Live online · US evening batch

Multi Cloud Online Training in USA

Learn AWS and Azure DevOps together in live classes that fit after your workday in the US: Sunday to Thursday, 9–11 PM Eastern / 6–8 PM Pacific. Build three real projects on both clouds and get interview-ready for US cloud and DevOps roles.

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Course at a glance

$360 Fee
100 days Duration
Sun–Thu Classes
9–11 PM Time (ET)

Free demo in US evening hours · No payment needed

US evening classes
AWS + Azure in one course
Every class recorded
3 projects for your GitHub
$360 · 100 days

Class schedule in US time zones

Our trainer teaches from Hyderabad early in the morning India time, which lands in the evening across the United States. You finish work, have dinner, and join a two-hour live class on Zoom. Classes run five days a week, Sunday to Thursday in the US, so Friday and Saturday stay free.

India does not change its clocks, but the US does. From the second Sunday of March to the first Sunday of November (daylight saving time), use the first time column. From November to March, every US class starts one hour earlier on your clock.

Missed a class because of an on-call shift or a late meeting? Every session is recorded and shared the next morning, and you can send doubts to the trainer on WhatsApp.

Time zoneMar – NovNov – Mar
Eastern (New York, New Jersey, Atlanta)9–11 PM8–10 PM
Central (Dallas, Houston, Chicago)8–10 PM7–9 PM
Mountain (Denver, Phoenix*)7–9 PM6–8 PM
Pacific (Bay Area, Seattle, LA)6–8 PM5–7 PM
India (trainer)6:30–8:30 AM6:30–8:30 AM

US days: Sunday to Thursday. India days: Monday to Friday.
*Arizona does not observe daylight saving time, so Phoenix follows the Nov–Mar column all year.

Who joins from the USA

Most of our US learners fall into one of these four groups.

Students on OPT or STEM OPT

You have a degree but need hands-on cloud work to talk about in interviews. You leave with three projects on AWS and Azure in your GitHub, and practice explaining them the way US hiring managers expect.

Consultants on the bench

Many consulting and staffing firms in New Jersey, Dallas and Atlanta look for engineers who can work on both AWS and Azure clients. Adding the second cloud widens the projects you can be submitted for.

QA, support and sysadmin professionals

You already work in IT and want to move into DevOps. The course starts from Linux, Git and Docker before cloud, so you are not lost in week one, and the evening timing lets you keep your current job.

Engineers who know only one cloud

Your company runs on Azure but job posts ask for AWS too, or the other way round. Every topic is taught once and built on both clouds, so you learn the second platform by comparing it to the one you know.

What you learn in 100 days

20 units and 3 hands-on projects. Each cloud topic is taught as one concept, then built as the same lab on AWS and on Azure.

Stage 1: The DevOps Toolkit

1

DevOps Essentials

▼
  • DevOps culture, principles and the roles in a DevOps team
  • From SDLC to the DevOps lifecycle
  • Continuous Integration, Continuous Delivery and Continuous Deployment
  • The DevOps tools landscape
2

Linux and Windows Administration

▼
  • Linux architecture, file system and directory layout
  • Everyday commands, permissions, users and groups
  • Packages, processes and services
  • Networking commands, SSH and remote access
  • Windows Server and PowerShell essentials
3

Shell Scripting and Automation

▼
  • Variables, user input, conditions, loops and functions
  • grep, awk and sed for text processing
  • Scheduling with cron
  • Real scripts: backups, log cleanup and health checks
4

Version Control with Git

▼
  • Repositories, commits, branches, merging and rebasing
  • Merge conflicts, tags, stash and branching strategies
  • GitHub pull requests and GitLab merge requests
  • Pipelines with GitHub Actions and GitLab CI/CD
  • The complete build-to-deploy cycle with Git
5

Containers with Docker

▼
  • Docker architecture and containers vs virtual machines
  • Images, containers, Dockerfiles and multi-stage builds
  • Volumes, networking and Docker Compose
  • Docker Hub and private registries
6

Orchestration with Kubernetes

▼
  • Control plane and worker node architecture
  • Pods, Deployments, Services, ConfigMaps and Secrets
  • Persistent Volumes, Ingress and Namespaces
  • Scaling, rolling updates, rollbacks and Helm basics
7

Web Servers, API Gateway and Code Quality

▼
  • Nginx as reverse proxy and load balancer, with SSL
  • Deploying Java web apps on Tomcat
  • Kong API Gateway: services, routes, plugins and rate limiting
  • SonarQube: code smells, bugs, vulnerabilities, quality gates and profiles
  • SonarQube checks inside CI/CD pipelines

