of using pods is to provide a logical and cohesive unit for application deployment and scaling.

[virtualizationhowto]

Kubectl get context: List Kubernetes cluster connections

Kubectl get context: List Kubernetes cluster connections @vexpert #homelab #vmwarecommunities #KubernetesCommandLineGuide #UnderstandingKubectl #ManagingKubernetesResources #KubectlContextManagement #WorkingWithMultipleKubernetesClusters #k8sforbeginners

kubectl, a command line tool, facilitates direct interaction with the Kubernetes API server. Its versatility spans various operations, from procuring cluster data with kubectl get context to manipulating resources using an assortment of kubectl commands. Table of contentsComprehending Fundamental Kubectl CommandsWorking with More Than One Kubernetes ClusterNavigating Contexts with kubectl…

[datamattsson]

He'll never learn.

[devsnews]

Minikube is an excellent tool for Kubernetes development because it allows users to run a single-node Kubernetes cluster locally on their laptops, making development and testing much more accessible. With Minikube, developers can quickly spin up and test Kubernetes applications and services in a local environment with the same configuration as their production clusters. This makes it easy to develop, test, and deploy applications on Kubernetes. Additionally, Minikube is simple to set up and provides a straightforward way to develop and maintain Kubernetes applications.

[govindhtech]

What is Argo CD? And When Was Argo CD Established?

What Is Argo CD?

Argo CD is declarative Kubernetes GitOps continuous delivery.

In DevOps, ArgoCD is a Continuous Delivery (CD) technology that has become well-liked for delivering applications to Kubernetes. It is based on the GitOps deployment methodology.

When was Argo CD Established?

Argo CD was created at Intuit and made publicly available following Applatix’s 2018 acquisition by Intuit. The founding developers of Applatix, Hong Wang, Jesse Suen, and Alexander Matyushentsev, made the Argo project open-source in 2017.

Why Argo CD?

Declarative and version-controlled application definitions, configurations, and environments are ideal. Automated, auditable, and easily comprehensible application deployment and lifecycle management are essential.

Getting Started

Quick Start

kubectl create namespace argocd kubectl apply -n argocd -f https://raw.githubusercontent.com/argoproj/argo-cd/stable/manifests/install.yaml

For some features, more user-friendly documentation is offered. Refer to the upgrade guide if you want to upgrade your Argo CD. Those interested in creating third-party connectors can access developer-oriented resources.

How it works

Argo CD defines the intended application state by employing Git repositories as the source of truth, in accordance with the GitOps pattern. There are various approaches to specify Kubernetes manifests:

Applications for Customization

Helm charts

JSONNET files

Simple YAML/JSON manifest directory

Any custom configuration management tool that is set up as a plugin

The deployment of the intended application states in the designated target settings is automated by Argo CD. Deployments of applications can monitor changes to branches, tags, or pinned to a particular manifest version at a Git commit.

Architecture

The implementation of Argo CD is a Kubernetes controller that continually observes active apps and contrasts their present, live state with the target state (as defined in the Git repository). Out Of Sync is the term used to describe a deployed application whose live state differs from the target state. In addition to reporting and visualizing the differences, Argo CD offers the ability to manually or automatically sync the current state back to the intended goal state. The designated target environments can automatically apply and reflect any changes made to the intended target state in the Git repository.

Components

API Server

The Web UI, CLI, and CI/CD systems use the API, which is exposed by the gRPC/REST server. Its duties include the following:

Status reporting and application management

Launching application functions (such as rollback, sync, and user-defined actions)

Cluster credential management and repository (k8s secrets)

RBAC enforcement

Authentication, and auth delegation to outside identity providers

Git webhook event listener/forwarder

Repository Server

An internal service called the repository server keeps a local cache of the Git repository containing the application manifests. When given the following inputs, it is in charge of creating and returning the Kubernetes manifests:

URL of the repository

Revision (tag, branch, commit)

Path of the application

Template-specific configurations: helm values.yaml, parameters

A Kubernetes controller known as the application controller keeps an eye on all active apps and contrasts their actual, live state with the intended target state as defined in the repository. When it identifies an Out Of Sync application state, it may take remedial action. It is in charge of calling any user-specified hooks for lifecycle events (Sync, PostSync, and PreSync).

Features

Applications are automatically deployed to designated target environments.

