HIGH-DEMAND PROGRAM β€’ INSTRUCTOR-LED LIVE
AWS Mastery:
The Corporate Readiness
Blueprint
Built by Ex-AWS Cloud Engineers, this program transforms you into a job-ready, production-level AWS professional.
πŸ“… Live Cohort
⏳ 12-Week Program
πŸ’» Online
βœ” Live
βœ” Labs
βœ” Placement
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PC
Deepak & Pradeep Ex-AWS Specialists
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EX-AWS CLOUD SPECIALISTS

LEARN FROM THE INDUSTRY EXPERTS – EX AWS

ENTERPRISE IMPACT
500+
ENTERPRISE ARCHITECTURE DESIGNS
GLOBAL CLIENTS
100+
FORTUNE 100 ENTERPRISE CUSTOMERS HANDLED
MENTORSHIP
100+
AWS NEW JOINERS MENTORED & ONBOARDED
TALENT ACQUISITION
300+
INTERVIEWS CONDUCTED AT AWS HIRING DRIVES
KNOWLEDGE TRANSFER
50+
TECHNICAL SESSIONS TO ENTERPRISE CLIENTS
BOOT CAMPS & ESCALATIONS
50+
TECH BOOT CAMPS & WAR ROOM ESCALATIONS
πŸš€ THIS PROGRAM IS BUILT FOR

Every Stage of Your Cloud Journey

Whether you're just starting out or stuck in your career, this program is engineered to get you hired.

Students & Fresh Graduates

Campus anxiety

Certified but Job-Seeking

Exam pass, no hire

IT Professionals Upskilling

On-premise IT role

Career Changers

Stuck in current field

Complete Beginners

"What is AWS?"

Why Most AWS Learners
Never Land the Job

The cloud job market is booming. Yet thousands of learners remain unemployed β€” because they're being trained the wrong way.

  • Drowning in theory instead of real AWS practice
  • No structured learning path
  • Zero corporate readiness
  • Learning alone without mentorship

Drowning in Theory, Not Practice

Most courses focus on theory and exam prep, not practical skills. You memorize services but can't build real solutions. When asked to design actual architectures, you freeze.

No Clear Learning Path

Endless content from various sources leaves you confused. You spend more time choosing what to learn than actually learning. Knowledge becomes fragmented.

Zero Corporate Readiness

Technical knowledge alone isn't enough. You're missing training on resumes, interview skills, and soft skills needed in enterprise environments.

Learning Alone, Without Guidance

Self-paced learning leaves you isolated. No mentor, no peer group, no feedback. This leads many learners to abandon their cloud career goals.

Why Most AWS Learners
Never Land the Job

The cloud job market is booming. Yet thousands of learners remain unemployed β€” because they're being trained the wrong way.

  • Drowning in theory instead of real AWS practice
  • No structured learning path
  • Zero corporate readiness
  • Learning alone without mentorship

Drowning in Theory, Not Practice

Most courses focus on theory and exam prep, not practical skills. You memorize services but can't build real solutions. When asked to design actual architectures, you freeze.

No Clear Learning Path

Endless content from various sources leaves you confused. You spend more time choosing what to learn than actually learning. Knowledge becomes fragmented.

Zero Corporate Readiness

Technical knowledge alone isn't enough. You're missing training on resumes, interview skills, and soft skills needed in enterprise environments.

Learning Alone, Without Guidance

Self-paced learning leaves you isolated. No mentor, no peer group, no feedback. This leads many learners to abandon their cloud career goals.

We Solve the Problems
Other Courses Ignore

AWS Mastery: The Corporate Readiness Blueprint is built specifically to transform you from confused learner to hired cloud professional.

01

Trained by Ex-AWS Professionals

  • Your trainers didn't just study AWS β€” they worked inside it
  • Enterprise experience building infrastructure
  • Production issue troubleshooting at scale
  • Best practices from real AWS environments
02

Every Session is Hands-On

  • No passive watching β€” you build from day one
  • Live labs on real AWS environments
  • Deploy, configure, troubleshoot services
  • Practice scenarios from actual jobs
03

Structured for Job Outcomes

  • Reverse-engineered from hiring manager demands
  • Master skills employers actually seek
  • Resume language that passes ATS systems
  • Interview prep with AWS expert strategies
  • Build job-ready confidence immediately
04

Live Mentorship, Not Recordings

  • This isn't a course you click through alone
  • Live sessions with real-time interaction
  • 1-on-1 doubt resolution when stuck
  • Mentor guidance tracking your progress
  • Direct expert access throughout journey
05

Small Cohorts, Real Attention

  • Limited batch sizes ensure personalized focus
  • Every learner gets meaningful attention
  • Build relationships with cohort peers
  • Collaborative learning environment
  • Your questions matter and get answered
06

Real-World Architecture Scenarios

  • Practice production-grade architectures
  • Design solutions companies deploy
  • Work with enterprise requirements
  • Master complex service integrations
  • Build portfolio projects that impress
01

Trained by Ex-AWS Professionals

  • Your trainers didn't just study AWS β€” they worked inside it
  • Enterprise experience building infrastructure
  • Production issue troubleshooting at scale
  • Best practices from real AWS environments
02

Every Session is Hands-On

  • No passive watching β€” you build from day one
  • Live labs on real AWS environments
  • Deploy, configure, troubleshoot services
  • Practice scenarios from actual jobs
03

Structured for Job Outcomes

  • Reverse-engineered from hiring manager demands
  • Master skills employers actually seek
  • Resume language that passes ATS systems
  • Interview prep with AWS expert strategies
  • Build job-ready confidence immediately
04

Live Mentorship, Not Recordings

  • This isn't a course you click through alone
  • Live sessions with real-time interaction
  • 1-on-1 doubt resolution when stuck
  • Mentor guidance tracking your progress
  • Direct expert access throughout journey
05

Small Cohorts, Real Attention

  • Limited batch sizes ensure personalized focus
  • Every learner gets meaningful attention
  • Build relationships with cohort peers
  • Collaborative learning environment
  • Your questions matter and get answered
06

Real-World Architecture Scenarios

  • Practice production-grade architectures
  • Design solutions companies deploy
  • Work with enterprise requirements
  • Master complex service integrations
  • Build portfolio projects that impress
Is This For You?
We've designed pathways for every stage of your cloud journey.
πŸŽ“
Fresh Graduates
CS/IT graduates ready to launch their careers with hands-on, job-ready cloud skills.
πŸ’Ό
Working Professionals
Tech professionals looking to deepen their expertise, specialise in cloud, and move into senior roles.
πŸ”„
Career Switchers
Professionals from other domains ready to pivot into cloud computing with structured, mentor-backed guidance.
🌱
Complete Beginners
Starting from zero with a strong drive to learn we'll take you from fundamentals to job-ready confidence.