Stage 2: Cloud Services on AWS and Azure

8

Getting Started on the Cloud

▼
  • Concept: Cloud models (IaaS, PaaS, SaaS), regions, availability zones, shared responsibility
  • Setup — AWS: Account, console, AWS CLI, CloudShell; Azure: Subscriptions, resource groups, portal, Azure CLI, Cloud Shell
  • Compare: How each cloud organizes and bills resources
9

Identity and Secrets

▼
  • Identity — AWS: IAM users, groups, roles, policies, MFA; Azure: Microsoft Entra ID, RBAC, managed identities
  • Secrets and keys — AWS: Secrets Manager, KMS; Azure: Azure Key Vault
10

Networking and DNS

▼
  • Private network — AWS: VPC, public and private subnets, VPC peering; Azure: VNet, subnets, route tables, VNet peering
  • Internet access — AWS: Internet Gateway, NAT Gateway; Azure: Public IPs and outbound access
  • Firewalls — AWS: Security Groups, NACLs; Azure: NSGs
  • DNS — AWS: Route 53; Azure: Azure DNS
11

Compute, Load Balancing and Scaling

▼
  • Virtual machines — AWS: EC2 instance types, AMIs, key pairs, user data; Azure: Virtual Machines, images
  • Disks and backups — AWS: EBS volumes and snapshots; Azure: Managed disks and snapshots
  • Load balancing — AWS: Application and Network Load Balancers, target groups; Azure: Azure Load Balancer, Application Gateway
  • Auto scaling — AWS: Auto Scaling groups, launch templates; Azure: VM Scale Sets
12

Storage and Databases

▼
  • Object storage — AWS: S3 buckets, storage classes, versioning, lifecycle, static hosting; Azure: Storage Accounts, blob containers, access tiers, file shares
  • Databases — AWS: RDS, DynamoDB; Azure: Azure SQL Database, Cosmos DB
13

Serverless and App Hosting

▼
  • Functions — AWS: Lambda with triggers; Azure: Azure Functions with triggers and bindings
  • Messaging — AWS: SNS, SQS
  • Web hosting — Azure: Azure App Service and deployment slots
14

Containers on the Cloud

▼
  • Registry — AWS: ECR; Azure: ACR
  • Serverless containers — AWS: ECS with Fargate; Azure: ACI
  • Managed Kubernetes — AWS: EKS; Azure: AKS
15

Monitoring and Auditing

▼
  • Metrics and logs — AWS: CloudWatch metrics, logs, dashboards, alarms; Azure: Azure Monitor, Log Analytics, Application Insights
  • Audit trail — AWS: CloudTrail; Azure: Activity Log
16

CI/CD Pipelines

▼
  • Concept: Build, test, release and approval stages
  • Native tools — AWS: CodeBuild, CodeDeploy, CodePipeline; Azure: Azure DevOps: Repos, YAML Pipelines, agents, service connections, environments, approvals
  • Common tools: GitHub Actions and GitLab CI deploying to both clouds

Stage 3: Automation, Monitoring and AI

17

Infrastructure as Code with Terraform

▼
  • How Infrastructure as Code works
  • AWS and AzureRM providers in one project
  • Resources, variables, outputs and data sources
  • Remote state on S3 and Azure Storage
  • Reusable multi-cloud modules and workspaces
  • Running Terraform from GitHub Actions, GitLab CI and Azure DevOps
18

Observability with Prometheus and Grafana

▼
  • Prometheus architecture, exporters and PromQL
  • Alertmanager and alert rules
  • One Grafana dashboard for EKS, AKS and cloud VMs
19

Multi-Cloud Design and Cost

▼
  • AWS and Azure service mapping cheat sheet
  • Picking the right cloud for each workload
  • Comparing costs, setting budgets and cost alerts on both clouds
  • Security best practices across both clouds
20

AI in Daily DevOps Work

▼
  • Basics of AI-Ops, Gen AI and prompt engineering
  • Writing scripts, Dockerfiles, pipelines and Terraform with Claude Sonnet
  • Fixing pipeline and Kubernetes errors with AI help
  • AI agents for everyday DevOps tasks

