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AWS

The AWS training is a bootcamp on AWS to prepare candidates on how to architect, develop and deploy secure and robust applications on AWS technologies. After finishing the training, the candidates will be able to design available, cost-efficient, fault-tolerant, scalable and distributed systems on AWS. The critical goal of the course is to make the candidates hands on

• Using compute, networking, storage, and database AWS services.

• Ability to identify and define technical requirements for an AWS-based application.

• Developing AWS Applications.

• Designing resilient architectures in AWS.

• Defining performant architectures in AWS.

• Designing Fault Tolerant architectures in AWS.

• Specifying secure applications and architectures in AWS.

• Designing cost-optimized architectures in AWS.

• Defining operationally excellent architectures in AWS.

Certification

After finishing the training, the candidates will have the sufficient knowledge to pass the following Certifications

AWS Certified Solution Architect − Professional

AWS Certified DevOps Engineer (Professional) − for top graduates

Course Overview

Topic 1: How Computers Work
  • Introduction to computer hardware (CPU, RAM, Storage)
  • How computers process information (binary, bits, bytes)
  • Overview of operating systems (Windows, macOS, Linux)
  • Basic computer architecture (input/output, storage, processing)
  • Building a Computer: A Step-by-Step Guide
Topic 2: Networking Fundamentals
  • Introduction to networking (LAN, WAN, Wi-Fi)
  • Network protocols (TCP/IP, HTTP, FTP)
  • Network devices (routers, switches, firewalls)
  • Basic network architecture (client-server, peer-to-peer)
Topic 3: Client-Server Architecture
  • Introduction to client-server architecture
  • How clients and servers communicate (requests, responses)
  • Types of clients (web browsers, mobile apps)
  • Types of servers (web servers, application servers, database servers)
Topic 4: Internet and Web Basics
  • Introduction to the Internet (history, infrastructure)
  • How the web works (HTTP, HTML, CSS, JavaScript)
  • Web browsers and how they work
  • Basic web development concepts (front-end, back-end)
Topic 5: Cloud Computing Basics
  • Introduction to cloud computing (IaaS, PaaS, SaaS
  • Cloud service models (public, private, hybrid)
  • Cloud deployment models (on-premises, off-premises)
  • Basic cloud security concepts (access control, data encryption)
Topic 6: Setting up a Development Environment
  • Introduction to development environments (IDEs, text editors)
  • Setting up a development environment (installing tools, configuring settings)
  • Basic version control concepts (Git, GitHub)
  • Introduction to command-line interfaces (CLI)

Topic 1: How Computers Work
  • Introduction to devops
  • History of DevOps
  • DevOps vs. traditional IT
  • Benefits of DevOps
Topic 2: History of DevOps
  • Early beginnings of DevOps
  • The rise of DevOps
  • Key milestones in DevOps history
  • Influence of DevOps on IT Industry
Topic 3: DevOps Principles and Practices
  • DevOps principles
  • DevOps practices
  • DevOps tools
  • DevOps methodologies
Topic 4: DevOps Culture and Organization
  • Introduction to DevOps culture
  • DevOps organization
  • DevOps leadership
  • DevOps metrics and feedback
Topic 5: DevOps Tools and Technologies
  • Introduction to DevOps tools
  • DevOps technologies
  • DevOps platforms
  • DevOps automation
Topic 6: DevOps Adoption and Implementation
  • Introduction to DevOps adoption
  • DevOps implementation roadmap
  • DevOps change management
  • DevOps training and education
Topic 7: DevOps Metrics and Monitoring
  • Introduction to DevOps metrics
  • DevOps monitoring
  • DevOps logging and analytics
  • DevOps feedback and continuous improvement
Topic 8: DevOps Security and Compliance
  • Introduction to DevOps security
  • DevOps compliance
  • DevOps risk management
  • DevOps security tools and technologies