AWS Career Program β€” Full Syllabus

The AWS Career Program is a complete, end-to-end training path built for anyone serious about becoming a job-ready AWS professional. Across 12 structured modules, you will go from understanding cloud fundamentals to designing, securing, and automating production-grade architectures β€” the same way real engineering teams do it. Every module is hands-on: you will build real infrastructure, write real policies, and make real architectural decisions β€” not just watch slides. The program covers core compute, storage, networking, identity, databases, serverless, infrastructure as code, monitoring, and security hardening, all culminating in a full capstone where you design and defend a complete production system. Whether you are aiming for your first cloud role, preparing for AWS certification, or levelling up from a junior position, this program gives you the depth, context, and practical experience that actually gets you hired.

Course Pricing

Course Price at

₹29,900

+ 18% GST

Choose your batch

2 options
Weekday Batch Mon - Fri Β· Live sessions

Weekend Batch

Sat & Sun | Live sessions

Enroll Now
Course Curriculum

AWS Career Program β€” Full Syllabus

Live Course Β· Built by Ex-AWS Engineers
Download Brochure
Module 01 Β· Foundations Β· Week 1
Most people skip the foundation.
That's why they hit walls later.
Before any lab, any service, any line of CLI β€” you need to understand how AWS thinks. This module builds that mental model. Fast.
AWS Fundamentals Console + Billing Lab Beginner Friendly

Most beginners rush into launching EC2 without understanding AWS regions, availability zones, or why their bill is higher than expected. We start where production starts β€” with account hygiene, cost guardrails, and infrastructure geography β€” because getting this wrong costs money and creates security incidents on day one.

What you actually learn
Cloud mental model
  • Why cloud exists and what it replaces in a data centre
  • Regions, Availability Zones, and Edge Locations β€” how AWS delivers global resilience
  • Shared Responsibility Model β€” what AWS owns vs. what you own
  • AWS Support plans and when each tier matters
Account & billing setup
  • Free Tier mechanics β€” what's always free vs. 12-month free vs. trial
  • Setting up billing alerts before your first resource
  • AWS Pricing Calculator β€” estimating cost before you build
  • Tagging strategy to track costs from day one
Core services map
  • Compute, Storage, Networking, Security β€” how AWS organises its 200+ services
  • Which services appear in every real architecture (not just tutorials)
  • Console, CLI, and SDK β€” the three ways to control AWS
  • AWS documentation structure β€” how to find answers at work
Account security baseline
  • Root user lockdown β€” why you never use it again after setup
  • MFA on root and IAM users β€” the one control that prevents most breaches
  • AWS Organizations basics for multi-account setups
  • CloudTrail β€” every API call logged from day one
What makes this module different
Most courses
Skip billing entirely
You set cost guardrails before touching a single service β€” and understand every charge on your bill
Most courses
One region, one AZ, no explanation
You understand AWS global infrastructure deeply enough to design for resiliency from lesson one
Most courses
Jump straight to EC2
You build the mental map first β€” so every service you learn after this clicks faster and sticks longer
Hands-on lab Β· AWS account setup done right
You secure and configure your AWS account like a pro
No skipped steps. No mystery bills. A properly hardened account before lab two.
30 min Β· Guided
1
Create account β€” AWS Free Tier with verified email and payment method
2
Lock root β€” enable Virtual MFA on root user immediately
3
Create IAM admin β€” least-privilege admin group and daily-use IAM user
4
Set billing alarm β€” CloudWatch alert at $5 to catch any surprise spend
5
Enable CloudTrail β€” turn on audit logging for the entire account
6
Explore console β€” navigate 5 core service pages and read your first API log
What you walk away with
A secure, production-ready AWS account
MFA on, billing alerts live, CloudTrail enabled β€” before any lab
AWS infrastructure geography
You can explain Regions, AZs, and Edge Locations in any interview
Cost clarity from day one
You understand the Free Tier deeply enough to never get surprise-billed
The AWS mindset
You understand the shared responsibility model β€” and where your obligation starts
Reverse-engineering the foundations
Troubleshooting mindset
Most courses teach you what things are. Here you also learn to work backwards β€” starting from a broken or unexpected outcome and tracing it back to the foundational concept that explains it. This is what makes knowledge stick.
When billing surprises you
Start from the charge, not the service. Trace the cost back through usage, region, and resource type β€” this forces you to deeply understand how AWS pricing actually works.
When the console confuses you
Instead of clicking until something works, ask: which layer owns this β€” AWS or me? The Shared Responsibility Model becomes real when you apply it to figure out who controls what's broken.
When a region behaves differently
If a service works in one region but not another, you're learning geography and service availability the hard way β€” which is the way it actually lands in memory.
When CloudTrail shows an unexpected call
An unknown API event in your trail is a perfect reverse-engineering puzzle. Who called it, from where, at what time β€” understanding the log structure starts with reading the anomaly.
Career edge β€” what this gets you in interviews
Cloud Support AssociateJunior Cloud EngineerIT Ops moving to Cloud
Interviewers routinely ask "what's the difference between a Region and an AZ?" β€” this module makes that a gimme
Understanding the Shared Responsibility Model is a baseline expectation in every cloud security and compliance interview
Engineers who can explain AWS billing mechanics are rare β€” and immediately trusted in cost-conscious teams
Module 02 Β· Core Infrastructure Β· Weeks 2–3
Clicking "Launch Instance" is easy.
Understanding what you just launched is the job.
EC2 is the backbone of most real AWS architectures. This module teaches how engineers actually use it β€” from instance selection logic to 3-tier production deployment.
EC2 Deep Dive Linux + Windows Labs 3-Tier Architecture Lab

The most expensive EC2 mistakes aren't technical β€” they're about picking the wrong instance family, ignoring the Nitro hypervisor's capabilities, or not knowing when Spot saves you 80% vs. when it'll destroy your workload. We teach the decision framework AWS engineers use, not just the click-through.