Multiple configuration management/templating tools (Kustomize, Helm, Jsonnet, and plain-YAML) are supported.

Capacity to oversee and implement across several clusters

Integration of SSO (OIDC, OAuth2, LDAP, SAML 2.0, Microsoft, LinkedIn, GitHub, GitLab)

RBAC and multi-tenancy authorization policies

Rollback/Roll-anywhere to any Git repository-committed application configuration

Analysis of the application resources’ health state

Automated visualization and detection of configuration drift

Applications can be synced manually or automatically to their desired state.

Web user interface that shows program activity in real time

CLI for CI integration and automation

Integration of webhooks (GitHub, BitBucket, GitLab)

Tokens of access for automation

Hooks for PreSync, Sync, and PostSync to facilitate intricate application rollouts (such as canary and blue/green upgrades)

Application event and API call audit trails

Prometheus measurements

To override helm parameters in Git, use parameter overrides.

Read more on Govindhtech.com

[hawkstack]

Kubernetes - Prometheus & Grafana

Introduction

Kubernetes is a powerful orchestration tool for containerized applications, but monitoring its health and performance is crucial for maintaining reliability. This is where Prometheus and Grafana come into play. Prometheus is a robust monitoring system that collects and stores time-series data, while Grafana provides rich visualization capabilities, making it easier to analyze metrics and spot issues.

In this post, we will explore how Prometheus and Grafana work together to monitor Kubernetes clusters, ensuring optimal performance and stability.

Why Use Prometheus and Grafana for Kubernetes Monitoring?

1. Prometheus - The Monitoring Powerhouse

Prometheus is widely used in Kubernetes environments due to its powerful features:

Time-series database: Efficiently stores metrics in a multi-dimensional format.

Kubernetes-native integration: Seamless discovery of pods, nodes, and services.

Powerful querying with PromQL: Enables complex queries to extract meaningful insights.

Alerting system: Supports rule-based alerts via Alertmanager.

2. Grafana - The Visualization Layer

Grafana transforms raw metrics from Prometheus into insightful dashboards:

Customizable dashboards: Tailor views to highlight key performance indicators.

Multi-source support: Can integrate data from multiple sources alongside Prometheus.

Alerting & notifications: Get notified about critical issues via various channels.

Setting Up Prometheus & Grafana in Kubernetes

1. Deploy Prometheus

Using Helm, you can install Prometheus in your Kubernetes cluster:

helm repo add prometheus-community https://prometheus-community.github.io/helm-charts

helm repo update

helm install prometheus prometheus-community/kube-prometheus-stack

This will install Prometheus, Alertmanager, and related components.

2. Deploy Grafana

Grafana is included in the kube-prometheus-stack Helm chart, but if you want to install it separately:

helm install grafana grafana/grafana

After installation, retrieve the admin password and access Grafana:

kubectl get secret --namespace default grafana -o jsonpath="{.data.admin-password}" | base64 --decode

kubectl port-forward svc/grafana 3000:80

Access Grafana at http://localhost:3000 using the retrieved credentials.

3. Configure Prometheus as a Data Source

In Grafana:

Go to Configuration > Data Sources

Select Prometheus

Enter the Prometheus service URL (e.g., http://prometheus-server.default.svc.cluster.local:9090)

Click Save & Test

4. Import Kubernetes Dashboards

Grafana provides ready-made dashboards for Kubernetes. You can import dashboards by using community templates available on Grafana Dashboards.

Key Metrics to Monitor in Kubernetes

Some essential Kubernetes metrics to track using Prometheus and Grafana include:

Node Health: CPU, memory, disk usage

Pod & Container Performance: CPU and memory usage per pod

Kubernetes API Server Health: Request latency, error rates

Networking Metrics: Traffic in/out per pod, DNS resolution times

Custom Application Metrics: Business logic performance, request rates

Setting Up Alerts

Using Prometheus Alertmanager, you can configure alerts for critical conditions:

- alert: HighCPUUsage expr: avg(rate(container_cpu_usage_seconds_total[5m])) by (pod) > 0.8 for: 5m labels: severity: critical annotations: summary: "High CPU usage detected"Alerts can be sent via email, Slack, PagerDuty, and other integrations.

Conclusion Prometheus and Grafana provide a comprehensive monitoring and visualization solution for Kubernetes clusters. With the right setup, you can gain deep insights into your cluster’s performance, detect anomalies, and ensure high availability.