Topic 1: What is Linux?
  • Definition of Linux
  • History of Linux
  • Linux distributions (Ubuntu, Debian, CentOS, Fedora)
  • Linux kernel and its role in the operating system
Topic 2: Linux File System
  • Overview of the Linux file system hierarchy
  • File system types (ext2, ext3, ext4, XFS)
  • File permissions and ownership
  • Basic file system commands (cd, ls, mkdir, rm)
Topic 3: Linux Shell and Command-Line Interface
  • Introduction to the Linux shell (bash, zsh, fish)
  • Basic shell commands (echo, cat, grep, sed)
  • Shell scripting basics (variables, loops, conditionals)
  • Introduction to the command-line interface (CLI)
Topic 4: Linux User Management
  • User accounts and groups
  • User authentication and authorization
  • Password management and security
  • Basic user management commands (useradd, usermod, groupadd)
Topic 5: Linux Package Management
  • Introduction to package management systems (apt, yum, rpm)
  • Package installation and removal
  • Package updates and upgrades
  • Basic package management commands (apt-get, yum install)
Topic 6: Linux Networking
  • Introduction to Linux networking (TCP/IP, DNS, DHCP)
  • Network configuration and management
  • Basic network commands (ifconfig, ip addr, ping)
  • Introduction to network security (firewalls, iptables)
Topic 7: Linux Security
  • Introduction to Linux security (access control, encryption)
  • Basic security commands (chmod, chown, setfacl)
  • Introduction to Linux security tools (SELinux, AppArmor)
  • Best practices for securing a Linux system
Topic 8: Linux Troubleshooting
  • Introduction to Linux troubleshooting (logs, debugging)
  • Basic troubleshooting commands (dmesg, journalctl, strace)
  • Introduction to Linux troubleshooting tools (syslog, systemd)
  • Best practices for troubleshooting a Linux system
Hands-on Activity: Setting up a Linux Environment
  • Install a Linux distribution (e.g., Ubuntu, CentOS)
  • Set up a user account and configure the shell
  • Install and configure a package management system
  • Configure the network and test connectivity
  • Practice basic Linux commands and troubleshooting techniques

Topic 1: Introduction to Version Control
  • Introduction to version control (definition, importance)
  • History of version control (RCS, CVS, SVN)
  • Types of version control systems (centralized, distributed)
  • Benefits of version control (collaboration, backup, tracking)
Topic 2: Git Fundamentals
  • Introduction to Git (definition, architecture)
  • Git basics (repository, commit, branch, merge)
  • Git workflow (clone, add, commit, push)
  • Git tools (git init, git add, git commit, git log)
Topic 3: Git Branching and Merging
  • Introduction to Git branching (definition, types)
  • Git branching models (feature branching, release branching)
  • Git merging (merge, rebase, cherry-pick)
  • Resolving conflicts in Git (merge conflicts, rebase conflicts)
Topic 4: Git Remote Repositories
  • Introduction to Git remote repositories (definition, types)
  • Git remote repository setup (GitHub, GitLab, Bitbucket)
  • Git remote repository workflow (clone, fetch, push)
  • Git remote repository collaboration (pull requests, code reviews)
Topic 5: Git Tools and Best Practices
  • Introduction to Git tools (Git GUI, Git CLI)
  • Git best practices (commit messages, branch naming)
  • Git workflows (feature branching, release branching)
  • Git security (SSH keys, access control)
Topic 6: Subversion (SVN) and Mercurial (Hg)
  • Introduction to SVN and Hg (definition, architecture)
  • SVN and Hg basics (repository, commit, branch, merge)
  • SVN and Hg workflow (checkout, update, commit)
  • SVN and Hg tools (svn init, svn add, svn commit, hg init, hg add, hg commit)
Topic 7: Version Control Systems Comparison
  • Comparison of version control systems (Git, SVN, Hg)
  • Features and limitations of each system
  • Choosing the right version control system
Topic 8: Source Code Management
  • Introduction to source code management (definition, importance)
  • Source code management best practices (code organization, code reviews)
  • Source code management tools (code analysis, code metrics)
  • Source code management workflows (continuous integration, continuous deployment)

