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Master Amazon Web Services from Global Infrastructure, IAM Least-Privilege Policies & STS Roles to S3 Storage Classes, CloudFront OAC, EC2/EBS, ALB, Multi-AZ VPC/NAT, RDS, DynamoDB, Lambda, API Gateway & SQS — with Python Boto3 programs, 244 Topic Mock Tests (10,440 MCQs), and Spoken Voice + MockAttempt AI Interviews at ₹5,999 + 18% GST.
Harpreet Singh Bedi
✓ Enrolled📍 Mohali • IT Ops → AWS SAA-C03 Architect
Enrolled: AWS Cloud Architect (SAA-C03) (AWSC)
📅 Weekend Sat–Sun (9–11 AM IST)
Mansi Parekh
✓ Enrolled📍 Surat • Backend Dev → VPC, EKS & IAM
Enrolled: AWS Cloud Architect (SAA-C03) (AWSC)
📅 Weekday Mon–Fri (8–9 AM IST)
Tushar Khandelwal
✓ Enrolled📍 Jaipur • SysAdmin → AWS Cloud & Terraform
Enrolled: AWS Cloud Architect (SAA-C03) (AWSC)
📅 Weekday Mon–Fri (7–8 PM IST)
AWSC • Cloud Computing & AWS Solutions Architecture
👨💻 Trainers: 100% Active Working IT Professionals
⏱️ Duration: 15–17 Weeks • Live + Hands-On Projects (210h Guided Mastery)
📅 Weekdays (Mon–Fri): 1 Hour / Day • 7:00 AM – 8:00 PM IST (choose any slot based on trainer availability)
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💻 LeetCode & HackerRank: Trainer problem-solving support (Python 3.12 (Boto3 SDK & AWS Lambda)).
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Click any module or topic below to expand its learning objectives, plain-language overview, real-world purpose, hands-on code, lab tasks, 50-MCQ mocks, MockAttempt AI interviews, and capstone project.
Module Learning & Hands-On Objectives
💡 Self-Explanatory Overview: In simple, everyday terms, AWS Cloud Computing Foundations — Shared Responsibility Model & Well-Architected Pillars teaches you how AWS applications how AWS replaces upfront CapEx data centers with elastic OpEx cloud primitives governed by the Shared Responsibility Model and the 6 Well-Architected Framework pillars. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply AWS Cloud Computing Foundations — Shared Responsibility Model & Well-Architected Pillars in real AWS systems — specifically: How AWS replaces upfront CapEx data centers with elastic OpEx cloud primitives governed by the Shared Responsibility Model and the 6 Well-Architected Framework pillars, so your code stays reliable, fast, and easy to maintain in production.
AWS tutorial provides basic and advanced concepts. Our AWS tutorial is designed for beginners and professionals. AWS stands for Amazon Web Services which uses distributed IT infrastructure to provide different IT resources on demand. Our AWS tutorial includes all the topics such as introduction, history of aws, global infrastructure, features of aws, IAM, Storage services, Database services, etc. What is Amazon AWS?...
AWS Cloud Computing Foundations — Shared Responsibility Model & Well-Architected Pillars — Practical Assignment
Implement a production-ready AWS Cloud & Solutions Architecture solution demonstrating AWS Cloud Computing Foundations — Shared Responsibility Model & Well-Architected Pillars using boto3.Session() +...
AWS Cloud Computing Foundations — Shared Responsibility Model & Well-Architected Pillars — Hands-On Lab Task
from botocore.config import Config
aws_cfg = Config(region_name='ap-south-1', connect_timeout=3, read_timeout=5, retries={'max_attempts': 4, 'mode': 'adaptive'})
matrix = {
'EC2': {'aws': 'Nitro Hypervisor', 'customer': 'Guest Linux Patching & SG'},
'S3': {'aws': '11-Nines Durability', 'customer': 'Bucket Policy & KMS Keys'},
}
for svc, owners in matrix.items():
print(f"{svc} [{aws_cfg.region_name}] -> Customer Owns: {owners['customer']}")
print(f"Retry Mode: {aws_cfg.retries['mode']} | Max Attempts: {...💡 Self-Explanatory Overview: In simple, everyday terms, AWS Global Infrastructure — Regions, Availability Zones, Local Zones & Edge Locations teaches you how AWS applications deep dive into geographically isolated AWS Regions, redundant Availability Zones linked via low-latency private fiber (< 2 ms), and global Edge PoPs. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply AWS Global Infrastructure — Regions, Availability Zones, Local Zones & Edge Locations in real AWS systems — specifically: Deep dive into geographically isolated AWS Regions, redundant Availability Zones linked via low-latency private fiber (< 2 ms), and global Edge PoPs, so your code stays reliable, fast, and easy to maintain in production.
AWS Global Infrastructure is a global network of data centers and cloud resources that offer security, reliability, and performance in delivering cloud services. It includes AWS Regions, Availability Zones (AZs), Local Zones, Edge Locations, Regional Edge Caches, and Wavelength Zones. Availability Zones are an integral component of the AWS infrastructure. They are located within AWS Regions and include a single or mu...
AWS Global Infrastructure — Regions, Availability Zones, Local Zones & Edge Locations — Practical Assignment
Implement a production-ready AWS Cloud & Solutions Architecture solution demonstrating AWS Global Infrastructure — Regions, Availability Zones, Local Zones & Edge Locations using ec2_client.describe_a...
AWS Global Infrastructure — Regions, Availability Zones, Local Zones & Edge Locations — Hands-On Lab Task
az_catalog = [
{'ZoneName': 'ap-south-1a', 'ZoneId': 'aps1-az1', 'State': 'available'},
{'ZoneName': 'ap-south-1b', 'ZoneId': 'aps1-az3', 'State': 'available'},
{'ZoneName': 'ap-south-1c', 'ZoneId': 'aps1-az2', 'State': 'available'},
]
active_ids = sorted(z['ZoneId'] for z in az_catalog if z['State'] == 'available')
is_ha_ready = len(active_ids) >= 3
print(f"Active AZ IDs: {', '.join(active_ids)}")
print(f"Multi-AZ Quorum Ready: {is_ha_ready}")Build a Python Boto3 architecture utility that audits workload placement across at least 3 Availability Zones in ap-south-1, maps Shared Responsibility controls per service tier, and flags single-AZ single points of failure.
Module Learning & Hands-On Objectives
💡 Self-Explanatory Overview: In simple, everyday terms, AWS IAM Architecture — Users, Groups, JSON Policies, Conditions & Explicit Deny Precedence teaches you how AWS applications how AWS IAM authenticates principals and evaluates identity-based, resource-based, and SCP JSON policy documents on every signed SigV4 API request. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply AWS IAM Architecture — Users, Groups, JSON Policies, Conditions & Explicit Deny Precedence in real AWS systems — specifically: How AWS IAM authenticates principals and evaluates identity-based, resource-based, and SCP JSON policy documents on every signed SigV4 API request, so your code stays reliable, fast, and easy to maintain in production.
A foundational AWS security service, AWS Identity and Access Management (IAM) enables you to securely manage access to your AWS resources. It manages access to your cloud environment and the actions authorized users and services can take, preventing unauthorized users and services from interacting with AWS resources. IAM allows you to manage users, groups, and roles, add permissions using policies, and give temporary...
AWS IAM Architecture — Users, Groups, JSON Policies, Conditions & Explicit Deny Precedence — Practical Assignment
Implement a production-ready AWS Cloud & Solutions Architecture solution demonstrating AWS IAM Architecture — Users, Groups, JSON Policies, Conditions & Explicit Deny Precedence using iam_client.simul...
AWS IAM Architecture — Users, Groups, JSON Policies, Conditions & Explicit Deny Precedence — Hands-On Lab Task
def evaluate_iam(statements, action):
allowed = False
for st in statements:
acts = st['Action'] if isinstance(st['Action'], list) else [st['Action']]
if action in acts or '*' in acts:
if st['Effect'] == 'Deny':
return 'EXPLICIT_DENY'
if st['Effect'] == 'Allow':
allowed = True
return 'ALLOW' if allowed else 'IMPLICIT_DENY'
policy = [{'Effect': 'Allow', 'Action': ['s3:GetObject', 's3:DeleteObject']}, {'Effect': 'Deny', 'Action': 's3:...💡 Self-Explanatory Overview: In simple, everyday terms, AWS IAM Roles & STS — Trust Policies, Instance Profiles, OIDC Federation & AssumeRole teaches you how AWS applications replacing static long-lived secrets with dynamic AWS Security Token Service (STS) ASIA temporary credentials for EC2, Lambda, GitHub OIDC, and cross-account access. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply AWS IAM Roles & STS — Trust Policies, Instance Profiles, OIDC Federation & AssumeRole in real AWS systems — specifically: Replacing static long-lived secrets with dynamic AWS Security Token Service (STS) ASIA temporary credentials for EC2, Lambda, GitHub OIDC, and cross-account access, so your code stays reliable, fast, and easy to maintain in production.
An AWS Identity and Access Management (IAM) role is an AWS identity that provides temporary access to AWS resources without using permanent credentials. It allows trusted users, applications, or AWS services to securely access AWS resources. AWS IAM includes Users, Groups, and Roles. Unlike users and groups, roles are assumed only when needed. Administrators can attach IAM policies to roles to define their permission...
AWS IAM Roles & STS — Trust Policies, Instance Profiles, OIDC Federation & AssumeRole — Practical Assignment
Implement a production-ready AWS Cloud & Solutions Architecture solution demonstrating AWS IAM Roles & STS — Trust Policies, Instance Profiles, OIDC Federation & AssumeRole using sts_client.assume_rol...
AWS IAM Roles & STS — Trust Policies, Instance Profiles, OIDC Federation & AssumeRole — Hands-On Lab Task
import json
trust_policy = {
'Version': '2012-10-17',
'Statement': [{
'Effect': 'Allow',
'Principal': {'AWS': 'arn:aws:iam::210987654321:root'},
'Action': 'sts:AssumeRole',
'Condition': {'StringEquals': {'sts:ExternalId': 'mockattempt-sec-991'}},
}],
}
stmt = trust_policy['Statement'][0]
ext_id = stmt['Condition']['StringEquals']['sts:ExternalId']
print(f"Action: {stmt['Action']} | ExternalId Guard: {ext_id} | Valid JSON: {len(json.dumps(trust_policy)) > 100}")Create an IAM security auditor and STS credential helper in Python that flags wildcard Action/Resource grants, verifies MFA Condition blocks, and formats short-lived STS session credentials.
Module Learning & Hands-On Objectives
💡 Self-Explanatory Overview: In simple, everyday terms, Amazon S3 Internals — Flat Key-Object Namespace, Strong Consistency, Versioning & Presigned URLs teaches you how AWS applications how Amazon S3 delivers 99.999999999% (11 nines) durability across >= 3 AZs with strong read-after-write consistency, versioning, and presigned direct-to-S3 transfers. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply Amazon S3 Internals — Flat Key-Object Namespace, Strong Consistency, Versioning & Presigned URLs in real AWS systems — specifically: How Amazon S3 delivers 99.999999999% (11 nines) durability across >= 3 AZs with strong read-after-write consistency, versioning, and presigned direct-to-S3 transfers, so your code stays reliable, fast, and easy to maintain in production.
