DevOps with Multi Cloud Training in KPHB

DevOps with Multi-Cloud

DevOps || AWS | Azure | GSP || 15+ DevOps Tools || 8 Cloud Services || Linux & Shell Scripting || PYTHON Scripting

Course Overview

DevOps with Multi-Cloud is transforming how businesses manage applications and infrastructure across cloud platforms. This course covers the integration of AWS, Azure, and Google Cloud with DevOps practices for seamless operations. You will learn automation, CI/CD pipelines, container orchestration, and monitoring techniques.

Mastering multi-cloud strategies improves scalability, security, and reliability. This training provides hands-on experience with cloud tools like Docker, Kubernetes, Terraform, Ansible, and Jenkins. Real-time projects and expert guidance will help you gain industry-ready skills.

Join our DevOps with Multi-Cloud Training in KPHB to unlock career opportunities in cloud computing. Whether you’re a beginner or an experienced professional, this course ensures you stay ahead in the evolving IT landscape.

Learn software skills with real experts, either in live classes with videos or without videos, whichever suits you best.

Course Details:

Course Price:

with videos : ₹ 25,000/-
with out videos : ₹ 20,000/-

Lesson Duration

100 Days

Language:

English

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Description

This course is designed to help professionals implement DevOps practices in multi-cloud environments. You will learn how to deploy, manage, and automate applications across AWS, Azure, and GCP using industry-leading DevOps tools.

The training covers infrastructure as code (IaC), CI/CD pipelines, microservices, Kubernetes, serverless computing, logging, and monitoring. You will also explore best practices for security, cost optimization, and cloud automation.

By the end of this course, you will have a strong foundation in DevOps and multi-cloud strategies, making you job-ready for roles like DevOps Engineer, Cloud Engineer, and Site Reliability Engineer (SRE).

Course Objectives

Understand DevOps fundamentals and multi-cloud architecture.
Deploy and manage applications on AWS, Azure, and GCP.
Implement CI/CD pipelines using Jenkins, Git, and Docker.
Automate infrastructure with Terraform, Ansible, and Kubernetes.
Optimize cloud security, monitoring, and logging with real-world tools.
Gain hands-on experience with real-time projects.

Prerequisites

Basic knowledge of Linux and scripting (Bash/Python).
Understanding of cloud computing concepts (AWS, Azure, or GCP basics).
Familiarity with networking and system administration is helpful.
Prior experience in software development or IT operations is an advantage but not required.

Course Curriculum

Introduction to Cloud Computing
- What is Cloud Computing?
- Evolution and importance of cloud technology
- Key players in the market: AWS, Azure, GCP
Why Cloud Computing?
- Traditional infrastructure vs. cloud infrastructure
- Benefits of moving to the cloud for businesses
- Use cases across industries: startups, enterprises, etc
Benefits of Cloud Computing
- Cost Efficiency
- Scalability and Elasticity
- Flexibility and Agility
- Disaster Recovery and Business Continuity
- Global Accessibility and High Availability
- Automated Infrastructure Management (AI/ML)
Types of Cloud Computing
- Public Cloud: Introduction and examples (AWS, Azure, GCP)
- Private Cloud: On-premise cloud solutions, hybrid models
- Hybrid Cloud: Combining public and private cloud resources
- Community Cloud: Shared cloud models for specific groups/organizations
Cloud Service Models
- Software as a Service (SaaS): Cloud-based software offerings (e.g., Gmail, Salesforce)
- Platform as a Service (PaaS): Managed platforms for development (e.g., AWS Elastic Beanstalk, Azure App Service, GCP App Engine)
- Infrastructure as a Service (IaaS): Compute resources on demand (e.g., AWS EC2, Azure Virtual Machines, GCP Compute Engine)
Scaling in Cloud Computing
- Horizontal Scaling: Adding more servers to handle increased load
- Vertical Scaling: Increasing the capacity of existing servers (CPU, RAM, etc.)
- Examples of scaling in AWS, Azure, and GCP
Cloud Computing Issues
- Vendor Lock-In
- Downtime and Outages
- Data Privacy and Compliance
- Integration with existing infrastructure
- Performance and Latency Issues
Security in the Cloud
- Shared Responsibility Model: Customer and cloud provider roles
- Identity and Access Management (IAM)
- Data Encryption (at rest and in transit)
- Cloud Security Best Practices (Security Groups, Firewalls, DDoS Protection)
- Compliance with global standards (GDPR, HIPAA, etc.)
Cloud Costing Models
- Pay-as-you-go vs. Reserved instances
- Cost Optimization Techniques
- AWS, Azure, and GCP pricing models comparison
- Monitoring and managing cloud costs (AWS Cost Explorer, Azure Cost Management, GCP Cost Calculator)