Projects

21

Hands-On Projects

▼
  • Same app on two clouds: Host the course website on EC2 behind an ALB with target groups, Route 53 and EBS snapshots on AWS, and on Azure VMs behind Application Gateway with Azure DNS, then compare the two setups
  • Containers and pipelines on both clouds: Containerize the app, push images to ECR and ACR, and deploy to EKS and AKS through GitHub Actions and Azure DevOps with SonarQube checks and secrets from Secrets Manager and Key Vault
  • Terraform-built multi-cloud platform: Provision the full infrastructure on AWS and Azure with Terraform, add a Lambda and an Azure Function, and monitor everything with CloudWatch, CloudTrail, Azure Monitor and Grafana

Certifications US employers ask for

US job posts for cloud and DevOps roles often list an AWS or Azure certification as preferred. The course topics overlap with the exams below, and the trainer helps you decide which one to take first based on the jobs you are applying for.

Both AWS and Microsoft let you take these exams online from home in the US, so you can book a slot on a weekend after the course.

  • AWS Certified Solutions Architect – Associate: a common first AWS certification
  • Microsoft Azure Administrator (AZ-104): the Azure counterpart for infrastructure roles
  • AWS Certified DevOps Engineer – Professional: for experienced engineers targeting senior roles
  • Azure DevOps Engineer Expert (AZ-400): pipelines, release management and monitoring on Azure

Multi Cloud DevOps roles and pay in the USA

Approximate yearly salary ranges. Actual pay varies a lot by city, company and visa status.

ExperienceTypical roleApprox. salary
0–2 yearsCloud Support Engineer, Junior DevOps Engineer$70K–$95K
2–5 yearsDevOps Engineer, Platform Engineer$95K–$140K
5–8 yearsSenior DevOps Engineer, SRE$140K–$180K
8+ yearsCloud Architect, Principal Engineer$180K+

Large employers and consulting firms in Dallas, New Jersey, the Bay Area, Seattle, Atlanta and Chicago run workloads on more than one cloud. Engineers who can set up the same pipeline, Kubernetes cluster or Terraform module on AWS and Azure are useful on more projects.

How to join from the USA

Four steps. Most students go from first message to first class within a week.

1

Book a free demo

Fill the form or WhatsApp us. We schedule a demo class in your evening hours.

2

Talk to the trainer

Share your background and goals. The trainer tells you honestly if this course fits.

3

Pay the fee

$360 (₹30,000) by UPI or bank transfer to our Indian account. Family in India can pay for you.

4

Join the batch

You get the Zoom link, WhatsApp group and syllabus PDF before the first class.

Questions from US students

Classes run Monday to Friday, 6:30–8:30 AM India time. In the USA that is Sunday to Thursday evening: 9–11 PM Eastern, 8–10 PM Central, 7–9 PM Mountain and 6–8 PM Pacific during daylight saving time (March to November). From November to March, US clocks go back one hour, so classes are 8–10 PM Eastern and 5–7 PM Pacific.

The fee is $360 (₹30,000) for the full 100-day program. It covers live classes on AWS and Azure, the syllabus PDF, three hands-on projects and interview preparation. There are no extra charges for recordings or doubt sessions.

You pay by UPI or bank transfer to our Indian account. Most US students ask a family member in India to pay by UPI, or send an international bank transfer from their US bank. Message us on WhatsApp at +91 98855 43638 and we will share the account details and confirm your seat.

Every class is live with the trainer, and you can ask questions on the call. Each session is also recorded, so if you miss a class because of work you can watch it the next day and clear doubts with the trainer on WhatsApp.

Yes. Many OPT students need hands-on cloud and DevOps projects to show in interviews. You build three projects on both AWS and Azure, push the code to your GitHub and get help preparing your resume and answers for US-style technical interviews.

Yes, you create your own free-tier accounts on AWS and Azure during the first week. The trainer shows how to set budgets and alerts so you do not get unexpected bills while practising.

The course topics overlap with AWS Certified Solutions Architect – Associate, AWS DevOps Engineer – Professional, Microsoft Azure Administrator (AZ-104) and Azure DevOps Engineer Expert (AZ-400). The trainer helps you choose which exam to take first. Both AWS and Microsoft exams can be taken online from home in the USA.

We do not place candidates directly with US companies. We help you get interview-ready for the US market: resume and LinkedIn review, mock interviews in your evening hours, and project walkthroughs you can explain confidently. Direct job referrals are for India-based roles.

In India? See the Hyderabad batch. In the UK? See the UK batch.

Book a free demo in your evening

Multi Cloud DevOps · $360 · 100 days · Live online

WhatsApp +91 98855 43638

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