Amazon Simple Storage Service, commonly known as Amazon S3 or AWS S3, is a cloud-based object storage service provided by Amazon Web Services (AWS). It allows users and organizations to store, manage, and retrieve large amounts of data from anywhere through the internet. Amazon S3 is a crucial storage solution for modern applications, websites, data analytics, backups, disaster recovery, and content delivery, known f...
Amazon S3 Internals — Flat Key-Object Namespace, Strong Consistency, Versioning & Presigned URLs — Practical Assignment
Implement a production-ready AWS Cloud & Solutions Architecture solution demonstrating Amazon S3 Internals — Flat Key-Object Namespace, Strong Consistency, Versioning & Presigned URLs using s3_client....
Amazon S3 Internals — Flat Key-Object Namespace, Strong Consistency, Versioning & Presigned URLs — Hands-On Lab Task
import math
def plan_s3_upload(file_mb, part_mb=64):
if file_mb <= 100:
return {'mode': 'SINGLE_PUT', 'parts': 1}
parts = math.ceil(file_mb / part_mb)
return {'mode': 'MULTIPART', 'parts': parts, 'part_mb': part_mb}
small = plan_s3_upload(45)
large = plan_s3_upload(650, part_mb=64)
print(f"45MB -> {small['mode']} ({small['parts']} part) | 650MB -> {large['mode']} ({large['parts']} parts)")💡 Self-Explanatory Overview: In simple, everyday terms, Amazon S3 Storage Classes — Standard, Intelligent-Tiering, Standard-IA, One Zone-IA & Glacier teaches you how AWS applications selecting the optimal S3 Storage Class by balancing per-GB storage rate, minimum billable object size (128 KB), minimum storage duration (30/90/180 days), and retrieval latency. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply Amazon S3 Storage Classes — Standard, Intelligent-Tiering, Standard-IA, One Zone-IA & Glacier in real AWS systems — specifically: Selecting the optimal S3 Storage Class by balancing per-GB storage rate, minimum billable object size (128 KB), minimum storage duration (30/90/180 days), and retrieval latency, so your code stays reliable, fast, and easy to maintain in production.
Amazon Simple Storage Service (Amazon S3) is an object storage service provided by Amazon Web Services (AWS). It is designed to store and retrieve large amounts of data from anywhere through the internet. Amazon S3 provides multiple storage classes, allowing users to choose a storage option according to their data access frequency, performance requirements, availability needs, and budget. Instead of storing all data...
Amazon S3 Storage Classes — Standard, Intelligent-Tiering, Standard-IA, One Zone-IA & Glacier — Practical Assignment
Implement a production-ready AWS Cloud & Solutions Architecture solution demonstrating Amazon S3 Storage Classes — Standard, Intelligent-Tiering, Standard-IA, One Zone-IA & Glacier using StorageClass=...
Amazon S3 Storage Classes — Standard, Intelligent-Tiering, Standard-IA, One Zone-IA & Glacier — Hands-On Lab Task
def recommend_s3_class(size_kb, retention_days, access_predictable, recreatable=False):
if size_kb < 128 or retention_days < 30:
return 'STANDARD'
if not access_predictable:
return 'INTELLIGENT_TIERING'
if recreatable and retention_days >= 30:
return 'ONEZONE_IA'
return 'GLACIER_IR' if retention_days >= 90 else 'STANDARD_IA'
print("Tiny Log:", recommend_s3_class(32, 60, True))
print("Unknown Pattern:", recommend_s3_class(2048, 120, False))
print("Quarterly Compliance:", reco...Implement a Python S3 storage utility that enforces SSE-KMS headers on uploads, computes optimal storage classes based on object access frequency and retention days, and prevents public ACL leaks.
Module Learning & Hands-On Objectives
💡 Self-Explanatory Overview: In simple, everyday terms, S3 Lifecycle Management — Waterfall Transitions, Noncurrent Version Expiry & Multipart Cleanup teaches you how AWS applications automating zero-touch object tiering, compliance expiration, version pruning, and orphaned multipart chunk cleanup via S3 Lifecycle Rules. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply S3 Lifecycle Management — Waterfall Transitions, Noncurrent Version Expiry & Multipart Cleanup in real AWS systems — specifically: Automating zero-touch object tiering, compliance expiration, version pruning, and orphaned multipart chunk cleanup via S3 Lifecycle Rules, so your code stays reliable, fast, and easy to maintain in production.
AWS S3 Lifecycle Management is a feature of Amazon Simple Storage Service (Amazon S3) that helps organizations automatically manage objects throughout their storage lifecycle. It allows users to define rules that automatically transition objects to different storage classes or delete them when they are no longer required. As data grows over time, storing every object in the same storage class can increase costs. Some...
S3 Lifecycle Management — Waterfall Transitions, Noncurrent Version Expiry & Multipart Cleanup — Practical Assignment
Implement a production-ready AWS Cloud & Solutions Architecture solution demonstrating S3 Lifecycle Management — Waterfall Transitions, Noncurrent Version Expiry & Multipart Cleanup using s3_client.pu...
S3 Lifecycle Management — Waterfall Transitions, Noncurrent Version Expiry & Multipart Cleanup — Hands-On Lab Task
rule = {
'ID': 'logs-tiering-v1',
'Status': 'Enabled',
'Filter': {'Prefix': 'audit-logs/'},
'Transitions': [
{'Days': 30, 'StorageClass': 'STANDARD_IA'},
{'Days': 90, 'StorageClass': 'DEEP_ARCHIVE'},
],
'AbortIncompleteMultipartUpload': {'DaysAfterInitiation': 7},
}
days = [t['Days'] for t in rule['Transitions']]
valid_waterfall = days == sorted(days) and days[0] >= 30
print(f"Rule: {rule['ID']} | Waterfall Valid: {valid_waterfall} | AbortMPU Days: {rule['AbortIncompleteMulti...💡 Self-Explanatory Overview: In simple, everyday terms, Amazon CloudFront CDN — Edge Caching, Origin Access Control (OAC), Signed URLs & Origin Shield teaches you how AWS applications accelerating static assets, HLS video streams, and dynamic APIs across global Edge PoPs while shielding private S3 buckets via Origin Access Control (OAC). Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply Amazon CloudFront CDN — Edge Caching, Origin Access Control (OAC), Signed URLs & Origin Shield in real AWS systems — specifically: Accelerating static assets, HLS video streams, and dynamic APIs across global Edge PoPs while shielding private S3 buckets via Origin Access Control (OAC), so your code stays reliable, fast, and easy to maintain in production.
CDNs are a network of interrelated servers that are used to provide web content in a fast and effective manner to users. It accelerates load times for data-intensive applications by caching copies of the content of websites, including images, videos, and other files, on servers in diverse locations. Typically, when a user accesses a website, the information needs to be sent from the web server to the user's devi...
Amazon CloudFront CDN — Edge Caching, Origin Access Control (OAC), Signed URLs & Origin Shield — Practical Assignment
Implement a production-ready AWS Cloud & Solutions Architecture solution demonstrating Amazon CloudFront CDN — Edge Caching, Origin Access Control (OAC), Signed URLs & Origin Shield using cloudfront_c...
Amazon CloudFront CDN — Edge Caching, Origin Access Control (OAC), Signed URLs & Origin Shield — Hands-On Lab Task
dist_arn = 'arn:aws:cloudfront::123456789012:distribution/E2QWRTY8899'
bucket_policy_stmt = {
'Effect': 'Allow',
'Principal': {'Service': 'cloudfront.amazonaws.com'},
'Action': 's3:GetObject',
'Resource': 'arn:aws:s3:::mockattempt-private-media/*',
'Condition': {'StringEquals': {'AWS:SourceArn': dist_arn}},
}
is_oac_scoped = bucket_policy_stmt['Principal']['Service'] == 'cloudfront.amazonaws.com' and 'AWS:SourceArn' in bucket_policy_stmt['Condition']['StringEquals']
print(f"Principal: {bucket_po...Generate a compliant S3 Lifecycle configuration (including incomplete multipart cleanup and noncurrent version expiration) paired with a CloudFront OAC bucket policy that blocks direct S3 URL bypass.
Module Learning & Hands-On Objectives
💡 Self-Explanatory Overview: In simple, everyday terms, Amazon EC2 Architecture — Nitro Instances, Purchasing Models, User Data & IMDSv2 Hardening teaches you how AWS applications provisioning virtual servers across General Purpose, Compute/Memory Optimized, and AWS Graviton ARM families while securing instance metadata via IMDSv2. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply Amazon EC2 Architecture — Nitro Instances, Purchasing Models, User Data & IMDSv2 Hardening in real AWS systems — specifically: Provisioning virtual servers across General Purpose, Compute/Memory Optimized, and AWS Graviton ARM families while securing instance metadata via IMDSv2, so your code stays reliable, fast, and easy to maintain in production.
Amazon EC2 (Elastic Compute Cloud) is a web service provided by Amazon Web Services (AWS) that offers resizable computing capacity in the cloud. It allows users to create and run virtual servers, called instances, without purchasing or maintaining physical hardware. Amazon EC2 is one of the most widely used AWS services for hosting websites, running applications, processing data, developing software, and performing v...
Amazon EC2 Architecture — Nitro Instances, Purchasing Models, User Data & IMDSv2 Hardening — Practical Assignment
Implement a production-ready AWS Cloud & Solutions Architecture solution demonstrating Amazon EC2 Architecture — Nitro Instances, Purchasing Models, User Data & IMDSv2 Hardening using ec2_client.run_i...
Amazon EC2 Architecture — Nitro Instances, Purchasing Models, User Data & IMDSv2 Hardening — Hands-On Lab Task
launch_spec = {
'InstanceType': 'c7g.large',
'MetadataOptions': {'HttpEndpoint': 'enabled', 'HttpTokens': 'required', 'HttpPutResponseHopLimit': 1},
}
hourly_od = 0.0725
baseline_sp = 4 * hourly_od * 0.65
burst_spot = 6 * hourly_od * 0.30
total_hr = round(baseline_sp + burst_spot, 4)
print(f"Type: {launch_spec['InstanceType']} | IMDSv2 Required: {launch_spec['MetadataOptions']['HttpTokens'] == 'required'} | Fleet $/hr: {total_hr}")💡 Self-Explanatory Overview: In simple, everyday terms, Amazon EBS Block Storage — gp3 vs io2 Volumes, AZ Affinity, Snapshots & KMS Encryption teaches you how AWS applications persistent network-attached block storage for EC2 with independent IOPS/throughput scaling on gp3, mission-critical 64k+ IOPS on io2, and incremental S3-backed snapshots. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply Amazon EBS Block Storage — gp3 vs io2 Volumes, AZ Affinity, Snapshots & KMS Encryption in real AWS systems — specifically: Persistent network-attached block storage for EC2 with independent IOPS/throughput scaling on gp3, mission-critical 64k+ IOPS on io2, and incremental S3-backed snapshots, so your code stays reliable, fast, and easy to maintain in production.
Amazon Elastic Block Store (Amazon EBS) is a scalable and persistent block storage option that can be used by Amazon EC2 instances. It offers storage volumes that can be attached to EC2 instances and treated just like a physical hard drive. A file system can be created on an EBS volume, data for applications can be stored, databases can be hosted, and other workloads that require reliable block-level storage can be u...
Amazon EBS Block Storage — gp3 vs io2 Volumes, AZ Affinity, Snapshots & KMS Encryption — Practical Assignment
Implement a production-ready AWS Cloud & Solutions Architecture solution demonstrating Amazon EBS Block Storage — gp3 vs io2 Volumes, AZ Affinity, Snapshots & KMS Encryption using ec2_client.create_vo...