What is virtualization?
- Virtualization and cloud computing
- Types of virtualizations
- Virtualization terminologies
- Hypervisor Concepts
- Benefits
- Vendors
Linux
- All-important Linux commands
- The Linux filesystem
- File permissions
- Process management.
- User account management
- Software management
- Networking in Linux

Instance Launch (Windows and Linux OS)
- Overview of launching cloud instances using EC2 (AWS), Azure VMs, and Compute Engine (GCP) with both Windows and Linux operating systems.
Instance Types
- Overview of instance types (General Purpose, Compute Optimized, Memory Optimized) and selecting appropriate types for different workloads across AWS, Azure, and GCP.
Key Pair Management
- Generating and managing SSH Key Pairs for Linux and RDP Access for Windows instances across all platforms
Security Groups & Firewalls
- Configuring Security Groups (AWS), NSGs (Azure), and Firewall Rules (GCP) to control network access and secure instances.
Storage and Snapshots
- Managing Volumes (AWS EBS, Azure Disks, GCP Persistent Disks) and creating Snapshots for backup and recovery
User Data and Metadata
- Automating instance configurations with User Data and retrieving instance-specific information using Metadata.
Load Balancers
- Configuring and managing different types of Load Balancers: Elastic Load Balancer (AWS), Azure Load Balancer, and GCP Load Balancer.
Billing and Monitoring Alarms
- Setting up Billing Alarms to monitor cloud spending and Instance Alarms for tracking performance and health across AWS, Azure, and GCP.
Auto Scaling
- Implementing Auto Scaling Groups to manage instance scaling automatically based on demand, using AWS Auto Scaling, Azure VM Scale Sets, and GCP Managed Instance Groups
Scaling Types and Policies
- Understanding Horizontal and Vertical Scaling, and configuring autoscaling policies to handle dynamic workloads.
Aws,Azure And Gcp Auto-scaling
- Get Started with Auto Scaling Using the Console
- Maintain a Fixed Number of Running EC2 Instances
- Dynamic Scaling
- The lifecycle of autoscaling
- The lifecycle of autoscaling
EBS (Elastic Block Storage)
- Create EBS volumes
- Delete EBS Volumes
- Attach and detach EBS volumes
- Mounting and unmounting EBS volume
- Creating and deleting snapshots
- Creating volumes from snapshots

Networking Basics
Public IPs & Private IPs
CIDR Range
Subnet Calculations
Creating custom VPCs and custom Subnets
Network ACL’s
Route Tables & IGW

What is s3,blob storage,cloud storage
Storage Classes
Versioning
S3 bucket ACL and bucket permission
S3 data partition
Data copying and moving
Cross-region replication / Same Region replication
Life Cycle Management
Security & Encryption
KMS (Key Management Service)
Static Webhosting with S3 bucket and blob storage container and cloud stoarge
Events configuration on S3 buckets,blob storage,cloud storage
Enabling cross account access for S3
S3 Data management and backup using 3rd Party applications.
Pre-Signed URLs
Storage Gateway

Root Account Vs IAM user
Multi Factor Authentication for Users
IAM Password Policies
Keys Configure and different access approaches
User, groups and Role concepts
Creating Customer Managed Policies.
Auditing User Activity

Launching a RDS Instances (MySQL, MSSQL & Aurora)
Multi-AZ & Read Replicas for RDS instances.
High Availability concept in RDS
Difference between DB on Ec2 and managed RDS
RDS Proxy configure process
Elasticache overview.
Connection process from RDS ton Ec2
Connection process from RDS to local machine by using Work Bench process
Creating DB and tables run the queries
Configure Read replica with masters and access the tables from read replica.
DynamoDB overview
Data Importing option from S3 to RDS
Database Migration Service
DB costings and reserved nodes process.