What you actually learn
Instance selection mastery
  • Instance family taxonomy (t, m, c, r, x, i) β€” what each is optimised for
  • Xen vs Nitro hypervisor β€” why Nitro matters for performance and security
  • Naming convention decoded: what c6i.2xlarge actually tells you
  • Tenancy models: shared, dedicated instance, dedicated host β€” licensing and compliance implications
AMIs, EBS & backup
  • AMI internals β€” what's in a machine image and how to build your own
  • EBS volume types and IOPS β€” choosing gp3 vs io2 with numbers
  • Snapshot strategies and Data Lifecycle Manager for automated backup
  • EC2 migration using AMI export β€” cross-region and cross-account patterns
Operations & metadata
  • Instance Metadata Service (IMDSv2) β€” how apps access their own identity securely
  • User Data scripts β€” automating bootstrap configuration at launch
  • AWS CLI for EC2 β€” describe-instances, start/stop/terminate from command line
  • Instance pricing: On-Demand, Reserved, Spot, Savings Plans β€” cost optimisation strategies
Resilience & performance
  • EC2 placement groups β€” when to cluster vs. spread vs. partition
  • Scheduled and maintenance events β€” how AWS notifies and how you respond
  • EC2 performance optimisation β€” Enhanced Networking, ENA, and SR-IOV
  • Compliance with EC2 β€” dedicated hosts for BYOL and regulatory workloads
What makes this module different
Most courses
Launch t2.micro, done
You learn the full instance taxonomy and make cost-justified choices for real workloads β€” with numbers
Most courses
Skip hypervisor entirely
You understand how Nitro changes EC2 performance, security, and what instance types it unlocks
Most courses
One basic Linux lab
You deploy a full 3-tier architecture on both Linux and Windows β€” the way it runs in production
Hands-on lab Β· 3-Tier architecture on EC2
You build a real production-grade 3-tier architecture
Web tier, app tier, database tier β€” deployed on Linux and Windows EC2 instances with networking fundamentals applied.
75 min Β· Advanced Guided
1
Launch web tier β€” t3.micro with NGINX, User Data bootstrap, Elastic IP, and security group configuration
2
Launch app tier β€” private subnet EC2, security groups with tier isolation and least-privilege rules
3
Configure Windows EC2 β€” RDP access, IIS setup, instance store vs EBS comparison
4
Attach & resize EBS β€” add gp3 data volume, mount, write data, snapshot it
5
Simulate failure β€” terminate web tier, restore from custom AMI to validate backup strategy
6
Cost analysis β€” compare On-Demand vs 1-year Reserved pricing for your architecture using CLI
What you walk away with
Confident instance selection
You justify every EC2 choice with performance and cost math, not guesswork
EBS fluency
You understand every volume type, can size IOPS correctly, and automate snapshots
3-tier architecture experience
You've built the architecture pattern used in most enterprise production systems
Recovery confidence
You've simulated a failure and restored from AMI β€” a task most developers have never done
Reading EC2 failures backwards
Troubleshooting mindset
The real test of EC2 knowledge isn't launching an instance β€” it's diagnosing one that won't start, won't respond, or costs twice what it should. These scenarios train you to reason backwards from symptoms to cause.
When SSH times out
Work backwards through the network stack: security group inbound rule β†’ subnet route table β†’ Internet Gateway attachment β†’ Elastic IP. Each layer you check reinforces how networking and compute connect.
When an instance won't start
Trace back through instance type availability, EBS volume limits, and AMI compatibility. The error message is the starting point, not the answer β€” following it to the root cause is the skill.
When costs are higher than expected
Start from the bill line item, trace back to the instance family and pricing model chosen. This backward walk solidifies the On-Demand vs Reserved vs Spot decision logic in a way a tutorial never does.
When User Data doesn't run
If your bootstrap script silently fails, reading the EC2 system log teaches you exactly how User Data is executed β€” timing, permissions, and failure modes you'd never encounter in a working demo.
Career edge β€” what this gets you in interviews
Cloud Support EngineerJunior DevOps / SRESolutions ArchitectFinOps Analyst
EC2 instance selection is a standard interview question for SA roles β€” you'll answer it with IOPS math, not gut feel
3-tier architecture knowledge is a baseline expectation in mid-level cloud engineering β€” you'll have built it hands-on
Being able to reduce compute costs 50–70% with Reserved or Spot is a valued skill that separates junior from mid-level engineers
Module 03 Β· Storage Β· Weeks 3–4
Storage is where teams waste money
and lose data they didn't back up.
EBS and S3 solve completely different problems. This module teaches you to choose the right storage type, configure it correctly, and never make the mistake of putting block storage where object storage belongs.
EBS + S3 Deep Dive CLI-based S3 Lab Lifecycle + Cost Optimisation

Storage mistakes are silent and expensive. Companies overpay on EBS volumes they could downgrade, keep data in S3 Standard when Glacier would cost 95% less, and skip versioning until a deletion incident. This module teaches the decision trees that AWS architects use β€” not a surface-level tour of the console.

What you actually learn
EBS fundamentals
  • Volume types (gp2, gp3, io1, io2, st1, sc1) β€” IOPS and throughput math for real workloads
  • EBS setup for Windows EC2 β€” attaching, formatting, and mounting volumes via Disk Manager
  • Snapshot policies with Data Lifecycle Manager β€” automating backup schedules
  • EBS encryption at rest β€” KMS keys, CMKs, and compliance requirements
S3 concepts & storage classes
  • Storage classes β€” Standard, IA, One-Zone-IA, Glacier, Intelligent-Tiering decision matrix
  • Bucket policies vs ACLs vs Object Ownership β€” which controls what and why ACLs are deprecated
  • Versioning β€” how it works, when to enable, and how to recover from accidental deletes
  • S3 Object Lock and Glacier Vault Lock for compliance and WORM requirements
Lifecycle & permissions
  • Lifecycle rules β€” automated transitions between storage classes with real cost modelling
  • Bucket policies β€” writing JSON policies for cross-account access and public hosting
  • S3 Transfer Acceleration β€” when it makes sense and how to measure the gain
  • Pre-signed URLs β€” time-limited secure access without exposing credentials
CLI & operations
  • AWS CLI S3 commands: cp, sync, mv, presign β€” used in real DevOps workflows
  • Multipart upload for large objects β€” why it matters and when it triggers automatically
  • CLI-based bucket creation, policy attachment, and versioning configuration
  • S3 Storage Lens β€” visualising spend and usage across buckets and accounts
What makes this module different
Most courses
"S3 has storage classes" β€” no math
You model the actual cost difference between Standard and Glacier for real access patterns
Most courses
Enable versioning, done
You understand how to recover from accidental deletes, and why versioning without lifecycle rules increases cost
Most courses
Console-only S3 demo
You use the CLI to automate S3 operations the way developers and DevOps engineers do in real pipelines
Hands-on lab Β· S3 setup, permissions, and CLI operations
You build a secured, versioned S3 bucket and automate its lifecycle
Console + CLI. You'll touch every major S3 config used in production, plus EBS setup on Windows.
50 min Β· Guided
1
Create bucket β€” block public access, versioning enabled, SSE-S3 encryption default
2
Bucket policy β€” write a JSON policy granting read to a specific IAM role only
3
CLI upload & sync β€” use aws s3 sync to mirror a local folder; verify object metadata
4
Versioning test β€” delete an object and restore it from a previous version
5
Lifecycle rule β€” auto-transition objects to S3-IA after 30 days, Glacier after 90
6
EBS Windows lab β€” attach a new gp3 volume to a Windows EC2, format in Disk Manager, and snapshot it
What you walk away with
Storage type decision skill
You can choose between EBS, S3, and storage classes with cost and access pattern reasoning
S3 CLI fluency
You operate S3 from the command line the way real DevOps engineers work every day
Lifecycle automation
You've built a rule that automatically reduces storage cost as data ages
Data recovery confidence
You've restored a deleted object and a Windows EBS volume β€” you'll never lose data to an accidental delete again
Diagnosing storage problems backwards
Troubleshooting mindset
Storage issues are silent until they're catastrophic. Learning to trace access errors, missing data, and runaway costs backwards through S3 and EBS logic cements the concepts far better than a clean demo ever could.
When S3 returns 403 Forbidden
Work backwards through the five access control layers: bucket policy β†’ ACL β†’ IAM policy β†’ S3 Block Public Access β†’ Object Ownership. Finding which layer is blocking teaches you the exact interaction between each control.
When an object disappears
Trace back through versioning state β€” was it a delete marker or a true permanent delete? Was versioning even enabled? This reverse walk makes the versioning model concrete and unforgettable.
When EBS performance degrades
Start from slow application reads and trace backwards through IOPS consumed, volume type limits, and burst credit balance. The IOPS maths becomes real when it explains a real slowdown.
When storage costs spike unexpectedly
Trace the bill back through storage class transitions and lifecycle rule gaps. Understanding why Glacier retrieval costs appeared teaches you the nuances of tiered pricing far faster than any lecture.
Career edge β€” what this gets you in interviews
Cloud EngineerData EngineerDevOps EngineerFinOps Analyst
S3 storage class selection and lifecycle policies are common in both Solutions Architect and Data Engineering interviews
Pre-signed URLs and bucket policies appear regularly in backend and API security discussions β€” you'll have built both
Cost optimisation through storage tiering is a real job skill that almost no course teaches with actual numbers
Module 04 Β· Networking Β· Weeks 4–5
VPC is the foundation of every secure AWS architecture.
Most engineers never learn it properly.
Every production AWS workload lives inside a VPC. If you don't understand subnets, routing, and network security from first principles β€” you're building on a shaky foundation. This module fixes that.
VPC + Route 53 Network Design Lab DNS + Routing Policies