Amazon EBS Block Storage — gp3 vs io2 Volumes, AZ Affinity, Snapshots & KMS Encryption — Hands-On Lab Task
def validate_ebs_gp3(ec2_az, vol_az, size_gb, target_iops):
if ec2_az != vol_az:
return f"CROSS_AZ_ERROR: snapshot required ({vol_az} -> {ec2_az})"
extra_iops = max(0, target_iops - 3000)
return f"ATTACH_OK ({size_gb}GB gp3) | Paid Extra IOPS: {extra_iops}"
print(validate_ebs_gp3('ap-south-1a', 'ap-south-1a', 100, 5000))
print(validate_ebs_gp3('ap-south-1b', 'ap-south-1a', 100, 3000))Develop a Python capacity planner that splits baseline vs burst compute across Savings Plans and Spot Instances, enforces IMDSv2 launch template settings, and computes savings from migrating legacy gp2 EBS volumes to gp3.
Module Learning & Hands-On Objectives
💡 Self-Explanatory Overview: In simple, everyday terms, AWS Security Groups — Stateful ENI Firewalls, Implicit Deny & SG-ID Chaining teaches you how AWS applications how Security Groups act as stateful virtual firewalls at the Elastic Network Interface (ENI) level supporting Allow-only rules and dynamic Security Group ID referencing. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply AWS Security Groups — Stateful ENI Firewalls, Implicit Deny & SG-ID Chaining in real AWS systems — specifically: How Security Groups act as stateful virtual firewalls at the Elastic Network Interface (ENI) level supporting Allow-only rules and dynamic Security Group ID referencing, so your code stays reliable, fast, and easy to maintain in production.
A security group is a virtual firewall which is controlling the traffic to your EC2 instances. When you first launch an EC2 instance, you can associate it with one or more security groups. A Security group is the first defence against hackers. Let's understand the concept of security group through an example. Sign in to the AWS Management console. Launch a new EC2 instance. Choose an Amazon Machine Image. Choose...
AWS Security Groups — Stateful ENI Firewalls, Implicit Deny & SG-ID Chaining — Practical Assignment
Implement a production-ready AWS Cloud & Solutions Architecture solution demonstrating AWS Security Groups — Stateful ENI Firewalls, Implicit Deny & SG-ID Chaining using ec2_client.authorize_security_...
AWS Security Groups — Stateful ENI Firewalls, Implicit Deny & SG-ID Chaining — Hands-On Lab Task
sg_rules = {
'sg-alb': [{'port': 443, 'source': '0.0.0.0/0'}],
'sg-app': [{'port': 8080, 'source': 'sg-alb'}],
'sg-rds': [{'port': 5432, 'source': 'sg-app'}],
}
private_exposed = any(
r['source'] == '0.0.0.0/0' for tier in ('sg-app', 'sg-rds') for r in sg_rules[tier]
)
chained = sg_rules['sg-app'][0]['source'] == 'sg-alb' and sg_rules['sg-rds'][0]['source'] == 'sg-app'
print(f"Private Exposed: {private_exposed} | Zero-Trust SG Chained: {chained}")💡 Self-Explanatory Overview: In simple, everyday terms, Elastic Load Balancing — ALB vs NLB, Target Groups, Health Checks & X-Forwarded-For teaches you how AWS applications distributing Multi-AZ traffic across EC2 instances, ECS IP tasks, and Lambda functions via Layer-7 ALB host/path rules or Layer-4 static-IP NLB. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply Elastic Load Balancing — ALB vs NLB, Target Groups, Health Checks & X-Forwarded-For in real AWS systems — specifically: Distributing Multi-AZ traffic across EC2 instances, ECS IP tasks, and Lambda functions via Layer-7 ALB host/path rules or Layer-4 static-IP NLB, so your code stays reliable, fast, and easy to maintain in production.
Load Balancer is a virtual machine or appliance that balances your web application load that could be Http or Https traffic that you are getting in. It balances a load of multiple web servers so that no web server gets overwhelmed. Application Load Balancer An Amazon Web Services (AWS) launched a new load balancer known as an Application load balancer (ALB) on August 11, 2016. It is used to direct user traffic to the...
Elastic Load Balancing — ALB vs NLB, Target Groups, Health Checks & X-Forwarded-For — Practical Assignment
Implement a production-ready AWS Cloud & Solutions Architecture solution demonstrating Elastic Load Balancing — ALB vs NLB, Target Groups, Health Checks & X-Forwarded-For using elbv2_client.create_loa...
Elastic Load Balancing — ALB vs NLB, Target Groups, Health Checks & X-Forwarded-For — Hands-On Lab Task
rules = [
{'priority': 10, 'prefix': '/api/v2/', 'target_group': 'tg-fastapi-v2'},
{'priority': 20, 'prefix': '/static/', 'target_group': 'tg-assets'},
]
def route_alb(path, xff_header):
client_ip = xff_header.split(',')[0].strip()
for r in sorted(rules, key=lambda x: x['priority']):
if path.startswith(r['prefix']):
return f"{client_ip} -> {r['target_group']}"
return f"{client_ip} -> tg-default-web"
print(route_alb('/api/v2/orders', '49.36.120.8, 10.0.1.44'))Build an automated AWS security & load-balancing topology validator that verifies SG-ID chaining across ALB, App, and Database tiers and checks ALB Target Group deregistration delay and health thresholds.
Module Learning & Hands-On Objectives
💡 Self-Explanatory Overview: In simple, everyday terms, Amazon VPC Internals — CIDR Blocks, 5 Reserved Subnet IPs, Route Tables & Internet Gateways teaches you how AWS applications building logically isolated software-defined cloud networks with non-overlapping RFC-1918 CIDRs, public/private route tables, VPC DNS (+2 IP), and Flow Logs. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply Amazon VPC Internals — CIDR Blocks, 5 Reserved Subnet IPs, Route Tables & Internet Gateways in real AWS systems — specifically: Building logically isolated software-defined cloud networks with non-overlapping RFC-1918 CIDRs, public/private route tables, VPC DNS (+2 IP), and Flow Logs, so your code stays reliable, fast, and easy to maintain in production.
VPC stands for Virtual Private Cloud. Amazon Virtual Private Cloud (Amazon VPC) provides a logically isolated area of the AWS cloud where you can launch AWS resources in a virtual network that you define. You have complete control over your virtual networking environment, including a selection of your IP address range, the creation of subnets, and configuration of route tables and network gateways. You can easily cus...
Amazon VPC Internals — CIDR Blocks, 5 Reserved Subnet IPs, Route Tables & Internet Gateways — Practical Assignment
Implement a production-ready AWS Cloud & Solutions Architecture solution demonstrating Amazon VPC Internals — CIDR Blocks, 5 Reserved Subnet IPs, Route Tables & Internet Gateways using ec2_client.crea...
Amazon VPC Internals — CIDR Blocks, 5 Reserved Subnet IPs, Route Tables & Internet Gateways — Hands-On Lab Task
import ipaddress
subnet = ipaddress.ip_network('10.20.1.0/24')
usable_ips = subnet.num_addresses - 5
vpc_router = subnet.network_address + 1
vpc_dns = subnet.network_address + 2
print(f"Subnet: {subnet} | Total: {subnet.num_addresses} | Usable AWS Hosts: {usable_ips}")
print(f"VPC Router: {vpc_router} | AWS DNS: {vpc_dns}")💡 Self-Explanatory Overview: In simple, everyday terms, AWS NAT Gateways & VPC Endpoints — Outbound-Only Private Egress, Multi-AZ HA & S3/DynamoDB Bypass teaches you how AWS applications enabling private-subnet outbound internet patching via managed NAT Gateways while slashing per-GB NAT fees with free Gateway VPC Endpoints for S3 and DynamoDB. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply AWS NAT Gateways & VPC Endpoints — Outbound-Only Private Egress, Multi-AZ HA & S3/DynamoDB Bypass in real AWS systems — specifically: Enabling private-subnet outbound internet patching via managed NAT Gateways while slashing per-GB NAT fees with free Gateway VPC Endpoints for S3 and DynamoDB, so your code stays reliable, fast, and easy to maintain in production.
AWS NAT Gateway is a managed network address translation service provided by Amazon Web Services (AWS). It allows resources in a private subnet of an Amazon Virtual Private Cloud (VPC) to initiate outbound connections to the internet, other VPCs, or on-premises networks without exposing those resources to unsolicited inbound connections. NAT stands for Network Address Translation. A NAT Gateway translates the private...
AWS NAT Gateways & VPC Endpoints — Outbound-Only Private Egress, Multi-AZ HA & S3/DynamoDB Bypass — Practical Assignment
Implement a production-ready AWS Cloud & Solutions Architecture solution demonstrating AWS NAT Gateways & VPC Endpoints — Outbound-Only Private Egress, Multi-AZ HA & S3/DynamoDB Bypass using ec2_clien...
AWS NAT Gateways & VPC Endpoints — Outbound-Only Private Egress, Multi-AZ HA & S3/DynamoDB Bypass — Hands-On Lab Task
def audit_nat_and_savings(nat_subnet_has_igw, monthly_s3_tb):
placement_ok = bool(nat_subnet_has_igw)
nat_gb_rate = 0.045
nat_data_cost = round(monthly_s3_tb * 1024 * nat_gb_rate, 2)
endpoint_cost = 0.00
saved = nat_data_cost - endpoint_cost
return f"NAT In Public Subnet: {placement_ok} | Saved via S3 Gateway Endpoint: ${saved:.2f}/mo"
print(audit_nat_and_savings(True, 10))Write a Python networking tool using ipaddress that partitions a 10.20.0.0/16 VPC into 6 Multi-AZ subnets, computes exact usable host IPs (total minus 5 AWS-reserved addresses), and wires Gateway VPC Endpoints onto private route tables.
Module Learning & Hands-On Objectives
💡 Self-Explanatory Overview: In simple, everyday terms, Network ACL (NACL) vs Security Group — Stateless Subnet Filtering, Rule Ordering & Ephemeral Ports teaches you how AWS applications comparing subnet-boundary stateless NACLs (ordered Allow/Deny rules + explicit ephemeral port rules) with ENI-boundary stateful Security Groups. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply Network ACL (NACL) vs Security Group — Stateless Subnet Filtering, Rule Ordering & Ephemeral Ports in real AWS systems — specifically: Comparing subnet-boundary stateless NACLs (ordered Allow/Deny rules + explicit ephemeral port rules) with ENI-boundary stateful Security Groups, so your code stays reliable, fast, and easy to maintain in production.
An AWS Security Group is a virtual firewall that manages the traffic that can flow in or out of AWS resources like EC2 instances, load balancers, RDS database instances, and other resources within a VPC. It lets or denies traffic to follow a specific set of security rules. As an example, if you create a security group to allow inbound traffic for ports 80 (http) and 443 (https) from any IP address, then your web app...
Network ACL (NACL) vs Security Group — Stateless Subnet Filtering, Rule Ordering & Ephemeral Ports — Practical Assignment
Implement a production-ready AWS Cloud & Solutions Architecture solution demonstrating Network ACL (NACL) vs Security Group — Stateless Subnet Filtering, Rule Ordering & Ephemeral Ports using ec2_clie...
