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Mastering Argo Rollouts: Progressive Delivery In Kubernetes

Posted By: ELK1nG
Mastering Argo Rollouts: Progressive Delivery In Kubernetes

Mastering Argo Rollouts: Progressive Delivery In Kubernetes
Published 3/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.55 GB | Duration: 7h 42m

From Basic to Advanced: Achieving Zero-Downtime and Reliable Canary and Blue-Green Deployments Strategy in Kubernetes

What you'll learn

Grasp Argo Rollouts Basics: Understand the core concepts and architecture of Argo Rollouts in Kubernetes.

Deployment Strategies Mastery: Learn to implement blue-green and canary deployments for controlled rollouts.

Rollout Monitoring Skills: Gain expertise in monitoring and managing rollout processes using Argo Rollouts.

Rollback Techniques: Acquire the ability to perform effective rollbacks and handle deployment failures.

Integration with Monitoring Tools: Learn to integrate Argo Rollouts with common monitoring tools for enhanced observability.

Best Practices for Progressive Delivery: Understand key practices for successful progressive delivery in cloud-native environments.

Requirements

Basic Kubernetes Knowledge: Familiarity with Kubernetes concepts such as Pods, Deployments, Services, and YAML configurations is essential.

Understanding of CI/CD Principles: A fundamental grasp of Continuous Integration and Continuous Deployment (CI/CD) processes will be beneficial.

Experience with Containerization: Practical experience with container technologies like Docker, as Argo Rollouts is used within a containerized environment.

Familiarity with Git: Basic knowledge of Git for version control, as code examples and exercises may involve Git operations.

Command Line Proficiency: Comfort with using command line interfaces (CLI), as many Kubernetes and Argo Rollouts tasks are performed via CLI.

Optional - Prior Exposure to Argo Workflows: While not mandatory, having some background in Argo Workflows or similar tools can enhance understanding.

Description

Dive into the world of Kubernetes with "Mastering Argo Rollouts: Progressive Delivery in Kubernetes." This comprehensive course is designed to equip DevOps professionals, Kubernetes enthusiasts, and software engineers with the skills to implement advanced deployment strategies in Kubernetes using Argo Rollouts. Here's a breakdown of what you'll learn, structured in engaging modules with a focus on both practical and theoretical aspects:Introduction to Kubernetes & Argo RolloutsUnderstanding the Kubernetes EcosystemFundamentals of Kubernetes DeploymentsIntroduction to Argo Rollouts and its importance in modern deploymentsDeploying with Argo RolloutsSetting up Argo Rollouts in your Kubernetes ClusterTransitioning from traditional deployments to Argo RolloutsHands-On Exercises: Deploy your first application using Argo RolloutsAdvanced Deployment StrategiesDeep dive into Canary Releases: Gradually rolling out changes to a subset of usersMastering Blue-Green Deployments: Ensuring zero-downtime during updatesPractical Scenarios: Implementing complex deployment strategiesMonitoring and Automated RollbacksIntegrating with monitoring tools like Prometheus and GrafanaSetting up Automated Rollbacks based on real-time metricsCritical Analysis: Understanding deployment metrics for decision-makingReal-World Applications and Best PracticesApplying Argo Rollouts in production environmentsBest Practices: Ensuring high availability and reliabilityCase Studies: Analysis of successful Argo Rollouts implementationsThroughout the course, emphasis is placed on practical implementation and real-world applicability, ensuring that you not only understand the concepts but also can confidently apply them in your Kubernetes environment. Whether you aim to enhance your DevOps capabilities or master progressive delivery techniques, this course is your gateway to excelling in the cloud-native landscape. Join us to become proficient in managing Kubernetes deployments with efficiency and control.