AWS Secret Manager
Key Management Services
AWS Certificate Manager
AWS Inspector
AWS Trusted Advisor
AWS Global Accelerator
Content Delivery Networks / CloudFront
AWS Shield and WAF (Web Application Firewall)
AWS Shield and WAF (Web Application Firewall)
AWS Config

Overview of the Lambda
Configuration with different services
Creation and automate the service by using lambda boto3
General configuration environment setup In lambda
Lambda layers and importance
Limitations

DNS Records overview
Routing Policies
Hosting sample Website and configuring Policies.
Simple RP
Weighted RP
Failover RP
Geo Location RP
Latency based routing
Cross region high availability
Configure records A type, C type
Alias configure to ELB, Static website hosting and Cloud Front

What is DevOps?
DevOps Market Trends | DevOps Engineer Skills
DevOps Delivery Pipeline
DevOps Ecosystem

Introduction
Type of shells
Variables
Types of variables
Operators
Input arguments
String comparison
Athematic comparison
File conditions
If, loops, case, functions
Examples

Apache webserver
- Installations
- Configuration
Tomcat application server
- Installation, configuration
- Tomcat manager
- Application management

Git Introductions
- What is Git
- How it will work
- Features
Git Workflow
- Working Directory
- Staging
- Local Repository
- Remote Repository
How to setup GIT
- Installing Git
- First-Time Git Setup
- Getting a Git Repository
Working with various commands in GIT
- Git Cheat sheet
Recording Changes to the Repository
- How to check the Status of Your Files
- How to track New Files
- Staging our modified files
- Ignoring Files from GIT
- Viewing Your Un-staged and Staged Changes
- How to commit Your Changes
- Skipping the Staging Area and commit
- Removing Files from GIT
Viewing the Commit History
- Limiting Log Output
- Using a GUI to Visualize History
Undoing Things
- Changing Your Last Commit
- Unstaging a Staged File
- Unmodifying a Modified File
Git Forking
- Repository forking
Working with Remotes
- Showing Your Remotes
- Adding Remote Repositories
- Fetching and Pulling from Your Remotes
- Pushing to Your Remotes
- Inspecting a Remote
- Removing and Renaming Remotes
Branching and Merging in Git
- What a Branch Is
- Basic in Branching and Merging
- Branch Management in GIT
- Branching Workflows and its usage
- Remote Branches – create and delete
- Rebasing

Maven Installation
Maven Build requirements
Maven POM Builds (pom.xml)
Maven Build Life Cycle
Maven Local Repository (.m2)
Maven Global Repository
Group ID, Artifact ID, Snapshot
Maven Dependencies
Maven Plugin

Installation & Configuration of SonarQube
Initiate code-scan with SonarQube server
SonarQube dashboard
Sample project to check code scan
Maven integration with SonarQube
Real-time use cases on SonarQube

Introduction to Jenkins
Continuous Integration with Jenkins
Configure Jeins
Jenkins Management
Scheduling build Jobs
- POLL SCM
- POLL SCM
Jenkins Master & Slave Node Configuration
Jenkins Workspace Management
Securing Jenkins
- Authentication
- Authorization
- Confidentiality
- Creating Users
Jenkins Plugins
- Installing Jenkins Plugins
- SCM plugin
- Build and test
Jenkins configure with below services tools
- Ec2
- Lambda
- S3
- GitHub
- Docker
- Jfrog
- SonarQube
- Kubernetes
- Trivy
- ArgoCD
Azure CiCd
Git Lab CiCd

Docker Introduction
What is Docker Image
How to get Docker Image
Docker Installation
Working with Docker Containers
- What is Container
- Docker Engine
- Crating Containers with an Image
- Working with Images
Docker Command Line Interphase
Docker Compose
Docker Hub
Docker Trusted Registry
Docker swarm
Docker attaches
Docker File & Command