Network ACL (NACL) vs Security Group — Stateless Subnet Filtering, Rule Ordering & Ephemeral Ports — Hands-On Lab Task
def eval_nacl(rules, port):
for r in sorted(rules, key=lambda x: x['num']):
if r['from'] <= port <= r['to']:
return r['action'].upper()
return 'IMPLICIT_DENY'
inbound = [{'num': 90, 'from': 443, 'to': 443, 'action': 'allow'}]
outbound = [{'num': 100, 'from': 1024, 'to': 65535, 'action': 'allow'}]
print("Req 443:", eval_nacl(inbound, 443), "| Resp Ephemeral 52144:", eval_nacl(outbound, 52144))💡 Self-Explanatory Overview: In simple, everyday terms, Amazon RDS Architecture — Multi-AZ Synchronous Failover, Read Replicas, PITR & RDS Proxy teaches you how AWS applications provisioning managed PostgreSQL/MySQL/Aurora databases in isolated DB Subnet Groups with automated Multi-AZ DNS failover, Point-in-Time Recovery, and RDS Proxy pooling. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply Amazon RDS Architecture — Multi-AZ Synchronous Failover, Read Replicas, PITR & RDS Proxy in real AWS systems — specifically: Provisioning managed PostgreSQL/MySQL/Aurora databases in isolated DB Subnet Groups with automated Multi-AZ DNS failover, Point-in-Time Recovery, and RDS Proxy pooling, so your code stays reliable, fast, and easy to maintain in production.
Step 1: Creating an RDS instance. Click on the RDS service under Database. Click on the Dashboard appearing on the left side of the console, then click on the Create Database button. Choose the MySQL database. Check the box of "Only enable options eligible for RDS Free Usage Tier", and then click on the Next. Specify DB details. Keep all the details as default. Enter the DB instance identifier which would b...
Amazon RDS Architecture — Multi-AZ Synchronous Failover, Read Replicas, PITR & RDS Proxy — Practical Assignment
Implement a production-ready AWS Cloud & Solutions Architecture solution demonstrating Amazon RDS Architecture — Multi-AZ Synchronous Failover, Read Replicas, PITR & RDS Proxy using rds_client.create_...
Amazon RDS Architecture — Multi-AZ Synchronous Failover, Read Replicas, PITR & RDS Proxy — Hands-On Lab Task
rds_spec = {
'DBInstanceIdentifier': 'academy-pg-prod',
'Engine': 'postgres',
'MultiAZ': True,
'PubliclyAccessible': False,
'StorageEncrypted': True,
'BackupRetentionPeriod': 14,
}
prod_compliant = (
rds_spec['MultiAZ'] and not rds_spec['PubliclyAccessible']
and rds_spec['StorageEncrypted'] and rds_spec['BackupRetentionPeriod'] >= 7
)
print(f"DB: {rds_spec['DBInstanceIdentifier']} | Prod HA & Security Compliant: {prod_compliant}")Implement a rule evaluator that tests numbered inbound/outbound stateless NACL rules (including ephemeral port return traffic) alongside an RDS Multi-AZ configuration validator.
Module Learning & Hands-On Objectives
💡 Self-Explanatory Overview: In simple, everyday terms, Amazon DynamoDB — Partition & Sort Keys, Query vs Scan, GSI/LSI, RCU/WCU & Streams teaches you how AWS applications delivering predictable single-digit millisecond latency at any scale using high-cardinality Partition Keys, B-tree Sort Keys, On-Demand/Provisioned capacity, and DynamoDB Streams. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply Amazon DynamoDB — Partition & Sort Keys, Query vs Scan, GSI/LSI, RCU/WCU & Streams in real AWS systems — specifically: Delivering predictable single-digit millisecond latency at any scale using high-cardinality Partition Keys, B-tree Sort Keys, On-Demand/Provisioned capacity, and DynamoDB Streams, so your code stays reliable, fast, and easy to maintain in production.
Amazon DynamoDB is a fully managed NoSQL database service offered by AWS, designed to be scalable, fast, and low-latency for accessing data. DynamoDB was developed to provide a cost-effective, flexible, and easy-to-use database that can handle large amounts of data and high levels of traffic. It can seamlessly scale for a huge amount of requests without having to worry about the underlying servers. Data is stored on...
Amazon DynamoDB — Partition & Sort Keys, Query vs Scan, GSI/LSI, RCU/WCU & Streams — Practical Assignment
Implement a production-ready AWS Cloud & Solutions Architecture solution demonstrating Amazon DynamoDB — Partition & Sort Keys, Query vs Scan, GSI/LSI, RCU/WCU & Streams using table.query(KeyCondition...
Amazon DynamoDB — Partition & Sort Keys, Query vs Scan, GSI/LSI, RCU/WCU & Streams — Hands-On Lab Task
import math
def calc_dynamodb_units(item_kb, reads_per_sec, writes_per_sec, strong_read=True):
read_blocks = math.ceil(item_kb / 4)
rcu = reads_per_sec * read_blocks if strong_read else math.ceil((reads_per_sec * read_blocks) / 2)
wcu = writes_per_sec * math.ceil(item_kb / 1)
return rcu, wcu
strong_rcu, std_wcu = calc_dynamodb_units(item_kb=6, reads_per_sec=100, writes_per_sec=40, strong_read=True)
eventual_rcu, _ = calc_dynamodb_units(item_kb=6, reads_per_sec=100, writes_per_sec=40, strong_read=F...💡 Self-Explanatory Overview: In simple, everyday terms, AWS Lambda Internals — Firecracker Execution Lifecycle, Cold Starts, Concurrency & Idempotency teaches you how AWS applications event-driven serverless compute scaling from zero to thousands of concurrent microVMs with proportional memory-to-vCPU allocation (1,769 MB = 1 full vCPU) and max 15-minute execution. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply AWS Lambda Internals — Firecracker Execution Lifecycle, Cold Starts, Concurrency & Idempotency in real AWS systems — specifically: Event-driven serverless compute scaling from zero to thousands of concurrent microVMs with proportional memory-to-vCPU allocation (1,769 MB = 1 full vCPU) and max 15-minute execution, so your code stays reliable, fast, and easy to maintain in production.
AWS Lambda is a serverless computing service provided by Amazon Web Services (AWS). It allows developers to run application code without managing servers, operating systems, or other underlying infrastructure. With Lambda, you upload your code, configure when it should run, and AWS automatically handles the required computing resources. AWS Lambda is commonly used to build event-driven applications, APIs, backend ser...
AWS Lambda Internals — Firecracker Execution Lifecycle, Cold Starts, Concurrency & Idempotency — Practical Assignment
Implement a production-ready AWS Cloud & Solutions Architecture solution demonstrating AWS Lambda Internals — Firecracker Execution Lifecycle, Cold Starts, Concurrency & Idempotency using def lambda_h...
AWS Lambda Internals — Firecracker Execution Lifecycle, Cold Starts, Concurrency & Idempotency — Hands-On Lab Task
SEEN_REQUESTS = set()
def lambda_handler(event, context=None):
req_id = event['order_id']
if req_id in SEEN_REQUESTS:
return {'statusCode': 200, 'status': 'DUPLICATE_SKIPPED'}
SEEN_REQUESTS.add(req_id)
return {'statusCode': 201, 'status': 'PROCESSED', 'warm_cache_size': len(SEEN_REQUESTS)}
print(lambda_handler({'order_id': 'ORD-901'}))
print(lambda_handler({'order_id': 'ORD-901'}))Build a DynamoDB RCU/WCU estimator paired with an AWS Lambda handler simulator that caches SDK clients at module scope and enforces conditional PutItem idempotency.
Module Learning & Hands-On Objectives
💡 Self-Explanatory Overview: In simple, everyday terms, Amazon API Gateway — HTTP vs REST vs WebSocket APIs, Authorizers, Throttling & 29s Limit teaches you how AWS applications securing and throttling serverless APIs at scale using Cognito/JWT Authorizers, Usage Plans, Token-Bucket Burst Limits, and Lambda Proxy Integration. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply Amazon API Gateway — HTTP vs REST vs WebSocket APIs, Authorizers, Throttling & 29s Limit in real AWS systems — specifically: Securing and throttling serverless APIs at scale using Cognito/JWT Authorizers, Usage Plans, Token-Bucket Burst Limits, and Lambda Proxy Integration, so your code stays reliable, fast, and easy to maintain in production.
Amazon API Gateway is a fully managed AWS service used to create, publish, maintain, monitor, and secure APIs. It acts as a front door between client applications and backend services such as AWS Lambda, Amazon EC2, Amazon ECS, and other HTTP-based applications. API Gateway is commonly used in serverless applications, microservices, mobile applications, web applications, and real-time applications. It supports HTTP A...
Amazon API Gateway — HTTP vs REST vs WebSocket APIs, Authorizers, Throttling & 29s Limit — Practical Assignment
Implement a production-ready AWS Cloud & Solutions Architecture solution demonstrating Amazon API Gateway — HTTP vs REST vs WebSocket APIs, Authorizers, Throttling & 29s Limit using apigwv2_client.cre...
Amazon API Gateway — HTTP vs REST vs WebSocket APIs, Authorizers, Throttling & 29s Limit — Hands-On Lab Task
import json
def handle_apigw_request(est_duration_sec, job_id):
if est_duration_sec >= 25:
return {'statusCode': 202, 'body': json.dumps({'jobId': job_id, 'mode': 'QUEUED_TO_SQS'})}
return {'statusCode': 200, 'body': json.dumps({'jobId': job_id, 'mode': 'SYNC_OK'})}
print(handle_apigw_request(4, 'JOB-10'))
print(handle_apigw_request(45, 'JOB-99'))💡 Self-Explanatory Overview: In simple, everyday terms, Amazon SQS — Standard vs FIFO Queues, Visibility Timeout, Long Polling & Dead-Letter Queues teaches you how AWS applications decoupling producer spikes from downstream workers with SQS Standard (unlimited throughput, at-least-once) and FIFO (.fifo, MessageGroupId ordering, deduplication), Long Polling, and DLQs. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply Amazon SQS — Standard vs FIFO Queues, Visibility Timeout, Long Polling & Dead-Letter Queues in real AWS systems — specifically: Decoupling producer spikes from downstream workers with SQS Standard (unlimited throughput, at-least-once) and FIFO (.fifo, MessageGroupId ordering, deduplication), Long Polling, and DLQs, so your code stays reliable, fast, and easy to maintain in production.
Amazon Simple Queue Service (SQS), a fully managed message queuing service offered by AWS, enables applications to send, receive, and store messages. It's meant to separate and scale microservices, distributed systems, and serverless applications, allowing them to communicate asynchronously. Amazon SQS is a reliable, scalable queue that temporarily holds messages between applications or between services. Message...
Amazon SQS — Standard vs FIFO Queues, Visibility Timeout, Long Polling & Dead-Letter Queues — Practical Assignment
Implement a production-ready AWS Cloud & Solutions Architecture solution demonstrating Amazon SQS — Standard vs FIFO Queues, Visibility Timeout, Long Polling & Dead-Letter Queues using sqs_client.rece...