By integrating Prometheus' powerful data collection with Grafana’s intuitive dashboards, teams can efficiently manage and troubleshoot Kubernetes environments. Start monitoring today and take your Kubernetes operations to the next level!

For more details www.hawkstack.com

[fromdevcom]

Introduction Too much monitoring and alert fatigue is a serious issue for today's engineering teams. Nowadays, there are several open-source and third-party solutions available to help you sort through the noise. It always seems too good to be true, and it probably is. However, as Kubernetes deployments have grown in complexity and size, performance optimization and observability have become critical to guaranteeing optimal resource usage and early issue identification. Kubernetes events give unique and unambiguous information about cluster health and performance. And in these days of too much data, they also give clear insight with minimal noise. In this article, we will learn about Kubernetes events and their importance, their types, and how to access them. What is a Kubernetes Event? A Kubernetes event is an object that displays what is going on inside a cluster, node, pod, or container. These items are typically created in reaction to changes that occur inside your K8s system. The Kubernetes API Server allows all key components to generate these events. In general, each event includes a log message. However, they are quite different and have no other effect on one another. Importance of Kubernetes Events When any of the resources that Kubernetes manages changes, it broadcasts an event. These events frequently provide crucial metadata about the object that caused them, such as the event category (Normal, Warning, Error), as well as the reason. This data is often saved in etcd and made available by running specific kubectl commands. These events help us understand what happened behind the scenes when an entity entered a given state. You may also obtain an aggregated list of all events by running kubectl get events. Events are produced by every part of a cluster, therefore as your Kubernetes environment grows, so will the amount of events your system produces. Furthermore, every change in your system generates events, and even healthy and normal operations require changes in a perfectly running system. This means that a big proportion of the events created by your clusters are purely informative and may not be relevant when debugging an issue. Monitoring Kubernetes Events Monitoring Kubernetes events can help you identify issues with pod scheduling, resource limits, access to external volumes, and other elements of your Kubernetes setup. Events give rich contextual hints that will assist you in troubleshooting these issues and ensuring system health, allowing you to keep your Kubernetes-based apps and infrastructure stable, reliable, and efficient. How to Identify Which Kubernetes Events are Important Naturally, there are a variety of events that may be relevant to your Kubernetes setup, and various issues may arise when Kubernetes or your cloud platform executes basic functions. Let's get into each main event. Failed Events The kube-scheduler in Kubernetes schedules pods, which contain containers that operate your application on available nodes. The kubelet monitors the node's resource use and guarantees that containers execute as intended. The building of the underlying container fails when the kube-scheduler fails to schedule a pod, causing the kubelet to generate a warning event. Eviction Events Eviction events are another crucial event to keep track of since they indicate when a node removes running pods. The most typical reason for an eviction event is a node's insufficient incompressible resources, such as RAM or storage. The kubelet generates resource-exhaustion eviction events on the affected node. In case Kubernetes determines that a pod is utilizing more incompressible resources than what its runtime permits, it can remove the pod from its node and arrange for a new time slot. Volume Events A directory holding data (like an external library) that a pod may access and expose to its containers so they can carry out their workloads with any necessary dependencies is known as a Kubernetes volume.

Separating this linked data from the pod offers a failsafe way for retaining information if the pod breaks, as well as facilitating data exchange amongst containers on the same pod. When Kubernetes assigns a volume to a new pod, it first detaches it from the node it is presently on, attaches it to the required node, and then mounts it onto a pod. Unready Node Events Node readiness is one of the requirements that the node's kubelet consistently returns as true or false. The kubelet creates unready node events when a node transitions from ready to not ready, indicating that it is not ready for pod scheduling.  How to Access Kubernetes Events Metrics, logs, and events may be exported from Kubernetes for observability. With a variety of methods at your fingertips, events may be a valuable source of information about what's going on in your services. Kubernetes does not have built-in functionality for accessing, storing, or forwarding long-term events. It stores it for a brief period of time before cleaning it up. However, Kubernetes event logs may be retrieved directly from the cluster using Kubectl and collected or monitored using a logging tool. Running the kubectl describe command on a given cluster resource will provide a list of its events. A more general approach is to use the kubectl get events command, which lists the events of specified resources or the whole cluster. Many free and commercial third-party solutions assist in providing visibility and reporting Kubernetes cluster events. Let's look at some free, open-source tools and how they may be used to monitor your Kubernetes installation: KubeWatch KubeWatch is an excellent open-source solution for monitoring and broadcasting K8s events to third-party applications and webhooks. You may set it up to deliver notifications to Slack channels when major status changes occur. You may also use it to transmit events to analytics and alerting systems such as Prometheus. Events Exporter The Kubernetes Events Exporter is a good alternative to K8s' native observing mechanisms. It allows you to constantly monitor K8s events and list them as needed. It also extracts a number of metrics from the data it collects, such as event counts and unique event counts, and offers a simple monitoring configuration. EventRouter EventRouter is another excellent open-source solution for gathering Kubernetes events. It is simple to build up and seeks to stream Kubernetes events to numerous sources, as described in its documentation. However, like KubeWatch, it does not have querying or persistent capabilities. To get the full experience, you should link it to a third-party storage and analysis tool. Conclusion Kubernetes events provide an excellent approach to monitor and improve the performance of your K8s clusters. They become more effective when combined with realistic tactics and vast toolsets. I hope this article helps you to understand the importance of Kubernetes events and how to get the most out of them.