Topic 1: Introduction to CI/CD
  • Introduction to CI/CD (definition, importance)
  • History of CI/CD (Agile, DevOps)
  • Benefits of CI/CD (faster time-to-market, improved quality, increased efficiency)
  • CI/CD pipeline (overview, components)
Topic 2: Continuous Integration (CI)
  • Introduction to CI (definition, principles)
  • CI tools (Jenkins, Travis CI, CircleCI)
  • CI workflow (build, test, deploy)
  • CI best practices (automated testing, code reviews)
Topic 3: Continuous Deployment (CD)
  • Introduction to CD (definition, principles)
  • CD tools (Ansible, Puppet, Chef)
  • CD workflow (deploy, monitor, feedback)
  • CD best practices (automated deployment, rollback)
Topic 4: CI/CD Pipeline
  • Introduction to CI/CD pipeline (definition, components)
  • CI/CD pipeline tools (Jenkins, GitLab CI/CD, CircleCI)
  • CI/CD pipeline workflow (build, test, deploy, monitor)
  • CI/CD pipeline best practices ( automation, feedback)
    • Topic 5: Automated Testing
    • Introduction to automated testing (definition, importance)
    • Types of automated testing (unit testing, integration testing, UI testing)
    • Automated testing tools (JUnit, PyUnit, Selenium)
    • Automated testing best practices (test-driven development, behavior-driven development)
    Topic 6: Continuous Monitoring and Feedback
    • Introduction to continuous monitoring (definition, importance)
    • Continuous monitoring tools (Prometheus, Grafana, New Relic)
    • Continuous monitoring best practices (real-time feedback, alerting)
    • Continuous feedback (definition, importance)
    • Continuous feedback tools (Jenkins, GitLab CI/CD, CircleCI)
    • Continuous feedback best practices (automated testing, code reviews)
    Topic 7: CI/CD Security
    • Introduction to CI/CD security (definition, importance)
    • CI/CD security best practices (access control, encryption)
    • CI/CD security tools (OWASP, Snyk, SonarQube)
    • CI/CD security workflows (security testing, vulnerability management)
    Topic 8: CI/CD in the Cloud
    • Introduction to CI/CD in the cloud (definition, importance)
    • CI/CD in the cloud tools (AWS CodePipeline, Azure DevOps, Google Cloud Build)
    • CI/CD in the cloud best practices (serverless, containerization)
    • CI/CD in the cloud workflows (automated deployment, continuous monitoring)
    Topic 9: Advanced CI/CD Concepts
    • Introduction to advanced CI/CD concepts (definition, importance)
    • Advanced CI/CD concepts tools (Spinnaker, Kubernetes, Jenkins)
    • Advanced CI/CD concepts and best practices (blue-green deployments, canary releases)
    • Advanced CI/CD concepts workflows (integrating security checks, continuous monitoring)