Amazon SQS — Standard vs FIFO Queues, Visibility Timeout, Long Polling & Dead-Letter Queues — Hands-On Lab Task
def sqs_batch_worker(records, lambda_timeout_sec, visibility_sec):
failures = []
for rec in records:
if 'POISON' in rec['body']:
failures.append({'itemIdentifier': rec['messageId']})
vis_safe = visibility_sec >= (6 * lambda_timeout_sec)
return {'vis_safe': vis_safe, 'batchItemFailures': failures}
batch = [{'messageId': 'm-1', 'body': 'OK'}, {'messageId': 'm-2', 'body': 'POISON_JSON'}]
print(sqs_batch_worker(batch, lambda_timeout_sec=30, visibility_sec=180))Architect an async order-processing pipeline that validates API Gateway Lambda Proxy responses, checks SQS VisibilityTimeout >= 6x consumer timeout, and returns batchItemFailures so poison messages isolate into a DLQ without re-running succeeded items.
Module Learning & Hands-On Objectives
💡 Self-Explanatory Overview: In simple, everyday terms, Remote Terraform State in Encrypted S3 + DynamoDB State Locking teaches you how AWS applications prevent two engineers or CI pipelines from corrupting cloud state simultaneously. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply Remote Terraform State in Encrypted S3 + DynamoDB State Locking in real AWS systems — specifically: Prevent two engineers or CI pipelines from corrupting cloud state simultaneously, so your code stays reliable, fast, and easy to maintain in production.
What Is Remote Terraform State in Encrypted S3 + DynamoDB State Locking & Why Industry Teams Use ItIn AWS Training, Remote Terraform State in Encrypted S3 + DynamoDB State Locking exists for one clear real-world purpose: Prevent two engineers or CI pipelines from corrupting cloud state simultaneously. Even if you come from a non-technical background, we start with the everyday real-life problem first before writi...
Hands-On Implementation: Remote Terraform State in Encrypted S3 + DynamoDB State Locking
Build and verify a clean working module demonstrating Remote Terraform State in Encrypted S3 + DynamoDB State Locking (Prevent two engineers or CI pipelines from corrupting cloud state simultaneously....
Live Lab Sprint: Remote Terraform State in Encrypted S3 + DynamoDB State Locking
# Remote Terraform State in Encrypted S3 + DynamoDB State Locking
# Purpose: Prevent two engineers or CI pipelines from corrupting cloud state simultaneously.
resource "aws_s3_bucket_public_access_block" "guard" {
block_public_acls = true
block_public_policy = true
}💡 Self-Explanatory Overview: In simple, everyday terms, Reusable VPC, ALB & RDS Modules Across Dev/Stage/Prod Workspaces teaches you how AWS applications provision identical, auditable AWS environments in minutes with zero console click-ops. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply Reusable VPC, ALB & RDS Modules Across Dev/Stage/Prod Workspaces in real AWS systems — specifically: Provision identical, auditable AWS environments in minutes with zero console click-ops, so your code stays reliable, fast, and easy to maintain in production.
What Is Reusable VPC, ALB & RDS Modules Across Dev/Stage/Prod Workspaces & Why Industry Teams Use ItIn AWS Training, Reusable VPC, ALB & RDS Modules Across Dev/Stage/Prod Workspaces exists for one clear real-world purpose: Provision identical, auditable AWS environments in minutes with zero console click-ops. Even if you come from a non-technical background, we start with the everyday real-life problem fi...
Hands-On Implementation: Reusable VPC, ALB & RDS Modules Across Dev/Stage/Prod Workspaces
Build and verify a clean working module demonstrating Reusable VPC, ALB & RDS Modules Across Dev/Stage/Prod Workspaces (Provision identical, auditable AWS environments in minutes with zero console cli...
Live Lab Sprint: Reusable VPC, ALB & RDS Modules Across Dev/Stage/Prod Workspaces
# Reusable VPC, ALB & RDS Modules Across Dev/Stage/Prod Workspaces
# Purpose: Provision identical, auditable AWS environments in minutes with zero console click-ops.
resource "aws_s3_bucket_public_access_block" "guard" {
block_public_acls = true
block_public_policy = true
}💡 Self-Explanatory Overview: In simple, everyday terms, IAM OIDC GitHub Actions Federation (Zero Long-Lived AWS Access Keys) teaches you how AWS applications deploy to AWS from CI using short-lived STS tokens instead of leak-prone static keys. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply IAM OIDC GitHub Actions Federation (Zero Long-Lived AWS Access Keys) in real AWS systems — specifically: Deploy to AWS from CI using short-lived STS tokens instead of leak-prone static keys, so your code stays reliable, fast, and easy to maintain in production.
What Is IAM OIDC GitHub Actions Federation (Zero Long-Lived AWS Access Keys) & Why Industry Teams Use ItIn AWS Training, IAM OIDC GitHub Actions Federation (Zero Long-Lived AWS Access Keys) exists for one clear real-world purpose: Deploy to AWS from CI using short-lived STS tokens instead of leak-prone static keys. Even if you come from a non-technical background, we start with the everyday real-life problem firs...
Hands-On Implementation: IAM OIDC GitHub Actions Federation (Zero Long-Lived AWS Access Keys)
Build and verify a clean working module demonstrating IAM OIDC GitHub Actions Federation (Zero Long-Lived AWS Access Keys) (Deploy to AWS from CI using short-lived STS tokens instead of leak-prone sta...
Live Lab Sprint: IAM OIDC GitHub Actions Federation (Zero Long-Lived AWS Access Keys)
# IAM OIDC GitHub Actions Federation (Zero Long-Lived AWS Access Keys)
# Purpose: Deploy to AWS from CI using short-lived STS tokens instead of leak-prone static keys.
resource "aws_s3_bucket_public_access_block" "guard" {
block_public_acls = true
block_public_policy = true
}💡 Self-Explanatory Overview: In simple, everyday terms, Drift Detection, Policy-as-Code Guardrails & Tagging Enforcement teaches you how AWS applications block unencrypted buckets or public security groups automatically before apply. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply Drift Detection, Policy-as-Code Guardrails & Tagging Enforcement in real AWS systems — specifically: Block unencrypted buckets or public security groups automatically before apply, so your code stays reliable, fast, and easy to maintain in production.
What Is Drift Detection, Policy-as-Code Guardrails & Tagging Enforcement & Why Industry Teams Use ItIn AWS Training, Drift Detection, Policy-as-Code Guardrails & Tagging Enforcement exists for one clear real-world purpose: Block unencrypted buckets or public security groups automatically before apply. Even if you come from a non-technical background, we start with the everyday real-life problem first befo...
Hands-On Implementation: Drift Detection, Policy-as-Code Guardrails & Tagging Enforcement
Build and verify a clean working module demonstrating Drift Detection, Policy-as-Code Guardrails & Tagging Enforcement (Block unencrypted buckets or public security groups automatically before apply.)...
Live Lab Sprint: Drift Detection, Policy-as-Code Guardrails & Tagging Enforcement
# Drift Detection, Policy-as-Code Guardrails & Tagging Enforcement
# Purpose: Block unencrypted buckets or public security groups automatically before apply.
resource "aws_s3_bucket_public_access_block" "guard" {
block_public_acls = true
block_public_policy = true
}Design, implement, test, and document 'Modular Terraform AWS VPC + Compute + RDS Blueprint' applying every production concept from Module 11 (Infrastructure as Code on AWS: Terraform / CloudFormation & Multi-Env State) of AWS Training.
Module Learning & Hands-On Objectives
💡 Self-Explanatory Overview: In simple, everyday terms, Amazon ECR Image Scanning & Serverless ECS Fargate Task Definitions teaches you how AWS applications run production containers without patching EC2 hosts, using per-task IAM roles. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply Amazon ECR Image Scanning & Serverless ECS Fargate Task Definitions in real AWS systems — specifically: Run production containers without patching EC2 hosts, using per-task IAM roles, so your code stays reliable, fast, and easy to maintain in production.
What Is Amazon ECR Image Scanning & Serverless ECS Fargate Task Definitions & Why Industry Teams Use ItIn AWS Training, Amazon ECR Image Scanning & Serverless ECS Fargate Task Definitions exists for one clear real-world purpose: Run production containers without patching EC2 hosts, using per-task IAM roles. Even if you come from a non-technical background, we start with the everyday real-life problem firs...
Hands-On Implementation: Amazon ECR Image Scanning & Serverless ECS Fargate Task Definitions
Build and verify a clean working module demonstrating Amazon ECR Image Scanning & Serverless ECS Fargate Task Definitions (Run production containers without patching EC2 hosts, using per-task IAM role...
Live Lab Sprint: Amazon ECR Image Scanning & Serverless ECS Fargate Task Definitions
# Amazon ECR Image Scanning & Serverless ECS Fargate Task Definitions
# Purpose: Run production containers without patching EC2 hosts, using per-task IAM roles.
resource "aws_s3_bucket_public_access_block" "guard" {
block_public_acls = true
block_public_policy = true
}💡 Self-Explanatory Overview: In simple, everyday terms, ALB Target Group Health Checks & ECS Service Auto Scaling teaches you how AWS applications scale container tasks seamlessly on CPU/request spikes with zero dropped connections. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply ALB Target Group Health Checks & ECS Service Auto Scaling in real AWS systems — specifically: Scale container tasks seamlessly on CPU/request spikes with zero dropped connections, so your code stays reliable, fast, and easy to maintain in production.
What Is ALB Target Group Health Checks & ECS Service Auto Scaling & Why Industry Teams Use ItIn AWS Training, ALB Target Group Health Checks & ECS Service Auto Scaling exists for one clear real-world purpose: Scale container tasks seamlessly on CPU/request spikes with zero dropped connections. Even if you come from a non-technical background, we start with the everyday real-life problem first before writi...
Hands-On Implementation: ALB Target Group Health Checks & ECS Service Auto Scaling
Build and verify a clean working module demonstrating ALB Target Group Health Checks & ECS Service Auto Scaling (Scale container tasks seamlessly on CPU/request spikes with zero dropped connections.)....
Live Lab Sprint: ALB Target Group Health Checks & ECS Service Auto Scaling
# ALB Target Group Health Checks & ECS Service Auto Scaling
# Purpose: Scale container tasks seamlessly on CPU/request spikes with zero dropped connections.
resource "aws_s3_bucket_public_access_block" "guard" {
block_public_acls = true
block_public_policy = true
}💡 Self-Explanatory Overview: In simple, everyday terms, AWS Lambda Cold-Start Tuning, API Gateway & DynamoDB Single-Table Patterns teaches you how AWS applications build pay-per-request serverless APIs with sub-10ms DynamoDB lookups. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply AWS Lambda Cold-Start Tuning, API Gateway & DynamoDB Single-Table Patterns in real AWS systems — specifically: Build pay-per-request serverless APIs with sub-10ms DynamoDB lookups, so your code stays reliable, fast, and easy to maintain in production.
What Is AWS Lambda Cold-Start Tuning, API Gateway & DynamoDB Single-Table Patterns & Why Industry Teams Use ItIn AWS Training, AWS Lambda Cold-Start Tuning, API Gateway & DynamoDB Single-Table Patterns exists for one clear real-world purpose: Build pay-per-request serverless APIs with sub-10ms DynamoDB lookups. Even if you come from a non-technical background, we start with the everyday real-life problem...
Hands-On Implementation: AWS Lambda Cold-Start Tuning, API Gateway & DynamoDB Single-Table Patterns
Build and verify a clean working module demonstrating AWS Lambda Cold-Start Tuning, API Gateway & DynamoDB Single-Table Patterns (Build pay-per-request serverless APIs with sub-10ms DynamoDB lookups.)...