Overview

Section 1: Introduction

Lecture 1 Introduction

Lecture 2 Command Reference Git Repository

Section 2: Argo Rollout Introduction

Lecture 3 Argo Rollout Why and Key Features

Lecture 4 Architecture and Components

Lecture 5 Argo Rollout Concepts

Lecture 6 Argo Rollout Controller Features

Section 3: Argo Rollout Installation

Lecture 7 Argo Rollout System Requirements

Lecture 8 Argo Rollout Installation

Lecture 9 Argo Rollout Specification

Lecture 10 Argo Rollout Simple Demo

Lecture 11 Argo Rollout Dashboard

Section 4: Rollout Strategies

Lecture 12 Canary Strategy Introduction

Lecture 13 Blue Green Strategy Introduction

Section 5: Canary Rollout Strategy

Lecture 14 Argo Rollout Operation Promote

Lecture 15 Argo Rollout Promote Manual

Lecture 16 Argo Rollout Promote Full

Lecture 17 Argo Rollout Abort

Lecture 18 Argo Rollout Rollback

Lecture 19 Argo Rollout Pause and Resume

Section 6: Rollout Analysis

Lecture 20 Analysis Introduction

Lecture 21 Analysis Demo with Mock Metrics

Lecture 22 Analysis Prometheus Positive Condition

Lecture 23 Analysis Prometheus Negative Condition

Lecture 24 Analysis Argument

Section 7: Rollout Demo Application

Lecture 25 Access Rollout Service with Proxy

Lecture 26 Demo Application UI Features

Lecture 27 Demo with Kustomize

Lecture 28 Verify Preview Service

Section 8: Experiments

Lecture 29 Experiment Introduction

Lecture 30 Experiment Success Condition

Lecture 31 Experiment Failure Condition

Lecture 32 Experiment Success Auto Promotion

Lecture 33 Experiment Failure Auto Roll Back

Section 9: Rollout Auto Scaling

Lecture 34 Metrics Server Addon Introduction

Lecture 35 Horizontal Pod Auto Scaling Demo

Lecture 36 HPA Scaling Down Demo

Section 10: Blue Green Deployment

Lecture 37 Blue Green Demo

Lecture 38 Pre Promotion Analysis

Lecture 39 Post Promotion Analysis

Lecture 40 Helm Blue Green Rollout

Lecture 41 Helm Cleanup

Section 11: Rollout With Istio

Lecture 42 Istio Introduction

Lecture 43 Istio Installation

Lecture 44 Istio Kiali Addon

Lecture 45 Argo Rollout Istio Implementation

Lecture 46 Istio Subset Implementation

Section 12: Environment Setup

Lecture 47 Setup AWS EC2 Instance with AWS Linux

Lecture 48 Setup AWS Windows EC2 Instance

Lecture 49 AWS Resource Pricing Model

Lecture 50 Minikube Setup in AWS EC2 Instance

Lecture 51 CentOS VirtualBox Setup

Lecture 52 VirtualBox GuestAddition

Lecture 53 Minikube Setup in CentOS

Lecture 54 Multi Node Kubernetes Setup

Section 13: Kubernetes Introduction

Lecture 55 Introduction to Containers

Lecture 56 Docker Container Demo - Docker Hub

Lecture 57 Kubernetes Architecture

Lecture 58 Kubernetes Pods

Lecture 59 Services in Kubernetes

Lecture 60 Service Demo - Cluster IP

Lecture 61 Service Demo - Node Port

Lecture 62 Service Demo - Node Port - SSH Tunnel

Lecture 63 Replicaset in Kubernetes

Lecture 64 Deployments in Kubernetes

Lecture 65 Kubernetes Additional Components

Section 14: Kubernetes Tools

Lecture 66 HELM3 Installation and Introduction

Lecture 67 Helm Repo, Charts, Templates Demo

Section 15: Prometheus and Grafana

Lecture 68 Prometheus Introduction

Lecture 69 Prometheus Installation

Lecture 70 Access Grafana and Prometheus UI

DevOps Engineers: Professionals who are involved in both development and operations, particularly those focusing on continuous integration and continuous deployment (CI/CD) practices.,Kubernetes Administrators: Individuals responsible for managing and orchestrating containerized applications using Kubernetes.,Software Developers: Developers who are working on building and deploying applications in Kubernetes environments and are interested in implementing progressive delivery techniques.,Site Reliability Engineers (SREs): Engineers focusing on the reliability and scalability of applications in cloud environments, and who are involved in automating operations tasks.,Cloud Architects: Professionals designing cloud infrastructure and services, especially those looking to implement advanced deployment strategies with Kubernetes.,Technical Team Leads: Team leaders or project managers overseeing teams that deploy applications in Kubernetes, who need to understand the deployment strategies and tools involved.