VPC is the number one topic where engineers make security errors. Opening 0.0.0.0/0 because "it works", confusing Security Groups with NACLs, or not knowing why a NAT Gateway is needed β€” these are real production incidents. We teach VPC the way a network engineer would, applied to AWS.

What you actually learn
VPC fundamentals
  • CIDR block planning β€” how to size a VPC so you don't run out of IPs at scale
  • Public vs private subnets β€” the security principle behind the separation
  • Internet Gateway vs NAT Gateway β€” when each is needed and what happens without them
  • Route Table logic β€” how AWS decides which traffic goes where in a multi-tier network
Network security layers
  • Security Groups (stateful) vs NACLs (stateless) β€” the distinction that trips most engineers
  • Inbound and outbound rules β€” designing least-privilege network policies
  • VPC Flow Logs β€” diagnosing connectivity issues with network traffic data
  • VPC Peering and PrivateLink β€” connecting services without internet exposure
Route 53 & DNS
  • DNS fundamentals β€” record types (A, CNAME, MX, Alias) and TTL behaviour
  • Hosted zones β€” public vs private and when you need both
  • Routing policies β€” Simple, Weighted, Latency, Failover, Geolocation with real use cases
  • Health checks integrated with failover routing for automated DR cutover
Multi-AZ network design
  • Designing subnets across 2–3 AZs for high availability
  • NAT Gateway per-AZ vs. shared β€” cost vs. resilience trade-off
  • Network topology patterns used in production: hub-spoke, flat VPC, segmented
  • Transit Gateway basics β€” connecting multiple VPCs at scale
What makes this module different
Most courses
Default VPC, no explanation
You design a custom VPC from scratch with proper CIDR planning, subnet tiers, and routing logic
Most courses
Security Groups = firewall, done
You know the difference between stateful SGs and stateless NACLs β€” and use both correctly to layer security
Most courses
Route 53 = DNS, one example
You configure weighted, latency-based, and failover routing β€” with health checks that trigger automatic cutover
Hands-on lab Β· Production VPC design
You design and build a multi-AZ, multi-tier VPC
Public and private subnets, NAT Gateway, route tables, SGs, NACLs β€” the full production network stack.
60 min Β· Guided
1
Design CIDR β€” plan a /16 VPC with /24 subnets across 2 AZs (public + private)
2
Internet Gateway β€” attach IGW, update public subnet route table for internet connectivity
3
NAT Gateway β€” provision in public subnet, route private subnet internet traffic through it
4
Security Groups β€” web tier (port 80/443), app tier (port 8080 from web SG only)
5
VPC Flow Logs β€” enable and read traffic logs to diagnose a blocked connection
6
Route 53 failover β€” set up health-checked DNS that auto-cuts over to a backup endpoint
What you walk away with
VPC design confidence
You can build a multi-AZ VPC from scratch β€” the way production environments are built
Network security fluency
You apply the right controls β€” Security Groups or NACLs β€” at the right layer for every scenario
DNS architecture skill
You configure Route 53 routing policies that control how traffic reaches your application globally
Connectivity troubleshooting
You use VPC Flow Logs to diagnose network issues β€” a core SRE and DevOps skill
Tracing network failures to their root
Troubleshooting mindset
Network failures in AWS are almost always silent β€” a packet drops and nothing tells you why. Learning to read the evidence backwards, from VPC Flow Logs to route tables to security rules, is what makes network knowledge operational.
When a private instance can't reach the internet
Trace backwards: is the NAT Gateway in a public subnet? Does the private route table point to it? Is the Internet Gateway attached to the VPC? Each hop you check maps directly to a concept from the module.
When VPC Flow Logs show REJECTs
Start from the REJECT record β€” source IP, destination port, protocol β€” and work backwards to identify whether a Security Group or NACL is blocking the traffic, and why the rule that's blocking exists.
When DNS resolution fails inside a VPC
Trace back through Route 53 resolver configuration, private hosted zone associations, and VPC DNS settings. Debugging DNS failure teaches you the difference between public and private zones at a level no tutorial achieves.
When failover routing doesn't cut over
Work backwards from the health check β€” is it targeting the right endpoint? Is the threshold right? TTL too high? Diagnosing a stuck failover makes Route 53 routing policy logic click permanently.
Career edge β€” what this gets you in interviews
Network EngineerCloud ArchitectSRE / DevOpsSecurity Engineer
VPC design β€” subnets, routing, NACLs vs SGs β€” is one of the most tested topics in AWS Solutions Architect interviews
Route 53 routing policy questions (weighted, failover, latency) appear in almost every cloud architect screening
The ability to read VPC Flow Logs and troubleshoot connectivity is a hands-on skill interviewers ask for in SRE and DevOps roles
Module 05 Β· Security Β· Week 5
Every AWS breach starts somewhere.
Most start with a misconfigured IAM policy.
IAM is not a feature β€” it's the security foundation of everything you build on AWS. This module teaches you to write policies, design role hierarchies, and apply least privilege the way AWS security teams do.
IAM Deep Dive Policy Writing Lab Cross-Account Roles

Attaching AdministratorAccess to everything "because it works" is one of the most dangerous habits in cloud. Real IAM is about writing precise JSON policies, understanding the evaluation logic, and knowing when a Role beats a User. We teach IAM the way an AWS security engineer would audit your account.