Live Lab Sprint: AWS Lambda Cold-Start Tuning, API Gateway & DynamoDB Single-Table Patterns
# AWS Lambda Cold-Start Tuning, API Gateway & DynamoDB Single-Table Patterns
# Purpose: Build pay-per-request serverless APIs with sub-10ms DynamoDB lookups.
resource "aws_s3_bucket_public_access_block" "guard" {
block_public_acls = true
block_public_policy = true
}💡 Self-Explanatory Overview: In simple, everyday terms, Decoupled Microservices with SQS Dead-Letter Queues, SNS & EventBridge teaches you how AWS applications absorb 10x traffic bursts reliably and isolate failed events for safe replay. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply Decoupled Microservices with SQS Dead-Letter Queues, SNS & EventBridge in real AWS systems — specifically: Absorb 10x traffic bursts reliably and isolate failed events for safe replay, so your code stays reliable, fast, and easy to maintain in production.
What Is Decoupled Microservices with SQS Dead-Letter Queues, SNS & EventBridge & Why Industry Teams Use ItIn AWS Training, Decoupled Microservices with SQS Dead-Letter Queues, SNS & EventBridge exists for one clear real-world purpose: Absorb 10x traffic bursts reliably and isolate failed events for safe replay. Even if you come from a non-technical background, we start with the everyday real-life problem...
Hands-On Implementation: Decoupled Microservices with SQS Dead-Letter Queues, SNS & EventBridge
Build and verify a clean working module demonstrating Decoupled Microservices with SQS Dead-Letter Queues, SNS & EventBridge (Absorb 10x traffic bursts reliably and isolate failed events for safe repl...
Live Lab Sprint: Decoupled Microservices with SQS Dead-Letter Queues, SNS & EventBridge
# Decoupled Microservices with SQS Dead-Letter Queues, SNS & EventBridge
# Purpose: Absorb 10x traffic bursts reliably and isolate failed events for safe replay.
resource "aws_s3_bucket_public_access_block" "guard" {
block_public_acls = true
block_public_policy = true
}Design, implement, test, and document 'Event-Driven Order Processing Pipeline on ECS Fargate & SQS' applying every production concept from Module 12 (AWS Containers & Serverless Event-Driven Architecture (ECS, Lambda, SQS)) of AWS Training.
Module Learning & Hands-On Objectives
💡 Self-Explanatory Overview: In simple, everyday terms, IAM Permission Boundaries, SCPs & Least-Privilege Policy Analysis teaches you how AWS applications contain blast radius across multi-account AWS Organizations workloads. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply IAM Permission Boundaries, SCPs & Least-Privilege Policy Analysis in real AWS systems — specifically: Contain blast radius across multi-account AWS Organizations workloads, so your code stays reliable, fast, and easy to maintain in production.
What Is IAM Permission Boundaries, SCPs & Least-Privilege Policy Analysis & Why Industry Teams Use ItIn AWS Training, IAM Permission Boundaries, SCPs & Least-Privilege Policy Analysis exists for one clear real-world purpose: Contain blast radius across multi-account AWS Organizations workloads. Even if you come from a non-technical background, we start with the everyday real-life problem first before writ...
Hands-On Implementation: IAM Permission Boundaries, SCPs & Least-Privilege Policy Analysis
Build and verify a clean working module demonstrating IAM Permission Boundaries, SCPs & Least-Privilege Policy Analysis (Contain blast radius across multi-account AWS Organizations workloads.). Handle...
Live Lab Sprint: IAM Permission Boundaries, SCPs & Least-Privilege Policy Analysis
# IAM Permission Boundaries, SCPs & Least-Privilege Policy Analysis
# Purpose: Contain blast radius across multi-account AWS Organizations workloads.
resource "aws_s3_bucket_public_access_block" "guard" {
block_public_acls = true
block_public_policy = true
}💡 Self-Explanatory Overview: In simple, everyday terms, Envelope Encryption with AWS KMS & Automatic Secrets Manager Rotation teaches you how AWS applications rotate RDS credentials and API keys automatically without redeploying application code. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply Envelope Encryption with AWS KMS & Automatic Secrets Manager Rotation in real AWS systems — specifically: Rotate RDS credentials and API keys automatically without redeploying application code, so your code stays reliable, fast, and easy to maintain in production.
What Is Envelope Encryption with AWS KMS & Automatic Secrets Manager Rotation & Why Industry Teams Use ItIn AWS Training, Envelope Encryption with AWS KMS & Automatic Secrets Manager Rotation exists for one clear real-world purpose: Rotate RDS credentials and API keys automatically without redeploying application code. Even if you come from a non-technical background, we start with the everyday real-life...
Hands-On Implementation: Envelope Encryption with AWS KMS & Automatic Secrets Manager Rotation
Build and verify a clean working module demonstrating Envelope Encryption with AWS KMS & Automatic Secrets Manager Rotation (Rotate RDS credentials and API keys automatically without redeploying appli...
Live Lab Sprint: Envelope Encryption with AWS KMS & Automatic Secrets Manager Rotation
# Envelope Encryption with AWS KMS & Automatic Secrets Manager Rotation
# Purpose: Rotate RDS credentials and API keys automatically without redeploying application code.
resource "aws_s3_bucket_public_access_block" "guard" {
block_public_acls = true
block_public_policy = true
}💡 Self-Explanatory Overview: In simple, everyday terms, AWS WAF Managed Rules, Shield DDoS Protection & VPC Endpoints (PrivateLink) teaches you how AWS applications block SQLi/XSS bot traffic at CloudFront edge and keep S3/Dynamo traffic off public internet. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply AWS WAF Managed Rules, Shield DDoS Protection & VPC Endpoints (PrivateLink) in real AWS systems — specifically: Block SQLi/XSS bot traffic at CloudFront edge and keep S3/Dynamo traffic off public internet, so your code stays reliable, fast, and easy to maintain in production.
What Is AWS WAF Managed Rules, Shield DDoS Protection & VPC Endpoints (PrivateLink) & Why Industry Teams Use ItIn AWS Training, AWS WAF Managed Rules, Shield DDoS Protection & VPC Endpoints (PrivateLink) exists for one clear real-world purpose: Block SQLi/XSS bot traffic at CloudFront edge and keep S3/Dynamo traffic off public internet. Even if you come from a non-technical background, we start with the e...
Hands-On Implementation: AWS WAF Managed Rules, Shield DDoS Protection & VPC Endpoints (PrivateLink)
Build and verify a clean working module demonstrating AWS WAF Managed Rules, Shield DDoS Protection & VPC Endpoints (PrivateLink) (Block SQLi/XSS bot traffic at CloudFront edge and keep S3/Dynamo traf...
Live Lab Sprint: AWS WAF Managed Rules, Shield DDoS Protection & VPC Endpoints (PrivateLink)
# AWS WAF Managed Rules, Shield DDoS Protection & VPC Endpoints (PrivateLink)
# Purpose: Block SQLi/XSS bot traffic at CloudFront edge and keep S3/Dynamo traffic off public internet.
resource "aws_s3_bucket_public_access_block" "guard" {
block_public_acls = true
block_public_policy = true
}💡 Self-Explanatory Overview: In simple, everyday terms, CloudTrail Audit Trails, GuardDuty Threat Detection & AWS Config Rules teaches you how AWS applications detect anomalous API calls and compliance drift within minutes. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply CloudTrail Audit Trails, GuardDuty Threat Detection & AWS Config Rules in real AWS systems — specifically: Detect anomalous API calls and compliance drift within minutes, so your code stays reliable, fast, and easy to maintain in production.
What Is CloudTrail Audit Trails, GuardDuty Threat Detection & AWS Config Rules & Why Industry Teams Use ItIn AWS Training, CloudTrail Audit Trails, GuardDuty Threat Detection & AWS Config Rules exists for one clear real-world purpose: Detect anomalous API calls and compliance drift within minutes. Even if you come from a non-technical background, we start with the everyday real-life problem first before w...
Hands-On Implementation: CloudTrail Audit Trails, GuardDuty Threat Detection & AWS Config Rules
Build and verify a clean working module demonstrating CloudTrail Audit Trails, GuardDuty Threat Detection & AWS Config Rules (Detect anomalous API calls and compliance drift within minutes.). Handle i...
Live Lab Sprint: CloudTrail Audit Trails, GuardDuty Threat Detection & AWS Config Rules
# CloudTrail Audit Trails, GuardDuty Threat Detection & AWS Config Rules
# Purpose: Detect anomalous API calls and compliance drift within minutes.
resource "aws_s3_bucket_public_access_block" "guard" {
block_public_acls = true
block_public_policy = true
}Design, implement, test, and document 'SOC2-Ready Hardened AWS Security & Secrets Architecture' applying every production concept from Module 13 (AWS Enterprise Security, KMS Encryption, Secrets Manager & WAF) of AWS Training.
Module Learning & Hands-On Objectives
💡 Self-Explanatory Overview: In simple, everyday terms, RTO vs RPO Tiers: Backup/Restore, Pilot Light, Warm Standby & Active-Active teaches you how AWS applications match business continuity SLAs to exact Route 53 failover and RDS cross-region designs. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply RTO vs RPO Tiers: Backup/Restore, Pilot Light, Warm Standby & Active-Active in real AWS systems — specifically: Match business continuity SLAs to exact Route 53 failover and RDS cross-region designs, so your code stays reliable, fast, and easy to maintain in production.
What Is RTO vs RPO Tiers: Backup/Restore, Pilot Light, Warm Standby & Active-Active & Why Industry Teams Use ItIn AWS Training, RTO vs RPO Tiers: Backup/Restore, Pilot Light, Warm Standby & Active-Active exists for one clear real-world purpose: Match business continuity SLAs to exact Route 53 failover and RDS cross-region designs. Even if you come from a non-technical background, we start with the everyda...
Hands-On Implementation: RTO vs RPO Tiers: Backup/Restore, Pilot Light, Warm Standby & Active-Active
Build and verify a clean working module demonstrating RTO vs RPO Tiers: Backup/Restore, Pilot Light, Warm Standby & Active-Active (Match business continuity SLAs to exact Route 53 failover and RDS cro...
Live Lab Sprint: RTO vs RPO Tiers: Backup/Restore, Pilot Light, Warm Standby & Active-Active
# RTO vs RPO Tiers: Backup/Restore, Pilot Light, Warm Standby & Active-Active
# Purpose: Match business continuity SLAs to exact Route 53 failover and RDS cross-region designs.
resource "aws_s3_bucket_public_access_block" "guard" {
block_public_acls = true
block_public_policy = true
}💡 Self-Explanatory Overview: In simple, everyday terms, CloudWatch Composite Alarms, Logs Insights, X-Ray Tracing & Dashboards teaches you how AWS applications pinpoint cross-service AWS latency bottlenecks and page on-call teams before outages spread. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply CloudWatch Composite Alarms, Logs Insights, X-Ray Tracing & Dashboards in real AWS systems — specifically: Pinpoint cross-service AWS latency bottlenecks and page on-call teams before outages spread, so your code stays reliable, fast, and easy to maintain in production.
What Is CloudWatch Composite Alarms, Logs Insights, X-Ray Tracing & Dashboards & Why Industry Teams Use ItIn AWS Training, CloudWatch Composite Alarms, Logs Insights, X-Ray Tracing & Dashboards exists for one clear real-world purpose: Pinpoint cross-service AWS latency bottlenecks and page on-call teams before outages spread. Even if you come from a non-technical background, we start with the everyday rea...