Topic 1: Introduction to IaC
  • Introduction to IaC (definition, importance)
  • History of IaC (DevOps, Agile)
  • Benefits of IaC (version control, reproducibility, scalability)
  • IaC vs. traditional infrastructure management
Topic 2: IaC Tools and Technologies
  • Introduction to IaC tools (Terraform, Ansible, CloudFormation)
  • IaC tool comparison (features, limitations)
  • IaC tool selection criteria (ease of use, scalability, compatibility)
Topic 3: Terraform Fundamentals
  • Introduction to Terraform (definition, architecture)
  • Terraform basics (providers, resources, modules)
  • Terraform workflow (init, plan, apply)
  • Terraform best practices (modularization, versioning)
Topic 4: Ansible Fundamentals
  • Introduction to Ansible (definition, architecture)
  • Ansible basics (playbooks, roles, modules)
  • Ansible workflow (inventory, playbook, execution)
  • Ansible best practices (modularization, idempotence)
Topic 5: CloudFormation Fundamentals
  • Introduction to CloudFormation (definition, architecture)
  • CloudFormation basics (templates, stacks, resources)
  • CloudFormation workflow (create, update, delete)
  • CloudFormation best practices (modularization, versioning)
Topic 6: IaC Best Practices
  • Introduction to IaC best practices (modularization, versioning)
  • IaC testing and validation (unit testing, integration testing)
  • IaC security and compliance (access control, encryption)
  • IaC collaboration and governance (version control, code reviews)
Topic 7: IaC and Continuous Integration/Continuous Deployment (CI/CD)
  • Introduction to IaC and CI/CD (integration, benefits)
  • IaC and CI/CD workflow (build, test, deploy)
  • IaC and CI/CD tools (Jenkins, GitLab CI/CD, CircleCI)
  • IaC and CI/CD best practices ( automation, feedback)
Topic 8: IaC and Cloud Computing
  • Introduction to IaC and cloud computing (integration, benefits)
  • IaC and cloud computing workflow (provision, configure, deploy)
  • IaC and cloud computing tools (AWS CloudFormation, Azure Resource Manager, Google Cloud Deployment Manager)
  • IaC and cloud computing best practices (scalability, security, cost optimization)

Topic 1: Introduction to Containerization
  • Introduction to containerization (definition, benefits)
  • History of containerization (chroot, LXC, Docker)
  • Containerization vs. virtualization
  • Benefits of containerization (lightweight, portable, scalable)
Topic 2: Docker Fundamentals
  • Introduction to Docker (definition, architecture)
  • Docker basics (images, containers, volumes)
  • Docker workflow (build, run, push)
  • Docker best practices (modularization, versioning)
Topic 3: Container Orchestration
  • Introduction to container orchestration (definition, benefits)
  • Container orchestration tools (Kubernetes, Docker Swarm, Apache Mesos)
  • Container orchestration workflow (deploy, manage, scale)
  • Container orchestration best practices (scalability, high availability, security)
Topic 4: Kubernetes Fundamentals
  • Introduction to Kubernetes (definition, architecture)
  • Kubernetes basics (pods, services, deployments)
  • Kubernetes workflow (create, update, delete)
  • Kubernetes best practices (modularization, versioning)
Topic 5: Docker Swarm Fundamentals
  • Introduction to Docker Swarm (definition, architecture)
  • Docker Swarm basics (nodes, services, tasks)
  • Docker Swarm workflow (create, update, delete)
  • Docker Swarm best practices (scalability, high availability, security)
Topic 6: Container Networking
  • Introduction to container networking (definition, benefits)
  • Container networking models (bridge, host, none)
  • Container networking tools (Docker networking, Kubernetes networking)
  • Container networking best practices (security, scalability)
Topic 7: Container Storage
  • Introduction to container storage (definition, benefits)
  • Container storage models (persistent, ephemeral)
  • Container storage tools (Docker volumes, Kubernetes persistent volumes)
  • Container storage best practices (security, scalability)
Topic 8: Container Security
  • Introduction to container security (definition, benefits)
  • Container security best practices (image scanning, network policies)
  • Container security tools (Docker security, Kubernetes security)
  • Container security workflows ( vulnerability management, compliance)