Revisiting Kubernetesz
Cluster Architecture
Spinning up a Kubernetes Cluster on Ec2 VMs
Exploring your Cluster
Understanding YAML
Creating a Deployment in Kubernetes using YAML
Creating a Service in Kubernetes
Installing Kubernetes Dashboard
Deploying an App using Dashboard
Using Rolling Updates in Kubernetes
Containers and Container Orchestration
Helm Charts
Schedulers
Metric Server deployment
Kubernetes volume
RBAC process
Aks
Eks

Helm installation
Helm configuration
Helm deployment

Configuration
K8s logs

Installation
Configurations
CD

Introduction to Continuous Monitoring
Introduction to Grafana
Installing Grafana
Grafana Prometheus and Objects
Grafana Prometheus configure to Kubernetes

Introduction to Ansible
Ansible Server Configuration
Infrastructure Management
SSH Connection in Ansible Master
YAML Scripts
Host Inventory
- Hosts and Groups
- Host Variables
- Group Variables
- Host and Group Specific Data
Ad-hoc Commands
Playbooks o Variables
- Conditionals
- Loops o Blocks
- Handlers
- Templates
Modules
- Core Modules
- Extra Modules
Ansible Role

Introduction to terraform
- Infrastructure Automation
- Install Terraform
- Providers
- Resources
- Basic Syntax
- Exercise: Your First Script main.tf
Getting started with Terraform
- Terraform Plan, show, Apply, Destroy
- Exploring Terraform Registry
- Interpolation
- Tainting and Updating Resources
- Terraform Console and Output
- Terraform Variables
- Breaking Out Our Variables and Outputs
- Lab exercises: Breaking down main.tf into variables.tf, output.tf
Terraform Modules
- Introduction to Modules
- Module repositories
- First Basic Module
- The Module codes
- Main Terraform Code
- Lab exercises: Modules – The Root Module
Terraform: Writing in a more organized way
- Maps and Lookups
- Terraform Workspaces
- Breaking Out Our Variable Definitions
- File, Remote -Exec and Local-Exec
Terraform with AWS: lab
- Setting up the system for AWS
- AWS Storage: The S3 Bucket and Random ID
- AWS Storage: The Root Module
- AWS Compute: AMI Data, Key Pair, and the File Function
- AWS Compute: The EC2 Instance
- AWS Compute: User Data and Template Files
- AWS Compute: The Root Module
Terraform state
- Remote state
- Data Sources
- Templates
- Conditionals
- Built-in Functions
- Working with state files
- Outputs, count and Join Function
Terraform with AWS: Lab Part
- AWS Networking: VPC, IGW, and Route Tables
- AWS Networking: Subnets, Security, and the Count Attribute
- AWS Networking: The Root Module
Terraform Troubleshooting and Testing
- Terraform Plan revisited
- Debugging the script
- Terraform Testing
- Lab: Writing test scripts for Terraform.
- Lab: Testing with Docker
Terraform Best Practices
- Best practices in writing terraform scripts
- Terraform Workflow
- Terraform projects
- Other Hashi Corp tools
- New features of Terraform Introduction to Terraform

Introduction to Python
List, Ranges & Tuples in Python
Input and Output in Python
Python Object Oriented
Python Regular Expressions
Python Necessity DevOps

Who can learn this course

IT Professionals looking to upskill in DevOps and cloud computing.
Software Developers who want to automate application deployment.
System Administrators aiming to transition into DevOps roles.
Cloud Engineers seeking expertise in multi-cloud environments.
Freshers & Graduates interested in cloud and DevOps careers.

Enroll Now!

In conclusion, our DevOps with Multi Cloud Training in KPHB, Hyderabad is the perfect program to launch your career. Not only will you gain theoretical knowledge, but you will also apply your skills through hands-on projects.

So why wait? Join today and start your journey in DevOps and Multi Cloud with expert guidance!

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FAQ's

DevOps with Multi-Cloud refers to implementing DevOps practices across multiple cloud platforms, such as AWS, Microsoft Azure, and Google Cloud Platform (GCP). It ensures high availability, flexibility, and resilience by avoiding vendor lock-in.

