Autor Tópico: Decoding DevOps - From Basics to Advanced Projects with AI (Lida 22 vezes)

WAREZBLOG · « **em:** 08 de Junho de 2026, 02:47 »

Decoding DevOps - From Basics to Advanced Projects with AI
Last updated 5/2026
Created by Imran Teli
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English + subtitle | Duration: 378 Lectures ( 63h 52m ) | Size: 39.6 GB

Master DevOps with AI, AWS, GCP, Linux, Jenkins, Gitlab, GithubActions, Docker, Kubernetes, Terraform, Ansible & GitOps
What you'll learn
⚡ Learn DevOps from total scratch
⚡ Linux and Server Management (Gemini CLI)
⚡ Networking fundamentals & Vagrant setup
⚡ YAML, JSON, and Bash scripting with GitHub Copilot (AI)
⚡ AWS Cloud (IAM, EC2, S3, RDS, EBS, ELB, Systems Manager, Lambda, VPC, Amazon Q, CloudWatch, Auto Scaling, Route 53)
⚡ Build & Test Automation using Git, Maven, Jenkins, GitHub Actions, and GitLab CI/CD
⚡ CI/CD Pipelines and DevOps Projects with Nexus, SonarQube & Slack integration
⚡ Python scripting Basics and for Automation and AWS tasks with Amazon Q (AI code assistant)
⚡ Infrastructure as Code using Terraform (VPC, modules, backends)
⚡ Configuration Management using Ansible
⚡ Monitoring & Observability with Prometheus, Grafana, Loki, Alert manager & Alloy
⚡ Docker and Kubernetes (production-grade setup, Helm with AI, Lens)
⚡ AWS DevOps Services: CodeCommit, CodeBuild, CodePipeline, Beanstalk, Lambda
⚡ GitOps Project - end-to-end CI/CD workflow with Git as the single source of truth
Requirements
❗ Basic Computer Knowledge
Description
This course is designed for anyone who wants tostart or advance their DevOps career throughhands-on, project-based learning.
You'll begin withLinux, networking, and scripting fundamentals, then progress through key DevOps tools -Git, Jenkins, GitHub Actions, GitLab, Terraform, Ansible, Docker, Kubernetes, and AWS Cloud.
Each step builds on the last withreal projects, like setting up theVprofile application across multiple DevOps stages - from on-premise to AWS to Kubernetes.
The course also introducesAI-powered tools such asGitHub Copilot,Amazon Q, andAI-integrated Helm, helping youautomate faster, code smarter, and build intelligent DevOps pipelines.
And now - introducing the brand-newMonitoring & Observability section, where you'll learn how tocollect, visualize, and analyze metrics, logs, and traces using tools likePrometheus, Grafana, Loki, and Alloy.
By the end, you'll master both thecore DevOps practices andmodern AI-driven workflows, preparing you for real-world cloud and automation environments.
Step-by-Step Learning Path
Step 1
✨ Basics of Linux
✨ Server Management in Linux
✨ Vagrant
✨ Basics of Networking
✨Project: VProfile Project Intro & Setup on VMs
Step 2
✨ YAML & JSON
✨ Bash Scripting (Variables, Conditions, Loops)
✨ Automating Admin Tasks
✨ GitHub Copilot as AI Assistant for Scripting
Step 3
✨ Cloud Computing Intro
✨ IAM, EC2, EBS, ELB
✨ SSM & CloudShell Intro
✨ AWS CLI, S3, CloudWatch, RDS, Auto Scaling, Route53
✨Project: Lift & Shift Web App to AWS
✨ Re-Architecting Web App on AWS (PaaS & SaaS)
Step 4
✨ Git & GitHub
✨ Maven Build Tools
✨ Jenkins (CI/CD Pipelines, Master/Slave, Nexus, SonarQube)
✨ GitHub Actions (Workflows, Runners, Security Scans)
✨ GitLab CI/CD (Pipelines, Stages, Docker Integration)
Step 5
✨ Python Scripting
✨ Automating OS Tasks
✨ Python for AWS using Amazon Q (AI)
Step 6
✨ Terraform Fundamentals (Variables, Modules, Backends)
✨ Infrastructure as Code for VPC Setup
Step 7 - Monitoring & Observability
✨ Introduction to Monitoring & Observability
✨ Why Monitoring is Essential for DevOps
✨ Setting up Prometheus, Grafana, Loki, and Alloy
✨ Writing Queries with PromQL
✨ Connecting Grafana Data Sources
✨ Building Dashboards and Alerts
✨ Slack Integrations for Real-Time Notifications
✨ Integrating Loki and Alloy for Logs and Metrics
Step 8
✨ Ansible Intro
✨ Ad Hoc Commands, Modules, YAML Basics
✨ Playbooks, Variables, Conditions, Loops
✨ Handlers, Templates, Roles
✨ Ansible for AWS Automation
Step 9
✨ AWS (VPC Deep Dive, Lambda, Logging, Custom Metrics)
✨Project: CI/CD on AWS - Beanstalk, RDS, CodePipeline
Step 10
✨Project: Google cloud platform for multi tier app setup
✨ GCP Cloud shell
✨ VPC
✨ Firewalls
✨ VMs
✨ Cloud SQL & Memorystore
✨ Cloud DNS
✨ Managed Instance groups
✨ Secure HTTPS Load Balancers
✨ Certificate Manager
Step 11
✨ Docker (Containers, Images, Volumes, Networks)
✨ Kubernetes (Setup, Objects, Autoscaling, Ingress, ConfigMaps)
✨ Helm with AI, Lens
✨Project: VProfile Deployment on Kubernetes
Step 12
✨Project on GitOps
Who this course is for
⭐ Anybody who wants to Learn DevOps
Homepage

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https://www.udemy.com/course/decodingdevops

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Autor Tópico: Decoding DevOps - From Basics to Advanced Projects with AI (Lida 22 vezes)

WAREZBLOG

Decoding DevOps - From Basics to Advanced Projects with AI