Topic 1: Introduction to Serverless Computing
  • Introduction to serverless computing (definition, benefits)
  • History of serverless computing (AWS Lambda, Azure Functions, Google Cloud Functions)
  • Serverless computing vs. traditional computing (cost, scalability, complexity)
  • Benefits of serverless computing (event-driven, real-time, cost-effective)
Topic 2: Serverless Computing Models
  • Introduction to serverless computing models (FaaS, BaaS, PaaS)
  • Function-as-a-Service (FaaS) (AWS Lambda, Azure Functions, Google Cloud Functions)
  • Backend-as-a-Service (BaaS) (Firebase, AWS Amplify, Google Cloud Firebase)
  • Platform-as-a-Service (PaaS) (Heroku, Google Cloud App Engine, Azure App Service)
Topic 3: Serverless Computing Providers
  • Introduction to serverless computing providers (AWS, Azure, Google Cloud)
  • AWS Lambda (features, pricing, use cases)
  • Azure Functions (features, pricing, use cases)
  • Google Cloud Functions (features, pricing, use cases)
Topic 4: Serverless Computing Architecture
  • Introduction to serverless computing architecture (event-driven, microservices)
  • Serverless computing architecture patterns (API Gateway, Load Balancer, Message Queue)
  • Serverless computing architecture best practices (scalability, security, monitoring)
Topic 5: Serverless Computing Security
  • Introduction to serverless computing security (benefits, challenges)
  • Serverless computing security best practices (IAM, encryption, access control)
  • Serverless computing security tools (AWS IAM, Azure Active Directory, Google Cloud IAM)
Topic 6: Serverless Computing Monitoring and Logging
  • Introduction to serverless computing monitoring and logging (benefits, challenges)
  • Serverless computing monitoring and logging tools (AWS CloudWatch, Azure Monitor, Google Cloud Logging)
  • Serverless computing monitoring and logging best practices (real-time feedback, alerting)
Topic 7: Serverless Computing Use Cases
  • Introduction to serverless computing use cases (real-time data processing, API Gateway, IoT)
  • Serverless computing use cases in industries (finance, healthcare, retail)
  • Serverless computing use cases in applications (web, mobile, desktop)
Topic 8: Serverless Computing Challenges and Limitations
  • Introduction to serverless computing challenges and limitations (cold start, vendor lock-in, debugging)
  • Serverless computing challenges and limitations in production (scalability, reliability, security)
  • Serverless computing challenges and limitations in development (testing, debugging, deployment)

Topic 1: Introduction to Security and Compliance
  • Introduction to security and compliance (definition, importance)
  • History of security and compliance (regulations, standards)
  • Security and compliance in DevOps (integration, automation)
  • Benefits of security and compliance in DevOps (risk reduction, cost savings)
Topic 2: Security Threats and Vulnerabilities
  • Introduction to security threats and vulnerabilities (types, examples)
  • Common security threats (malware, phishing, ransomware)
  • Common security vulnerabilities (SQL injection, cross-site scripting)
  • Security threat and vulnerability management (identification, assessment, mitigation)
Topic 3: Security Controls and Measures
  • Introduction to security controls and measures (types, examples)
  • Security controls (access control, authentication, authorization)
  • Security measures (encryption, firewalls, intrusion detection)
  • Security control and measure implementation (best practices, tools)
Topic 4: Compliance and Regulatory Requirements
  • Introduction to compliance and regulatory requirements (types, examples)
  • Common compliance and regulatory requirements (HIPAA, PCI-DSS, GDPR)
  • Compliance and regulatory requirement implementation (best practices, tools)
  • Compliance and regulatory requirement management (auditing, reporting)
Topic 5: Security and Compliance in Cloud Computing
  • Introduction to security and compliance in cloud computing (benefits, challenges)
  • Cloud computing security and compliance best practices (data encryption, access control)
  • Cloud computing security and compliance tools (AWS IAM, Azure Security Center, Google Cloud Security)
  • Cloud computing security and compliance management (auditing, reporting)
Topic 6: Security and Compliance in Containerization
  • Introduction to security and compliance in containerization (benefits, challenges)
  • Containerization security and compliance best practices (image scanning, network policies)
  • Containerization security and compliance tools (Docker Security, Kubernetes Security)
  • Containerization security and compliance management (auditing, reporting)
Topic 7: Security and Compliance in Serverless Computing
  • Introduction to security and compliance in serverless computing (benefits, challenges)
  • Serverless computing security and compliance best practices (function-level security, access control)
  • Serverless computing security and compliance tools (AWS Lambda Security, Azure Functions Security)
  • Serverless computing security and compliance management (auditing, reporting)
Topic 8: Security and Compliance in DevOps Tools
  • Introduction to security and compliance in DevOps tools (benefits, challenges)
  • DevOps tool security and compliance best practices (integration, automation)
  • DevOps tool security and compliance tools (Jenkins Security, GitLab Security)
  • DevOps tool security and compliance management (auditing, reporting)