What you actually learn
IAM fundamentals
  • Users, Groups, and Roles β€” when to use each, and why Roles beat long-lived credentials
  • IAM identity-based vs resource-based policies β€” how both interact in a single API call
  • Service Control Policies (SCPs) in AWS Organizations β€” setting guardrails across accounts
  • Permission boundaries β€” limiting what an IAM entity can do even with broad policies
Policies & permissions
  • JSON policy structure β€” Effect, Action, Resource, Condition β€” written from scratch
  • AWS managed vs customer managed policies β€” trade-offs in maintainability and precision
  • IAM policy evaluation logic β€” DENY always wins, and how to trace a permission error
  • Condition keys β€” IP restrictions, MFA requirements, and tag-based access controls
Roles in practice
  • EC2 instance profiles β€” how applications get AWS credentials without hardcoding keys
  • Cross-account role assumption β€” the pattern used in enterprise multi-account setups
  • Lambda execution roles β€” least-privilege for serverless functions
  • AssumeRole with STS β€” temporary credentials and how they expire
Security best practices
  • IAM Access Analyzer β€” automated detection of overly permissive policies
  • Credential Report and Access Advisor β€” finding unused permissions to remove
  • MFA enforcement with policy conditions β€” requiring strong auth for sensitive actions
  • AWS Security Hub integration β€” continuous IAM posture monitoring at scale
What makes this module different
Most courses
Create user, attach admin policy
You write custom least-privilege policies from scratch and understand exactly what each statement permits
Most courses
IAM Roles briefly mentioned
You configure EC2 instance profiles, cross-account roles, and STS token flows β€” the way enterprise AWS is built
Most courses
No mention of policy evaluation
You can trace any AccessDenied error to its root cause using the policy evaluation logic and Policy Simulator
Hands-on lab Β· Policy writing and role assumption
You write, test, and debug real IAM policies
Custom policies, role assumption, and the IAM Policy Simulator β€” tools used in security audits every day.
45 min Β· Guided
1
Write S3 read-only policy β€” JSON from scratch, specific bucket and prefix, no wildcards
2
Attach condition key β€” restrict access to requests originating from your VPC only
3
Create EC2 instance profile β€” role with S3 read policy, attach to EC2, verify access via CLI
4
Test policy simulator β€” validate Allow/Deny before deploying to production
5
Cross-account role β€” create a role in Account A, assume it from Account B using STS
6
Access Analyzer β€” run a finding on your account and remediate an overly permissive policy
What you walk away with
Custom policy authoring
You write precise IAM policies from scratch β€” not just attaching managed policies and hoping
Role architecture fluency
You configure instance profiles, cross-account roles, and STS flows used in real enterprise setups
Security audit skill
You use Access Analyzer and Credential Reports to find and fix over-permissive IAM configurations
AccessDenied debugging
You trace any permission error to its root cause using the IAM Policy Simulator and evaluation logic
Decoding permission errors backwards
Troubleshooting mindset
An AccessDenied error is not an obstacle β€” it's a map. Learning to read the IAM evaluation chain in reverse, from the error back to the policy that caused it, is how IAM knowledge becomes a real skill rather than memorised theory.
When AccessDenied appears on an API call
Trace backwards through the evaluation logic: was it an explicit Deny (SCP, resource policy, or identity policy)? Or an implicit Deny from a missing Allow?
When an EC2 instance can't access S3
Start from the 403 and work backwards: is there an instance profile? Does the role have the right policy? Is there a resource-based bucket policy overriding it?
When cross-account role assumption fails
Trace back through the trust policy, the AssumeRole permission, and the STS service endpoint.
When Access Analyzer flags a finding
Start from the finding and work backwards to understand which policy statement created the exposure.
Career edge β€” what this gets you in interviews
Cloud Security EngineerDevOps EngineerSolutions ArchitectSysOps Engineer
IAM policy evaluation β€” DENY precedence, condition keys, resource-based policies β€” is tested in nearly every cloud security interview
Cross-account role assumption is a question in almost every enterprise AWS architect panel β€” you'll have done it in the lab
The ability to audit and remediate over-permissive IAM is a key ask for any cloud security or compliance role
Module 06 Β· Resilience Β· Week 6
Any system can handle steady traffic.
Production systems handle spikes without falling over.
Load balancing and auto scaling are the two mechanisms that turn a single EC2 instance into a scalable, self-healing system. This module teaches you to build both β€” correctly, with real failure simulations.
ELB + Auto Scaling HA Architecture Lab Scaling Policy Design

Teams pay for over-provisioned EC2 instances because they don't trust their Auto Scaling to work. Or they misconfigure health checks so the load balancer keeps sending traffic to unhealthy instances. We teach the failure modes first β€” so your scaling is reliable when it matters, not just in a demo.