It is important because:

Prevents Cloud Lock-in – Organizations are not restricted to a single provider.
Enhances Reliability – Workloads are distributed across different clouds, improving uptime.
Optimizes Costs – Businesses can choose cost-effective cloud solutions.
Increases Flexibility – Different cloud providers offer unique services that can be leveraged.
Improves Disaster Recovery – Data replication across clouds ensures quick recovery in case of failure.

Multi-cloud DevOps enables organizations to maximize performance, cost savings, and security.

To implement DevOps in a Multi-Cloud environment, key tools and technologies include:

Infrastructure as Code (IaC) – Terraform, AWS CloudFormation, Azure ARM Templates.
Containerization & Orchestration – Docker, Kubernetes (EKS, AKS, GKE).
CI/CD Pipelines – Jenkins, GitHub Actions, GitLab CI/CD, AWS CodePipeline.
Configuration Management – Ansible, Puppet, Chef.
Monitoring & Logging – Prometheus, Grafana, ELK Stack, AWS CloudWatch, Azure Monitor.
Security & Compliance – HashiCorp Vault, AWS IAM, Azure Security Center.
Serverless Computing – AWS Lambda, Azure Functions, Google Cloud Functions.

These technologies enable seamless automation, deployment, monitoring, and security across multiple cloud environments.

Multi-Cloud DevOps improves CI/CD by:

Automating Deployments – Using tools like Jenkins, GitHub Actions, and AWS CodePipeline.
Containerized Applications – Docker and Kubernetes allow seamless deployment across clouds.
Cross-Cloud Orchestration – Terraform and Ansible manage infrastructure across multiple providers.
Monitoring and Feedback Loops – Prometheus, CloudWatch, and Azure Monitor provide real-time insights.
Security & Compliance Integration – HashiCorp Vault and cloud IAM ensure secure deployments.

CI/CD in Multi-Cloud ensures faster releases, minimal downtime, and consistency across different cloud platforms.

Learning DevOps with Multi-Cloud offers several advantages:

High Demand in IT – Multi-Cloud skills are in demand across enterprises and startups.
Better Career Opportunities – Opens doors to roles in cloud engineering, DevOps, and automation.
Scalability & Flexibility – Enables deployment of applications on multiple cloud providers.
Improved Disaster Recovery – Ensures resilience and data redundancy across cloud platforms.
Cost Optimization – Organizations can choose the most cost-effective cloud services.
Vendor Independence – Prevents reliance on a single cloud provider.

With Multi-Cloud expertise, you can work in cloud security, DevOps automation, and enterprise IT solutions.

To get started with DevOps in Multi-Cloud, you should have:

Basic Linux Knowledge – Understanding of commands, shell scripting, and system administration.
Cloud Computing Basics – Familiarity with AWS, Azure, or GCP fundamentals.
Networking Concepts – Understanding of VPC, subnets, security groups, and DNS.
Infrastructure as Code (IaC) – Basics of Terraform, Ansible, or CloudFormation.
Version Control (Git/GitHub) – Experience with Git for code collaboration.
CI/CD Pipeline Concepts – Understanding of Jenkins, GitHub Actions, or GitLab CI/CD.

If you are new to cloud computing, starting with AWS, Azure, or Google Cloud certification can help build a strong foundation.

With expertise in Multi-Cloud DevOps, you can apply for roles such as:

Multi-Cloud DevOps Engineer – Automates deployments across AWS, Azure, and GCP.
Cloud Solutions Architect – Designs scalable cloud solutions using multiple providers.
Site Reliability Engineer (SRE) – Ensures system reliability and automates operations.
Infrastructure Engineer – Manages cloud infrastructure using IaC tools like Terraform.
CI/CD Engineer – Focuses on continuous integration, testing, and deployments.
Cloud Security Engineer – Implements security best practices in Multi-Cloud environments.
Kubernetes Administrator – Manages containerized applications across cloud platforms.

Multi-Cloud expertise is highly valuable in enterprises looking for cloud flexibility, security, and automation.

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