Topic 1: Introduction to Monitoring and Logging
  • Introduction to monitoring and logging (definition, importance)
  • History of monitoring and logging (traditional, modern)
  • Monitoring and logging in DevOps (integration, automation)
  • Benefits of monitoring and logging in DevOps (real-time feedback, issue detection)
Topic 2: Monitoring Tools and Techniques
  • Introduction to monitoring tools and techniques (types, examples)
  • Monitoring tools (Nagios, Prometheus, Grafana)
  • Monitoring techniques (polling, trapping, logging)
  • Monitoring tool and technique implementation (best practices, tools)
Topic 3: Logging Tools and Techniques
  • Introduction to logging tools and techniques (types, examples)
  • Logging tools (ELK, Splunk, Sumo Logic)
  • Logging techniques (log aggregation, log analysis, log visualization)
  • Logging tool and technique implementation (best practices, tools)
Topic 4: Monitoring and Logging in Cloud Computing
  • Introduction to monitoring and logging in cloud computing (benefits, challenges)
  • Cloud computing monitoring and logging best practices (real-time feedback, issue detection)
  • Cloud computing monitoring and logging tools (AWS CloudWatch, Azure Monitor, Google Cloud Logging)
  • Cloud computing monitoring and logging management (auditing, reporting)
Topic 5: Monitoring and Logging in Containerization
  • Introduction to monitoring and logging in containerization (benefits, challenges)
  • Containerization monitoring and logging best practices (real-time feedback, issue detection)
  • Containerization monitoring and logging tools (Docker Monitoring, Kubernetes Monitoring)
  • Containerization monitoring and logging management (auditing, reporting)
Topic 6: Monitoring and Logging in Serverless Computing
  • Introduction to monitoring and logging in serverless computing (benefits, challenges)
  • Serverless computing monitoring and logging best practices (real-time feedback, issue detection)
  • Serverless computing monitoring and logging tools (AWS Lambda Monitoring, Azure Functions Monitoring)
  • Serverless computing monitoring and logging management (auditing, reporting)
Topic 7: Monitoring and Logging in DevOps Tools
  • Introduction to monitoring and logging in DevOps tools (benefits, challenges)
  • DevOps tool monitoring and logging best practices (integration, automation)
  • DevOps tool monitoring and logging tools (Jenkins Monitoring, GitLab Monitoring)
  • DevOps tool monitoring and logging management (auditing, reporting)
Topic 8: Advanced Monitoring and Logging Techniques
  • Introduction to advanced monitoring and logging techniques (types, examples)
  • Advanced monitoring techniques (AIOps, machine learning)
  • Advanced logging techniques (log analytics, log visualization)
  • Advanced monitoring and logging tool and technique implementation (best practices, tools)