What you actually learn
Load balancer types
  • ALB vs NLB vs CLB β€” layer 4 vs layer 7 and which workload demands which type
  • Target groups β€” instance targets, IP targets, Lambda targets, and weighting
  • Listener rules β€” path-based and host-based routing for microservices architectures
  • ALB access logs and connection draining β€” graceful shutdown without dropped requests
Traffic distribution & health checks
  • ELB health check configuration β€” interval, threshold, timeout, and path selection
  • EC2 status checks vs ELB health checks β€” the two-layer system and when each triggers action
  • Unhealthy host detection β€” how the ALB removes and re-adds instances automatically
  • Stickiness (session affinity) β€” when it helps and when it breaks your scaling
Auto Scaling Groups
  • Launch Templates vs Launch Configurations β€” why LTs are the current standard
  • Min, max, desired capacity β€” the triangle of Auto Scaling design decisions
  • Scaling policies: Target Tracking, Step Scaling, Scheduled β€” when each applies
  • Warm pools and predictive scaling β€” advanced patterns for latency-sensitive workloads
High availability & fault tolerance
  • Multi-AZ ASG β€” distributing instances so no single AZ outage takes you down
  • Instance refresh β€” rolling updates to EC2 instances without downtime
  • Termination policies β€” controlling which instances get terminated first during scale-in
  • Lifecycle hooks β€” running scripts before an instance is launched or terminated
What makes this module different
Most courses
Create an ALB, done
You configure listener rules, target group weights, and path-based routing β€” like a microservices architecture requires
Most courses
Set a scaling policy with CPU alarm
You choose between Target Tracking, Step, and Scheduled scaling based on actual workload characteristics
Most courses
No failure scenario coverage
You simulate an AZ failure and watch Auto Scaling replace instances in surviving AZs β€” live in the lab
Hands-on lab Β· Self-healing, multi-AZ architecture
You build a system that heals itself when instances fail
Real ALB, real ASG, real failure simulation β€” and you watch it recover automatically.
60 min Β· Guided
1
Create Launch Template β€” AMI, instance type, security group, user data for web server bootstrap
2
Configure ASG β€” min:2, max:6, desired:2, spanning 2 AZs with proper subnet selection
3
Attach ALB β€” target group with HTTP health check on /health endpoint
4
Set scaling policy β€” Target Tracking on ALBRequestCountPerTarget at 1000 req/min
5
Simulate failure β€” terminate an EC2 instance and watch ASG replace it automatically
6
Load test β€” run a stress test with Apache Bench and watch the ASG scale out in real time
What you walk away with
Load balancer configuration skill
You configure ALBs with listener rules, health checks, and target groups for production traffic
Auto Scaling design fluency
You choose the right scaling policy for any workload pattern and configure it from scratch
Failure simulation experience
You've killed an instance and watched the system recover β€” most engineers haven't done this until production forces them to
HA architecture reasoning
You understand the trade-offs between cost and resilience in every multi-AZ design decision
Working backwards from scaling failures
Troubleshooting mindset
Auto Scaling that doesn't scale and load balancers that route to dead instances are two of the most confidence-shaking production experiences. Learning to trace these failures in reverse makes the underlying mechanics real and durable.
When an ALB keeps returning 502 errors
Trace backwards from the error code: is the target unhealthy? Is the health check path correct? Is there a timeout mismatch between ALB and the backend? Reading access logs backwards to the root cause is the skill here.
When Auto Scaling doesn't trigger
Start from the scaling activity log and work backwards: is the metric breaching the threshold? Is the cooldown period blocking? Is the desired capacity already at max? Each check reinforces how ASG decisions are made.
When new instances launch but stay unhealthy
Trace backwards from the health check failure through the application startup time, health check interval, and User Data script. This diagnostic walk teaches the lifecycle of an ASG-launched instance completely.
When traffic is uneven across instances
Start from the skewed request count in ALB metrics and trace backwards through stickiness settings, target group weights, and AZ balancing. Understanding why traffic is uneven teaches you how the ALB routing algorithm really works.
Career edge β€” what this gets you in interviews
Solutions ArchitectDevOps EngineerSREPlatform Engineer
ALB vs NLB selection and target group configuration are standard questions in Solutions Architect and DevOps interviews
Explaining Auto Scaling policy selection β€” Target Tracking vs Step β€” with workload reasoning sets you apart from candidates who just say "I use CPU alarms"
Having run a real failure simulation and watched ASG recover is a compelling interview story β€” almost no candidate at junior level has done this
Module 07 Β· Observability Β· Week 7
You can't fix what you can't see.
CloudWatch is how AWS engineers see everything.
Monitoring is not an afterthought β€” it's how you prove your system is working and how you find problems before they become incidents. This module teaches production observability from the AWS SRE playbook.
CloudWatch + CloudTrail + SNS Alarm + Dashboard Lab Audit & Governance

Most engineers only look at CloudWatch when something breaks. Real SRE teams build dashboards, set proactive alarms, and use Logs Insights to find anomalies before users notice. This module teaches you to build the observability layer that prevents incidents, not just responds to them.

What you actually learn
CloudWatch metrics & alarms
  • Standard vs custom metrics β€” when the built-in metrics aren't enough and how to push your own
  • Alarm states (OK, ALARM, INSUFFICIENT_DATA) and how transitions trigger actions
  • Composite alarms β€” combining conditions to reduce alert noise on-call teams hate
  • Metric math β€” calculating derived metrics (error rate %, p99 latency) directly in CloudWatch
CloudWatch Logs
  • Log Groups and Log Streams β€” organising application and system logs at scale
  • Logs Insights β€” querying logs with a filter, parse, stats, sort pipeline
  • Metric filters β€” converting log patterns into CloudWatch metrics for alerting
  • Log retention policies β€” controlling cost on long-running log storage
CloudTrail & governance
  • CloudTrail trails β€” management events vs data events and why data events cost more
  • Reading a CloudTrail event β€” who called what API, from where, at what time
  • Trail integration with S3 and CloudWatch Logs for long-term audit retention
  • Detecting anomalies β€” querying CloudTrail with Logs Insights for security events
SNS & notification pipelines
  • SNS topics β€” publishing to email, SMS, SQS, Lambda, HTTP endpoints from one publisher
  • Fan-out architecture β€” one event triggering multiple downstream consumers
  • CloudWatch β†’ SNS β†’ Slack pipeline β€” the real-world on-call notification setup
  • Message filtering β€” delivering only relevant events to each subscriber
What makes this module different
Most courses
Create a CPU alarm, done
You build composite alarms with metric math, reducing alert noise the way SRE teams do in production
Most courses
CloudTrail = "audit logs"
You query CloudTrail with Logs Insights to find security events β€” a real threat detection workflow
Most courses
SNS = "send notifications"
You build a fan-out notification pipeline connecting CloudWatch alarms to a Slack channel in real time
Hands-on lab Β· Production monitoring stack
You build an operational dashboard with real-time alerting
Metrics, logs, alarms, and notifications β€” the complete on-call monitoring stack for a real workload.
50 min Β· Guided
1
CloudWatch dashboard β€” EC2 CPU, Network In/Out, EBS read/write ops on one unified screen
2
Custom metric β€” push memory utilisation from EC2 (not built-in) using CloudWatch Agent
3
Composite alarm β€” alert only when CPU >80% AND memory >70% simultaneously
4
Logs Insights query β€” find the 10 slowest API calls in an application log group
5
SNS topic β€” connect CloudWatch alarm β†’ SNS β†’ email notification pipeline end-to-end
6
CloudTrail query β€” find who deleted an S3 object using Logs Insights on trail data
What you walk away with
Operational visibility
You can build a CloudWatch dashboard that shows the health of any workload at a glance
Proactive alerting
You design composite alarms that catch real problems β€” without waking on-call for noise
Logs Insights fluency
You write queries to find anomalies, errors, and slow operations in application logs
Audit trail mastery
You read and query CloudTrail events to answer "who did what and when" in any security investigation
Reading observability signals in reverse
Troubleshooting mindset
Monitoring tools are only useful when you know how to read the signals they produce under failure. Learning to work backwards from a metric spike, a missing alarm, or a silent alert teaches you what each component in the observability stack actually does.
When an alarm never fires despite real problems
Trace backwards from the alarm state: is the metric publishing? Is the evaluation period or threshold misconfigured? Is it stuck in INSUFFICIENT_DATA? Each failure mode teaches you how CloudWatch alarm evaluation actually works.
When Logs Insights returns no results
Work backwards from the empty result through the log group selection, time range, and query syntax. Debugging a query that should match teaches the log ingestion pipeline and query language far better than a working example.
When notifications stop arriving
Trace backwards through the SNS topic subscription, delivery status, and the CloudWatch alarm state that should trigger it. Following a broken notification pipeline makes the CloudWatch β†’ SNS architecture concrete.
When CloudTrail doesn't show an expected event
Start from the missing event and work backwards: is it a data event vs management event? Is the trail region-scoped? Is there a delivery delay? This diagnostic walk teaches the full CloudTrail architecture in minutes.
Career edge β€” what this gets you in interviews
SREDevOps EngineerCloud SupportSecurity Analyst
CloudWatch alarm design and Logs Insights querying are tested in every SRE and DevOps role interview β€” you'll have built both
The ability to read CloudTrail events and trace a security incident is a hard skill almost no junior candidate can demonstrate
Building a CloudWatch β†’ SNS notification pipeline is a standard expectation in cloud operations roles β€” you'll have done it in the lab
Module 08 Β· Migration Β· Week 8
Every company is moving to cloud.
Very few engineers know how to actually do it.
Migration strategy is one of the highest-value skills in cloud β€” and one of the least taught. This module teaches you the full migration lifecycle, from assessment to cutover, using real AWS migration tools.
Migration Strategy & Tools Linux + Windows Migration Labs 7Rs Framework