[codeonedigest]

Kubernetes API Tutorial with Examples for Devops Beginners and Students

Hi, a new #video on #kubernetesapi is published on #codeonedigest #youtube channel. Learn #kubernetes #api #kubectl  #node #docker #container #cloud #aws #azure #programming #coding with #codeonedigest

@java #java #awscloud @awscloud #aws @AWSCloudIndia #Cloud #CloudComputing @YouTube #youtube #azure #msazure #microsoftazure  #kubernetes #kubernetestutorial #kubernetestutorialforbeginners #kubernetesinstallation #kubernetesinterviewquestions #kubernetesexplained #kubernetesorchestrationtutorial #kubernetesoperator #kubernetesoverview #kubernetesnetworkpolicy #kubernetesnetworkpolicyexplained #kubernetesnetworkpolicytutorial #kubernetesnetworkpolicyexample #containernetworkinterface #containernetworkinterfaceKubernetes #containernetworkinterfaceplugin #containernetworkinterfaceazure #containernetworkinterfaceaws #azure #aws #azurecloud #awscloud #orchestration #kubernetesapi #Kubernetesapiserver #Kubernetesapigateway #Kubernetesapipython #Kubernetesapiauthentication #Kubernetesapiversion #Kubernetesapijavaclient #Kubernetesapiclient

[dockerdummy]

Cheat Sheet: How to install Kubernetes via kubadm on Ubuntu 24.04 (and trying to join it as an additional master to an existing cluster)

ChatGPT helped in this task, but some commands did not work immediately, so I had to ask ChatCPT how to fix the errors I encountered. The command presented here leads through the process of installing Kubernetes using kubeadm on a fresh Ubuntu 24.04 system without any errors (as long as the world does not change too much). Step 1: Install kubeadm, kubelet and kubectl MAJOR_VERSION=1.26 # Add GPG…

[qcsdslabs]

Networking in OpenShift Virtualization: A Deep Dive

OpenShift Virtualization is a powerful extension of Red Hat OpenShift that enables you to run and manage virtual machines (VMs) alongside containerized workloads. Networking plays a crucial role in OpenShift Virtualization, ensuring seamless communication between VMs, containers, and external systems. In this blog, we will explore the core components and configurations that make networking in OpenShift Virtualization robust and flexible.

Key Networking Components

Multus CNI (Container Network Interface):

OpenShift Virtualization leverages Multus CNI to enable multiple network interfaces per pod or VM.

This allows VMs to connect to different networks, such as internal pod networks and external VLANs.

KubeVirt:

Acts as the core virtualization engine, providing networking capabilities for VMs.

Integrates with OpenShift’s SDN (Software-Defined Networking) to offer seamless communication.

OVN-Kubernetes:

The default SDN in OpenShift that provides Layer 2 and Layer 3 networking.

Ensures high performance and scalability for both VMs and containers.

Networking Models in OpenShift Virtualization

OpenShift Virtualization offers several networking models tailored to different use cases:

Pod Networking:

VMs use the same network as Kubernetes pods.

Simplifies communication between VMs and containerized workloads.

For example, a VM hosting a database can easily connect to application pods within the same namespace.

Bridge Networking:

Provides direct access to the host network.

Ideal for workloads requiring low latency or specialized networking protocols.