Hands-On Implementation: CloudWatch Composite Alarms, Logs Insights, X-Ray Tracing & Dashboards
Build and verify a clean working module demonstrating CloudWatch Composite Alarms, Logs Insights, X-Ray Tracing & Dashboards (Pinpoint cross-service AWS latency bottlenecks and page on-call teams befo...
Live Lab Sprint: CloudWatch Composite Alarms, Logs Insights, X-Ray Tracing & Dashboards
# CloudWatch Composite Alarms, Logs Insights, X-Ray Tracing & Dashboards
# Purpose: Pinpoint cross-service AWS latency bottlenecks and page on-call teams before outages spread.
resource "aws_s3_bucket_public_access_block" "guard" {
block_public_acls = true
block_public_policy = true
}💡 Self-Explanatory Overview: In simple, everyday terms, S3 Intelligent-Tiering, CloudFront Origin Shield & RDS Read Replicas teaches you how AWS applications slash egress bandwidth bills and database CPU load simultaneously. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply S3 Intelligent-Tiering, CloudFront Origin Shield & RDS Read Replicas in real AWS systems — specifically: Slash egress bandwidth bills and database CPU load simultaneously, so your code stays reliable, fast, and easy to maintain in production.
What Is S3 Intelligent-Tiering, CloudFront Origin Shield & RDS Read Replicas & Why Industry Teams Use ItIn AWS Training, S3 Intelligent-Tiering, CloudFront Origin Shield & RDS Read Replicas exists for one clear real-world purpose: Slash egress bandwidth bills and database CPU load simultaneously. Even if you come from a non-technical background, we start with the everyday real-life problem first before wr...
Hands-On Implementation: S3 Intelligent-Tiering, CloudFront Origin Shield & RDS Read Replicas
Build and verify a clean working module demonstrating S3 Intelligent-Tiering, CloudFront Origin Shield & RDS Read Replicas (Slash egress bandwidth bills and database CPU load simultaneously.). Handle...
Live Lab Sprint: S3 Intelligent-Tiering, CloudFront Origin Shield & RDS Read Replicas
# S3 Intelligent-Tiering, CloudFront Origin Shield & RDS Read Replicas
# Purpose: Slash egress bandwidth bills and database CPU load simultaneously.
resource "aws_s3_bucket_public_access_block" "guard" {
block_public_acls = true
block_public_policy = true
}💡 Self-Explanatory Overview: In simple, everyday terms, AWS Budgets, Cost Anomaly Alerts, Savings Plans & Right-Sizing Audits teaches you how AWS applications cut monthly AWS cloud spend by 30–50% without sacrificing reliability. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply AWS Budgets, Cost Anomaly Alerts, Savings Plans & Right-Sizing Audits in real AWS systems — specifically: Cut monthly AWS cloud spend by 30–50% without sacrificing reliability, so your code stays reliable, fast, and easy to maintain in production.
What Is AWS Budgets, Cost Anomaly Alerts, Savings Plans & Right-Sizing Audits & Why Industry Teams Use ItIn AWS Training, AWS Budgets, Cost Anomaly Alerts, Savings Plans & Right-Sizing Audits exists for one clear real-world purpose: Cut monthly AWS cloud spend by 30–50% without sacrificing reliability. Even if you come from a non-technical background, we start with the everyday real-life problem first bef...
Hands-On Implementation: AWS Budgets, Cost Anomaly Alerts, Savings Plans & Right-Sizing Audits
Build and verify a clean working module demonstrating AWS Budgets, Cost Anomaly Alerts, Savings Plans & Right-Sizing Audits (Cut monthly AWS cloud spend by 30–50% without sacrificing reliability.). Ha...
Live Lab Sprint: AWS Budgets, Cost Anomaly Alerts, Savings Plans & Right-Sizing Audits
# AWS Budgets, Cost Anomaly Alerts, Savings Plans & Right-Sizing Audits
# Purpose: Cut monthly AWS cloud spend by 30–50% without sacrificing reliability.
resource "aws_s3_bucket_public_access_block" "guard" {
block_public_acls = true
block_public_policy = true
}Design, implement, test, and document 'Multi-AZ/Region Failover & FinOps Cost-Governed Cloud Stack' applying every production concept from Module 14 (Multi-Region Disaster Recovery, Observability & FinOps Cost Optimization) of AWS Training.
Module Learning & Hands-On Objectives
💡 Self-Explanatory Overview: In simple, everyday terms, AWS Organizations, Service Control Policies (SCPs), IAM Permission Boundaries & OIDC teaches you how AWS applications enforce multi-account security guardrails and keyless CI/CD deployments without static access keys. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply AWS Organizations, Service Control Policies (SCPs), IAM Permission Boundaries & OIDC in real AWS systems — specifically: Enforce multi-account security guardrails and keyless CI/CD deployments without static access keys, so your code stays reliable, fast, and easy to maintain in production.
Self-Explanatory Guide: AWS Organizations, Service Control Policies (SCPs), IAM Permission Boundaries & OIDC (Plain-English & Industry Purpose)In simple, everyday terms, AWS Organizations, Service Control Policies (SCPs), IAM Permission Boundaries & OIDC teaches you how AWS applications enforce multi-account security guardrails and keyless CI/CD deployments without static access keys. Even if you have nev...
Practical Implementation: AWS Organizations, Service Control Policies (SCPs), IAM Permission Boundaries & OIDC
Implement and verify AWS Organizations, Service Control Policies (SCPs), IAM Permission Boundaries & OIDC (Enforce multi-account security guardrails and keyless CI/CD deployments without static access...
Guided Live Lab Checklist: AWS Organizations, Service Control Policies (SCPs), IAM Permission Boundaries & OIDC
# AWS Organizations, Service Control Policies (SCPs), IAM Permission Boundaries & OIDC
# Purpose: Enforce multi-account security guardrails and keyless CI/CD deployments without static access keys
def a_w_s_organizations_service(payload: dict[str, object]) -> dict[str, object]:
if not payload:
raise ValueError('Input payload cannot be empty')
return {'topic': 'AWS Organizations, Service Control Policies (SCPs), IAM Permission Boundaries & OIDC', 'verified': True, 'keys': sorted(payload.keys())}
if...💡 Self-Explanatory Overview: In simple, everyday terms, AWS KMS Customer-Managed Keys, Secrets Manager Rotation & WAF + Shield Protection teaches you how AWS applications encrypt S3, EBS, and RDS data at rest and block SQLi/bot layer-7 attacks at CloudFront/ALB. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply AWS KMS Customer-Managed Keys, Secrets Manager Rotation & WAF + Shield Protection in real AWS systems — specifically: Encrypt S3, EBS, and RDS data at rest and block SQLi/bot layer-7 attacks at CloudFront/ALB, so your code stays reliable, fast, and easy to maintain in production.
Self-Explanatory Guide: AWS KMS Customer-Managed Keys, Secrets Manager Rotation & WAF + Shield Protection (Plain-English & Industry Purpose)In simple, everyday terms, AWS KMS Customer-Managed Keys, Secrets Manager Rotation & WAF + Shield Protection teaches you how AWS applications encrypt S3, EBS, and RDS data at rest and block SQLi/bot layer-7 attacks at CloudFront/ALB. Even if you have never seen this c...
Practical Implementation: AWS KMS Customer-Managed Keys, Secrets Manager Rotation & WAF + Shield Protection
Implement and verify AWS KMS Customer-Managed Keys, Secrets Manager Rotation & WAF + Shield Protection (Encrypt S3, EBS, and RDS data at rest and block SQLi/bot layer-7 attacks at CloudFront/ALB) with...
Guided Live Lab Checklist: AWS KMS Customer-Managed Keys, Secrets Manager Rotation & WAF + Shield Protection
# AWS KMS Customer-Managed Keys, Secrets Manager Rotation & WAF + Shield Protection
# Purpose: Encrypt S3, EBS, and RDS data at rest and block SQLi/bot layer-7 attacks at CloudFront/ALB
def a_w_s_k_m_s_customer_managed(payload: dict[str, object]) -> dict[str, object]:
if not payload:
raise ValueError('Input payload cannot be empty')
return {'topic': 'AWS KMS Customer-Managed Keys, Secrets Manager Rotation & WAF + Shield Protection', 'verified': True, 'keys': sorted(payload.keys())}
if __name__ == '...💡 Self-Explanatory Overview: In simple, everyday terms, AWS Cost Explorer, Budgets, Savings Plans, S3 Intelligent-Tiering & Right-Sizing teaches you how AWS applications prevent surprise cloud bills with automated anomaly alerts and storage/compute lifecycle rules. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply AWS Cost Explorer, Budgets, Savings Plans, S3 Intelligent-Tiering & Right-Sizing in real AWS systems — specifically: Prevent surprise cloud bills with automated anomaly alerts and storage/compute lifecycle rules, so your code stays reliable, fast, and easy to maintain in production.
Self-Explanatory Guide: AWS Cost Explorer, Budgets, Savings Plans, S3 Intelligent-Tiering & Right-Sizing (Plain-English & Industry Purpose)In simple, everyday terms, AWS Cost Explorer, Budgets, Savings Plans, S3 Intelligent-Tiering & Right-Sizing teaches you how AWS applications prevent surprise cloud bills with automated anomaly alerts and storage/compute lifecycle rules. Even if you have never seen this...
Practical Implementation: AWS Cost Explorer, Budgets, Savings Plans, S3 Intelligent-Tiering & Right-Sizing
Implement and verify AWS Cost Explorer, Budgets, Savings Plans, S3 Intelligent-Tiering & Right-Sizing (Prevent surprise cloud bills with automated anomaly alerts and storage/compute lifecycle rules) w...
Guided Live Lab Checklist: AWS Cost Explorer, Budgets, Savings Plans, S3 Intelligent-Tiering & Right-Sizing
# AWS Cost Explorer, Budgets, Savings Plans, S3 Intelligent-Tiering & Right-Sizing
# Purpose: Prevent surprise cloud bills with automated anomaly alerts and storage/compute lifecycle rules
def a_w_s_cost_explorer(payload: dict[str, object]) -> dict[str, object]:
if not payload:
raise ValueError('Input payload cannot be empty')
return {'topic': 'AWS Cost Explorer, Budgets, Savings Plans, S3 Intelligent-Tiering & Right-Sizing', 'verified': True, 'keys': sorted(payload.keys())}
if __name__ == '__main_...Architect, implement, test, and document 'Least-Privilege AWS Organization SCP, KMS Envelope Encryption & Budget Guard' applying every bullet-wise engineering concept from Module 15 (AWS Cloud Security Governance, KMS Encryption & Cost FinOps Architecture) of AWS Training.
Module Learning & Hands-On Objectives
💡 Self-Explanatory Overview: In simple, everyday terms, Disaster Recovery Tiers: Backup & Restore, Pilot Light, Warm Standby & Multi-Site Active-Active teaches you how AWS applications match exact RTO and RPO business targets to cost-effective AWS multi-region architectures. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply Disaster Recovery Tiers: Backup & Restore, Pilot Light, Warm Standby & Multi-Site Active-Active in real AWS systems — specifically: Match exact RTO and RPO business targets to cost-effective AWS multi-region architectures, so your code stays reliable, fast, and easy to maintain in production.