Most courses teach cloud-native but skip migration entirely. The reality is that billions of dollars of workloads still run on-premises, and companies pay serious money for engineers who can move them safely. We teach the strategy frameworks and the actual AWS tools β€” because real migration projects follow a process, not a tutorial.

What you actually learn
Migration strategies β€” the 7Rs
  • Rehost (Lift & Shift) β€” when speed beats optimisation and how to execute it at scale
  • Replatform β€” targeted changes that improve performance without full re-architecting
  • Refactor β€” what it actually means to re-architect for cloud-native patterns
  • Retire, Retain, Repurchase, Relocate β€” the four Rs most courses completely skip
Migration planning & assessment
  • AWS Migration Hub β€” tracking progress across multiple migration streams
  • AWS Application Discovery Service β€” automated inventory of on-premises servers
  • Migration Evaluator β€” business case builder for cloud ROI conversations
  • Wave planning β€” sequencing workloads to minimise risk and dependency conflicts
VM migration tools
  • AWS Application Migration Service (MGN) β€” agent-based continuous block replication
  • Launch Test Instances β€” validating migrated workloads before committing to cutover
  • Cutover process β€” the final DNS flip and how to roll back safely if needed
  • Post-migration validation β€” performance benchmarking and compliance confirmation
Best practices & tools
  • AWS Database Migration Service (DMS) β€” homogeneous and heterogeneous migrations
  • Change Data Capture (CDC) β€” continuous replication to minimise downtime during migrations
  • Schema Conversion Tool (SCT) β€” converting Oracle/SQL Server schemas to Aurora
  • Security and compliance checkpoints β€” IAM, encryption, and audit trail during migration
What makes this module different
Most courses
No migration content at all
You learn the full 7Rs framework and choose the right strategy for any workload β€” with reasoning, not guesswork
Most courses
Theory only, no tools
You use MGN and DMS β€” the actual AWS tools used in enterprise migration projects worth millions
Most courses
Linux only, no Windows
You migrate both Linux and Windows workloads β€” because enterprise environments run both
Hands-on lab Β· End-to-end server migration
You migrate a Linux and a Windows server to AWS
Agent installation, replication, test launch, cutover β€” the full MGN migration lifecycle for both platforms.
75 min Β· Advanced Guided
1
Install MGN agent β€” on source Linux server, verify replication initiation in the Migration console
2
Configure launch template β€” set target instance type, subnet, security group for the migrated server
3
Launch test instance β€” verify application functionality before committing to cutover
4
Repeat for Windows β€” install agent, validate RDP access, run application health check
5
Execute cutover β€” final launch, DNS update, verify zero-downtime transition
6
Post-migration audit β€” benchmark performance and confirm CloudTrail audit trail for compliance
What you walk away with
7Rs decision framework
You assess any workload and recommend the right migration strategy with business justification
MGN migration experience
You've completed a full lift-and-shift migration of both Linux and Windows servers to AWS
DMS database migration skill
You understand how to migrate databases using CDC replication with minimal downtime
Cutover process knowledge
You know how to execute a final cutover, update DNS, and roll back safely if something goes wrong
Career edge β€” what this gets you in interviews
Cloud Migration EngineerSolutions ArchitectIT ConsultantCloud Transformation Lead
Migration strategy (7Rs) is a question in almost every Solutions Architect Associate and Professional exam β€” and in nearly every enterprise cloud role interview
Engineers who have hands-on MGN experience are rare at the junior level β€” most learn it only when they're already on a migration project
The ability to discuss wave planning and cutover risk management positions you for cloud consultant and transformation lead roles, not just engineer roles
Module 09 Β· Operational Excellence Β· Week 9
Anyone can build on AWS.
The job is keeping it running when things break.
Troubleshooting is the skill that proves you understand AWS deeply β€” not just how to use it, but why it behaves the way it does under pressure. This module teaches the structured debugging approach ex-AWS support engineers use every day.
Troubleshooting Methodology Real Incident Scenarios Log Analysis + Performance

Most engineers learn troubleshooting the hard way β€” by being paged at 2am and clicking randomly until something works. There's a better way. AWS has a structured methodology for diagnosing every category of problem β€” connectivity, performance, permissions, configuration β€” and this module teaches it before you're in production under pressure.