Topic 1: Introduction to DevOps Tools and Practices
  • Introduction to DevOps tools and practices (definition, importance)
  • History of DevOps tools and practices (traditional, modern)
  • DevOps tools and practices in DevOps (integration, automation)
  • Benefits of DevOps tools and practices in DevOps (efficiency, quality)
Topic 2: Version Control Systems
  • Introduction to version control systems (definition, importance)
  • Types of version control systems (centralized, distributed)
  • Version control system tools (Git, SVN, Mercurial)
  • Version control system best practices (branching, merging, committing)
Topic 3: Continuous Integration and Continuous Deployment
  • Introduction to continuous integration and continuous deployment (definition, importance)
  • Continuous integration and continuous deployment tools (Jenkins, Travis CI, CircleCI)
  • Continuous integration and continuous deployment best practices (testing, validation, deployment)
Topic 4: Configuration Management
  • Introduction to configuration management (definition, importance)
  • Configuration management tools (Ansible, Puppet, Chef)
  • Configuration management best practices (infrastructure as code, idempotence)
Topic 5: Monitoring and Logging Tools
  • Introduction to monitoring and logging tools (definition, importance)
  • Monitoring and logging tools (Nagios, Prometheus, Grafana)
  • Monitoring and logging best practices (real-time feedback, issue detection)
Topic 6: Agile Project Management
  • Introduction to agile project management (definition, importance)
  • Agile project management tools (Jira, Trello, Asana)
  • Agile project management best practices (sprints, backlogs, retrospectives)
Topic 7: DevOps Automation Tools
  • Introduction to DevOps automation tools (definition, importance)
  • DevOps automation tools (Ansible, SaltStack, PowerShell)
  • DevOps automation best practices (infrastructure as code, idempotence)
Topic 8: DevOps Security Tools
  • Introduction to DevOps security tools (definition, importance)
  • DevOps security tools (OWASP, Snyk, SonarQube)
  • DevOps security best practices (security testing, vulnerability management)
Topic 9: DevOps Collaboration Tools
  • Introduction to DevOps collaboration tools (definition, importance)
  • DevOps collaboration tools (Slack, Microsoft Teams, Email)
  • DevOps collaboration best practices (communication, feedback, transparency)
Topic 10: DevOps Metrics and Feedback
  • Introduction to DevOps metrics and feedback (definition, importance)
  • DevOps metrics and feedback tools (DORA, DevOps Research and Assessment)
  • DevOps metrics and feedback best practices (lead time, deployment frequency, mean time to recovery)

Topic 1: Introduction to Cloud Computing in DevOps
  • Introduction to cloud computing in DevOps (definition, importance)
  • History of cloud computing in DevOps (traditional, modern)
  • Cloud computing in DevOps (integration, automation)
  • Benefits of cloud computing in DevOps (scalability, flexibility)
Topic 2: Cloud Computing Providers
  • Introduction to cloud computing providers (AWS, Azure, Google Cloud)
  • Cloud computing provider comparison (features, pricing)
  • Cloud computing provider selection criteria (security, compliance, support)
Topic 3: AWS in DevOps
  • Introduction to AWS in DevOps (definition, importance)
  • AWS services for DevOps (EC2, S3, Lambda)
  • AWS integration with DevOps tools (Jenkins, Docker, Kubernetes)
  • AWS best practices for DevOps (security, monitoring, logging)
Topic 4: Azure in DevOps
  • Introduction to Azure in DevOps (definition, importance)
  • Azure services for DevOps (VMs, Storage, Functions)
  • Azure integration with DevOps tools (Azure DevOps, Docker, Kubernetes)
  • Azure best practices for DevOps (security, monitoring, logging)
Topic 5: Google Cloud in DevOps
  • Introduction to Google Cloud in DevOps (definition, importance)
  • Google Cloud services for DevOps (Compute Engine, Cloud Storage, Cloud Functions)
  • Google Cloud integration with DevOps tools (Google Cloud Build, Docker, Kubernetes)
  • Google Cloud best practices for DevOps (security, monitoring, logging)
Topic 6: Cloud Computing Security in DevOps
  • Introduction to cloud computing security in DevOps (definition, importance)
  • Cloud computing security best practices (IAM, encryption, access control)
  • Cloud computing security tools (AWS IAM, Azure Security Center, Google Cloud Security)
Topic 7: Cloud Computing Monitoring and Logging in DevOps
  • Introduction to cloud computing monitoring and logging in DevOps (definition, importance)
  • Cloud computing monitoring and logging best practices (real-time feedback, issue detection)
  • Cloud computing monitoring and logging tools (AWS CloudWatch, Azure Monitor, Google Cloud Logging)
Topic 8: Cloud Computing Cost Optimization in DevOps
  • Introduction to cloud computing cost optimization in DevOps (definition, importance)
  • Cloud computing cost optimization best practices (rightsizing, reserved instances, autoscaling)
  • Cloud computing cost optimization tools (AWS Cost Explorer, Azure Cost Estimator, Google Cloud Cost Management)
Topic 9: Cloud Computing Migration and Deployment in DevOps
  • Introduction to cloud computing migration and deployment in DevOps (definition, importance)
  • Cloud computing migration and deployment best practices (lift and shift, re-architecture, hybrid)
  • Cloud computing migration and deployment tools (AWS Migration Hub, Azure Migration Center, Google Cloud Migration)
Topic 10: Cloud Computing Governance and Compliance in DevOps
  • Introduction to cloud computing governance and compliance in DevOps (definition, importance)
  • Cloud computing governance and compliance best practices (security, compliance, risk management)
  • Cloud computing governance and compliance tools (AWS Governance, Azure Governance, Google Cloud Governance)