Self-Explanatory Guide: Disaster Recovery Tiers: Backup & Restore, Pilot Light, Warm Standby & Multi-Site Active-Active (Plain-English & Industry Purpose)In simple, everyday terms, Disaster Recovery Tiers: Backup & Restore, Pilot Light, Warm Standby & Multi-Site Active-Active teaches you how AWS applications match exact RTO and RPO business targets to cost-effective AWS multi-region architectures....
Practical Implementation: Disaster Recovery Tiers: Backup & Restore, Pilot Light, Warm Standby & Multi-Site Active-Active
Implement and verify Disaster Recovery Tiers: Backup & Restore, Pilot Light, Warm Standby & Multi-Site Active-Active (Match exact RTO and RPO business targets to cost-effective AWS multi-region archit...
Guided Live Lab Checklist: Disaster Recovery Tiers: Backup & Restore, Pilot Light, Warm Standby & Multi-Site Active-Active
# Disaster Recovery Tiers: Backup & Restore, Pilot Light, Warm Standby & Multi-Site Active-Active
# Purpose: Match exact RTO and RPO business targets to cost-effective AWS multi-region architectures
def disaster_recovery_tiers(payload: dict[str, object]) -> dict[str, object]:
if not payload:
raise ValueError('Input payload cannot be empty')
return {'topic': 'Disaster Recovery Tiers: Backup & Restore, Pilot Light, Warm Standby & Multi-Site Active-Active', 'verified': True, 'keys': sorted(payload.keys...💡 Self-Explanatory Overview: In simple, everyday terms, Centralized Observability with CloudWatch Embedded Metrics, X-Ray Tracing & CloudTrail teaches you how AWS applications correlate API latency, Lambda cold starts, and IAM audit trails during live incident triage. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply Centralized Observability with CloudWatch Embedded Metrics, X-Ray Tracing & CloudTrail in real AWS systems — specifically: Correlate API latency, Lambda cold starts, and IAM audit trails during live incident triage, so your code stays reliable, fast, and easy to maintain in production.
Self-Explanatory Guide: Centralized Observability with CloudWatch Embedded Metrics, X-Ray Tracing & CloudTrail (Plain-English & Industry Purpose)In simple, everyday terms, Centralized Observability with CloudWatch Embedded Metrics, X-Ray Tracing & CloudTrail teaches you how AWS applications correlate API latency, Lambda cold starts, and IAM audit trails during live incident triage. Even if you have never...
Practical Implementation: Centralized Observability with CloudWatch Embedded Metrics, X-Ray Tracing & CloudTrail
Implement and verify Centralized Observability with CloudWatch Embedded Metrics, X-Ray Tracing & CloudTrail (Correlate API latency, Lambda cold starts, and IAM audit trails during live incident triage...
Guided Live Lab Checklist: Centralized Observability with CloudWatch Embedded Metrics, X-Ray Tracing & CloudTrail
# Centralized Observability with CloudWatch Embedded Metrics, X-Ray Tracing & CloudTrail
# Purpose: Correlate API latency, Lambda cold starts, and IAM audit trails during live incident triage
def centralized_observability_with(payload: dict[str, object]) -> dict[str, object]:
if not payload:
raise ValueError('Input payload cannot be empty')
return {'topic': 'Centralized Observability with CloudWatch Embedded Metrics, X-Ray Tracing & CloudTrail', 'verified': True, 'keys': sorted(payload.keys())}
if...💡 Self-Explanatory Overview: In simple, everyday terms, AWS Solutions Architect Scenario Walkthroughs & Production Cutover Checklists teaches you how AWS applications solve real SAA-C03 architecture trade-off questions across networking, storage, and serverless. Even if you have never seen this concept before, your trainer explains the real-life problem first, writes clean AWS IAM, STS & KMS, Amazon S3 & CloudFront CDN, Amazon EC2, EBS & ALB code live on screen, and shows what breaks in production if this step is skipped.
🎯 For What Purpose: To understand and apply AWS Solutions Architect Scenario Walkthroughs & Production Cutover Checklists in real AWS systems — specifically: Solve real SAA-C03 architecture trade-off questions across networking, storage, and serverless, so your code stays reliable, fast, and easy to maintain in production.
Self-Explanatory Guide: AWS Solutions Architect Scenario Walkthroughs & Production Cutover Checklists (Plain-English & Industry Purpose)In simple, everyday terms, AWS Solutions Architect Scenario Walkthroughs & Production Cutover Checklists teaches you how AWS applications solve real SAA-C03 architecture trade-off questions across networking, storage, and serverless. Even if you have never seen this conce...
Practical Implementation: AWS Solutions Architect Scenario Walkthroughs & Production Cutover Checklists
Implement and verify AWS Solutions Architect Scenario Walkthroughs & Production Cutover Checklists (Solve real SAA-C03 architecture trade-off questions across networking, storage, and serverless) with...
Guided Live Lab Checklist: AWS Solutions Architect Scenario Walkthroughs & Production Cutover Checklists
# AWS Solutions Architect Scenario Walkthroughs & Production Cutover Checklists
# Purpose: Solve real SAA-C03 architecture trade-off questions across networking, storage, and serverless
def a_w_s_solutions_architect(payload: dict[str, object]) -> dict[str, object]:
if not payload:
raise ValueError('Input payload cannot be empty')
return {'topic': 'AWS Solutions Architect Scenario Walkthroughs & Production Cutover Checklists', 'verified': True, 'keys': sorted(payload.keys())}
if __name__ == '__main_...Architect, implement, test, and document 'Multi-Region Failover Architecture Blueprint & CloudWatch Alarm Runbook' applying every bullet-wise engineering concept from Module 16 (AWS Well-Architected Disaster Recovery, Observability & SAA-C03 Scenarios) of AWS Training.
Linux & Cloud Networking
OS & Scripting
AWS EC2, S3, VPC & Route53
Cloud Infra
AWS IAM, KMS, WAF & STS
App & Cloud Security
Amazon RDS, Aurora & DynamoDB
Enterprise RDBMS
AWS Lambda, SQS, SNS & API GW
Serverless
Amazon ECR, ECS & EKS
Containers
Terraform Cloud IaC
Infra as Code
CloudWatch & Cost FinOps
Metrics & Alerts
LeetCode Problem Solving
Trainer Coding Prep
HackerRank Coding Prep
Trainer Coding PrepInstead of buying physical servers in an office, modern companies rent elastic cloud servers, storage, and security from Amazon Web Services (AWS) — powering Netflix, Airbnb, Zomato, and Swiggy.
Highly accessible for BOTH non-coding IT aspirants (cloud admin/support/ops roles require minimal coding!) and software developers wanting cloud architecture mastery.
Key Engineering Capabilities You Will Build:
Purpose: Prevent cloud data breaches and unauthorized access across teams and services.
Purpose: Isolate private backend servers safely while scaling capacity automatically during traffic spikes.
Purpose: Store terabytes durably at low cost and deliver assets globally in milliseconds.
Purpose: Run high-availability production databases with automated failover and zero data loss.
Taught live by active Working IT Professionals between 7:00 AM and 8:00 PM IST (choose any slot based on trainer availability).
Weekdays (Mon – Fri): 1 Hour / Day • 7:00 AM to 8:00 PM IST (choose any slot based on trainer availability)
Weekends (Sat – Sun): 2 Hours / Day • 7:00 AM to 8:00 PM IST (choose any slot based on trainer availability)
AWS Training — Weekday Live Online Cohort (₹5,999 + 18% GST)
Mon - Fri (Weekday Live • 1 Hr/Day) • 07:00 AM - 08:00 PM IST (1 Hr/Day • Any Slot per Trainer Availability)
Starts: 10 Oct 2026
AWS Training — Weekend Live Online Cohort (₹5,999 + 18% GST)
Sat - Sun (Weekend Live • 2 Hrs/Day) • 07:00 AM - 08:00 PM IST (2 Hrs/Day • Any Slot per Trainer Availability)
Starts: 05 Nov 2026
LeetCode Support
HackerRank Support
Enrolled students receive live trainer mentorship to break down algorithmic/query patterns, edge cases, and optimal complexity so you can confidently crack LeetCode and HackerRank problems in Python 3.12 (Boto3 SDK & AWS Lambda).
🚀 Live Client Production Project + Internship Letter
After completing all 16 progressive hands-on module projects during live classes, students join our mentor-led Client Production Sprint to build, test, and deploy "CloudShield Multi-AZ Auto-Scaling SaaS Infrastructure & Disaster Recovery Platform" to live cloud production — earning an Official Verified Internship Letter detailing their exact technical contributions.
Domain: Cloud-Native FinTech & SaaS Client Infrastructure • Infra: AWS VPC + ALB + EC2 Auto Scaling + RDS Multi-AZ + S3 + CloudFront + IAM
Certified on Your Official Internship Confirmation Letter:
See the exact job positions and realistic salary packages unlocked by AWS Training, plus which specialized MockAttempt Academy courses to pair next to qualify for higher-paying multi-stack engineering roles.
VPC, IAM, EC2/ALB, S3/CloudFront, RDS Multi-AZ & live AWS client architecture proof.
IaC automation, serverless architectures, security hardening & cost governance.
Unlocked rapidly by combining AWS with Docker, Kubernetes & DevOps CI/CD!
Why Learn Next (For What Purpose): Run enterprise containerized microservices on AWS EKS / Kubernetes clusters.
Why Learn Next (For What Purpose): Automate AWS infrastructure provisioning with Terraform and GitHub Actions CI/CD pipelines.
Why Learn Next (For What Purpose): Write Python Boto3 scripts and AWS Lambda functions to automate cloud security and operations.
MockAttempt Academy keeps production-grade AWS Cloud & Solutions Architecture training ultra-affordable at ₹5,999 + 18% GST so every learner gets 10,440 MCQs, 16 Capstone Projects, Live Client Production deployment, and spoken MockAttempt AI interview coaching.
Regular Skill Courses offer both Weekday Live Batches (Monday–Friday, 1 Hour/Day between 7:00 AM and 8:00 PM IST) and Weekend Live Batches (Saturday–Sunday, 2 Hours/Day between 7:00 AM and 8:00 PM IST) taught 100% by active Working IT Professionals — students can choose any convenient slot based on trainer availability.
Instead of passive pre-recorded videos, you code live with senior architects, monitor 100% of syllabus progress transparently, build 16 progressive Module Projects during training, and deploy a real Live Client Project to production at the end of the course — earning both a Barcode Graduation Certificate and an Official Project Internship Confirmation Letter.
Across all 42 syllabus topics in 16 modules, this course includes 244 Timed Topic Mock Tests (10,440 curated MCQs with detailed explanations) and 244 Spoken Voice + MockAttempt AI Technical Interview rounds — ensuring 100% of topics are assessed.
The AI Interviewer speaks each question aloud via Text-to-Speech, listens via microphone Speech-to-Text, normalizes spoken technical syntax, and sends your transcript to the MockAttempt AI verification agent for scoring and follow-up probing.
All MockAttempt Tech Academy fees are 100% fixed and non-negotiable (₹5,999 + 18% GST). We never inflate fake MRPs only to bargain discounts because we refuse to compromise on Senior Industry Expert trainers, small interactive live batches, real cloud/repository labs, daily assessments, or placement mentorship.
Yes! Because this curriculum includes Python 3.12 (Boto3 SDK & AWS Lambda), your trainer provides guided problem-solving support to break down patterns, edge cases, and optimal complexity so you can confidently crack LeetCode and HackerRank problems.
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