What you actually learn
Troubleshooting methodology
  • The structured AWS debugging framework: isolate, reproduce, identify, remediate
  • Layer-by-layer approach β€” network, OS, application, AWS service, permissions
  • Using the AWS Console vs CLI for diagnosis β€” what each shows you the other doesn't
  • When to open an AWS Support case β€” and how to write one that gets results fast
Common issues & debugging
  • EC2 connectivity failures β€” SSH timeouts, security group mistakes, missing IGW
  • IAM AccessDenied errors β€” tracing through policy evaluation to the root cause
  • S3 403 Forbidden β€” the 5-layer access control model and where each error originates
  • ELB 5xx errors β€” target group health, backend timeouts, and connection draining issues
Monitoring & log analysis
  • CloudWatch Logs Insights β€” query patterns for common failure modes and error detection
  • VPC Flow Logs β€” reading ACCEPT/REJECT records to trace blocked connections precisely
  • ALB access logs β€” finding slow requests, 5xx errors, and problematic client patterns
  • EC2 system logs β€” diagnosing boot failures and OS-level errors without SSH access
Performance troubleshooting
  • CPU throttling β€” T-series credit exhaustion and how to detect it before it hits users
  • EBS IOPS starvation β€” reading volume metrics to identify the throughput bottleneck
  • Memory pressure β€” why CloudWatch doesn't show memory by default and how to fix that
  • Network throughput limits β€” understanding ENI bandwidth caps per instance type
What makes this module different
Most courses
No troubleshooting content at all
You finish with a repeatable debugging framework β€” not guessing, but systematically isolating every failure category
Most courses
Generic "check your logs" advice
You write real Logs Insights queries that surface the exact line of log data that explains the failure
Most courses
Scenarios created for tutorials
You debug real failure patterns pulled from the types of cases ex-AWS support engineers handled at enterprise scale
Hands-on lab Β· Incident diagnosis and resolution
You diagnose and fix 4 real AWS failure scenarios
No hints. No guided steps. You apply the methodology and work through each incident yourself.
60 min Β· Scenario-based
1
Connectivity failure β€” EC2 is unreachable via SSH; identify and fix the security group + route table issue
2
Access denied β€” S3 403 error from an EC2 instance; trace the IAM role, bucket policy, and ACL
3
ALB 502 errors β€” read access logs to identify the unhealthy target and misconfigured health check
4
Performance degradation β€” identify T-series CPU credit exhaustion using CloudWatch metrics and remediate
5
Log Insights query β€” write a query to find all ERROR-level events in the last hour from a specific source
6
Support case β€” draft a well-structured AWS Support case with reproduction steps, logs, and impact statement
What you walk away with
Structured debugging framework
You approach every AWS problem systematically β€” not by clicking randomly until something works
Log analysis fluency
You extract the exact evidence you need from CloudWatch Logs, VPC Flow Logs, and ALB access logs
Performance diagnosis skill
You identify CPU, memory, IOPS, and network bottlenecks using CloudWatch metrics before users feel them
Incident response confidence
You've diagnosed 4 real failure scenarios without guided steps β€” that's the skill you bring to any cloud team
Career edge β€” what this gets you in interviews
Cloud Support EngineerSREDevOps EngineerPlatform Engineer
"Walk me through how you'd troubleshoot a 502 error on an ALB" is a standard SRE and DevOps interview question β€” you'll answer it with specific log evidence and the IAM/SG/health check checklist
The ability to write CloudWatch Logs Insights queries for real failure patterns is a differentiator in technical screens at cloud-native companies
Having resolved real incident scenarios β€” not just built things that work β€” tells an interviewer you're ready for production on day one, not day ninety
INCLUDED WITH EVERY SESSION

What You Gain Beyond the Curriculum

Every session is loaded with practical value β€” real-world knowledge, insider expertise, and career-shaping insights woven directly into your learning journey.

β€’ INCLUDED

Interview Tips β€” As You Learn

Interview prep happens throughout the program, not at the end. Every time a topic comes up that hiring managers love to test, you get targeted tips right then β€” so you absorb interview-ready thinking as you go.

β€’ INCLUDED

Corporate Readiness Training

Understand how professional cloud teams operate β€” how decisions get made, how issues escalate, and how communication flows across organizations. You'll enter your first role knowing how things actually work.

β€’ INCLUDED

AWS Insider Tips

Gain the practical wisdom that only comes from years in the field β€” the cost traps to avoid, the architecture patterns that hold up under pressure, and the subtle decisions that separate production-grade solutions.

β€’ INCLUDED

Labs, Projects & Real-World Scenarios

Build what you learn through structured hands-on labs and projects grounded in real industry scenarios. By the time you're done, you won't just understand cloud concepts β€” you'll have the work to prove it.

CLOUD CAREER ROADMAP

Prepare for Roles at World-Class Tech
Organizations

Cloud expertise is the #1 most in-demand skill for the next decade. Our curriculum is designed to help you meet the engineering standards of top-tier global teams and high-growth startups.

Start your journey toward a career in High-Scale Cloud Engineering.

Meet Your Mentors

Learn from engineers who've built, broken, and fixed cloud systems at scale.
Not trainers β€” practitioners.

Enterprise Impact
500+
Enterprise Architecture Designs
Global Clients
100+
Fortune 100 Enterprise Customers
Mentorship
100+
AWS New Joiners Mentored
Talent Acquisition
300+
Interviews at AWS Hiring Drives
Knowledge Transfer
50+
Technical Sessions to Clients
Boot Camps
50+
Tech Boot Camps & War Rooms
Deepak Dhaker
Architects complex enterprise cloud solutions at scale. Specializes in robust system design, performance optimization, and cost efficiency β€” driving large-scale cloud initiatives end to end.
Pradeep Chauhan
Designs core compute solutions, complex network architectures, and large-scale AWS migrations. Specializes in building resilient, high-performance infrastructure for enterprise systems.
Verified by AWS
Certifications & SME Awards
AWS Badge AWS Badge AWS Badge AWS Badge AWS Badge AWS Badge AWS Badge AWS Badge AWS Badge AWS Badge AWS Badge AWS Badge AWS Badge AWS Badge
Enterprise Impact
500+ Architecture Designs
Combined across both mentors
Global Clients
Fortune 100 Accounts
100+ enterprise customers handled
Talent Acquisition
300+ Interviews Led
AWS hiring drives across India
Mentorship
100+ Engineers Onboarded
AWS new joiner programs
Knowledge Transfer
50+ Technical Sessions
Deep-dive enterprise workshops
Boot Camps
50+ War Rooms Run
Mission-critical escalations

Your Questions,Answered Honestly

We don't do vague promises. If you have a question that's not here, our team is happy to answer it on a call before you apply.

Apply for Program
Live sessions with real-time Q&A
Ex-AWS professionals as instructors
Production-grade hands-on labs
Yes. We've designed the curriculum to meet you where you are. Whether you're a fresh graduate or transitioning from another tech role, we start from fundamentals and build up to production-level skills. What matters is your commitment, not your starting point.
This program provides job assistance β€” including mock interviews and resume reviews β€” but we don't guarantee a job. No ethical program can. What we guarantee is that you'll be significantly more capable and confident than the majority of candidates.
Udemy, YouTube, and most instructor-led programs teach you what AWS services are β€” concepts, theory, and controlled demos. We teach you how to apply them under real production conditions. Our instructors have handled production escalations for Fortune 100 enterprises and have designed scalable, robust, and highly available systems as Ex-AWS Professionals. That depth simply cannot be replicated in recorded courses.
Fortune 100 Escalations
Ex-AWS Professional
Scalable Architecture Design
Highly Available Systems
Absolutely. We've had many certified candidates who kept getting rejected because they couldn't demonstrate hands-on skills in interviews. This program fills exactly that gap β€” from troubleshooting real production issues, diagnosing live system failures, and working through hands-on labs, to reviewing and understanding scalable architecture decisions and articulating your full thought process under interview pressure.
Certifications prove you can pass an exam. This program proves you can do the job.
Production Troubleshooting
Hands-On Labs
Scalable Architecture Review
Interview Readiness
All sessions are live and instructor-led. You get real-time interaction, the ability to ask questions, and immediate feedback. Recordings of all sessions are also provided so you can revisit them at your own pace β€” but the live experience is where the real learning happens.
You don't need to be an expert to join β€” you need to be driven. This program is engineered to take people from diverse starting points and forge them into job-ready cloud professionals. The curriculum is structured to challenge you progressively, so no one gets left behind and no one gets held back.
The starting point doesn't define the outcome. The work you put in does.