Topic 1: Introduction to Automation Scripting in DevOps
  • Introduction to automation scripting in DevOps (definition, importance)
  • History of automation scripting in DevOps (traditional, modern)
  • Automation scripting in DevOps (integration, automation)
  • Benefits of automation scripting in DevOps (efficiency, consistency)
Topic 2: Bash Scripting in DevOps
  • Introduction to Bash scripting in DevOps (definition, importance)
  • Bash scripting basics (variables, loops, conditionals)
  • Bash scripting for DevOps ( automating infrastructure changes, application deployments)
  • Bash scripting best practices (security, error handling)
Topic 3: PowerShell Scripting in DevOps
  • Introduction to PowerShell scripting in DevOps (definition, importance)
  • PowerShell scripting basics (variables, loops, conditionals)
  • PowerShell scripting for DevOps ( automating infrastructure changes, application deployments)
  • PowerShell scripting best practices (security, error handling)
Topic 4: Python Scripting in DevOps
  • Introduction to Python scripting in DevOps (definition, importance)
  • Python scripting basics (variables, loops, conditionals)
  • Python scripting for DevOps ( automating infrastructure changes, application deployments)
  • Python scripting best practices (security, error handling)
Topic 5: Automation Scripting Tools and Frameworks
  • Introduction to automation scripting tools and frameworks (Ansible, SaltStack, Puppet)
  • Automation scripting tool and framework comparison (features, pricing)
  • Automation scripting tool and framework selection criteria (security, compliance, support)
Topic 6: Automating Infrastructure Changes with Scripts
  • Introduction to automating infrastructure changes with scripts (definition, importance)
  • Automating infrastructure changes with Bash, PowerShell, and Python scripts
  • Automating infrastructure changes best practices (security, error handling)
Topic 7: Automating Application Deployments with Scripts
  • Introduction to automating application deployments with scripts (definition, importance)
  • Automating application deployments with Bash, PowerShell, and Python scripts
  • Automating application deployments best practices (security, error handling)
Topic 8: Continuous Integration and Continuous Deployment with Scripts
  • Introduction to continuous integration and continuous deployment with scripts (definition, importance)
  • Continuous integration and continuous deployment with Bash, PowerShell, and Python scripts
  • Continuous integration and continuous deployment best practices (security, error handling)
Topic 9: Monitoring and Logging with Scripts
  • Introduction to monitoring and logging with scripts (definition, importance)
  • Monitoring and logging with Bash, PowerShell, and Python scripts
  • Monitoring and logging best practices (security, error handling)
Topic 10: Advanced Automation Scripting Topics
  • Introduction to advanced automation scripting topics (definition, importance)
  • Advanced automation scripting topics (machine learning, artificial intelligence)
  • Advanced automation scripting best practices (security, error handling)
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