SR-IOV (Single Root I/O Virtualization):

Enables direct access to physical NICs (Network Interface Cards) for high-performance applications.

Suitable for workloads like real-time analytics or financial applications that demand low latency and high throughput.

MACVLAN Networking:

Assigns a unique MAC address to each VM for direct communication with external networks.

Simplifies integration with legacy systems.

Network Configuration Workflow

Define Network Attachments:

Create additional network attachments to connect VMs to different networks.

Attach Networks to VMs:

Add network interfaces to VMs to enable multi-network communication.

Configure Network Policies:

Set up rules to control traffic flow between VMs, pods, and external systems.

Best Practices

Plan Your Network Topology:

Understand your workload requirements and choose the appropriate networking model.

Use SR-IOV for high-performance workloads and Pod Networking for general-purpose workloads.

Secure Your Networks:

Implement Network Policies to restrict traffic based on namespaces, labels, or CIDR blocks.

Enable encryption for sensitive communications.

Monitor and Troubleshoot:

Use tools like OpenShift Console and kubectl for monitoring and debugging.

Analyze logs and metrics to ensure optimal performance.

Leverage Automation:

Automate network configuration and deployments using infrastructure-as-code tools.

Conclusion

Networking in OpenShift Virtualization is a sophisticated and flexible system that ensures seamless integration of VMs and containers. By leveraging its diverse networking models and following best practices, you can build a robust and secure environment for your workloads. Whether you are modernizing legacy applications or scaling cloud-native workloads, OpenShift Virtualization has the tools to meet your networking needs.

For more information visit: https://www.hawkstack.com/

[qcs01]

Getting Started with Kubernetes: A Hands-on Guide

Getting Started with Kubernetes: A Hands-on Guide

Kubernetes: A Brief Overview

Kubernetes, often abbreviated as K8s, is a powerful open-source platform designed to automate the deployment, scaling, and management of containerized applications. It1 simplifies the complexities of container orchestration, allowing developers to focus on building and deploying applications without worrying about the underlying infrastructure.2

Key Kubernetes Concepts

Cluster: A group of machines (nodes) working together to run containerized applications.

Node: A physical or virtual machine that runs containerized applications.

Pod: The smallest deployable3 unit of computing, consisting of one or more containers.

Container: A standardized unit of software that packages code and its dependencies.

Setting Up a Kubernetes Environment

To start your Kubernetes journey, you can set up a local development environment using minikube. Minikube creates a single-node Kubernetes cluster on your local machine.

Install minikube: Follow the instructions for your operating system on the minikube website.

Start the minikube cluster: Bashminikube start

Configure kubectl: Bashminikube config --default-context

Interacting with Kubernetes: Using kubectl

kubectl is the command-line tool used to interact with Kubernetes clusters. Here are some basic commands:

Get information about nodes: Bashkubectl get nodes

Get information about pods: Bashkubectl get pods

Create a deployment: Bashkubectl create deployment my-deployment --image=nginx

Expose a service: Bashkubectl expose deployment my-deployment --type=NodePort

Your First Kubernetes Application

Create a simple Dockerfile: DockerfileFROM nginx:alpine COPY index.html /usr/share/nginx/html/

Build the Docker image: Bashdocker build -t my-nginx .

Push the image to a registry (e.g., Docker Hub): Bashdocker push your-username/my-nginx

Create a Kubernetes Deployment: Bashkubectl create deployment my-nginx --image=your-username/my-nginx

Expose the deployment as a service: Bashkubectl expose deployment my-nginx --type=NodePort

Access the application: Use the NodePort exposed by the service to access the application in your browser.

Conclusion

Kubernetes offers a powerful and flexible platform for managing containerized applications. By understanding the core concepts and mastering the kubectl tool, you can efficiently deploy, scale, and manage your applications.

Keywords: Kubernetes, container orchestration, minikube, kubectl, deployment, scaling, pods, services, Docker, Dockerfile

[sandeep2363]

Chapter 2: Setting Up Your Kubernetes Cluster

In this chapter, we’ll cover the step-by-step process to set up Kubernetes using Minikube. You’ll learn how to install and configure Minikube, explore essential kubectl commands, and navigate the Kubernetes Dashboard. Each section includes detailed commands, live examples, and insights to simulate production-like environments. 1. Installing and Configuring Minikube Minikube creates a…