AWS Certified Solutions Architect & Cloud Engineering Master Program
100% Placement Guaranteed | Production Cloud Engineering, AWS Solutions Architecture, Terraform IaC, Kubernetes, DevOps & SAA-C03 Certification | 100% Placement Guaranteed* (6 Months Fees Refund*)
Technologies You Will Master
100% Fees Refund* If Not Placed Within 6 Months
We believe in real career outcomes, not just empty certificates. If you complete the course modules, project milestones, and mock interview assessments but do not secure an IT engineering placement within 6 Months of course completion, MockAttempt guarantees a 100% full refund of your tuition fees* directly to your bank account with zero deductions.
Program Overview & Architectural Focus
### 🛡️ 100% Placement Assurance & Fees Refund Guarantee* (6-Month Window)
MockAttempt officially guarantees that upon graduating from this program and clearing the Job-Ready Assessment Pipeline, you will secure an IT engineering placement within 6 Months of course completion. If you are not placed within this 6-month post-completion period, you receive a **100% full refund of your course tuition fees*** directly into your bank account.
### 🎯 Multi-Dimensional Mastery & Assessment Framework (All Topics)
To ensure every graduate is genuinely world-class and job-ready for tier-1 enterprises:
- **Daily Topic Mock Tests (>98% Score Required)**: For every daily topic, students must score over 98% in proctored mock assessments. Students have access to **100+ dedicated Mock Tests per topic** to practice thoroughly.
- **Daily Topic-Wise AI Technical Interviews (>98% Score Required)**: Candidates undergo targeted AI technical voice interviews strictly testing that day's concept, requiring a >98% score.
- **Final Exit Benchmark (≥95% Minimum Score)**: To prove successful program completion and activate placement drives, candidates must achieve at least 95% in the comprehensive Final AI Interview and Mock Exam.
- **Multiple Re-Attempt Opportunities**: Students receive multiple chances to re-take assessments. Our goal is not just testing rote theoretical concepts, but rigorously developing **logical skills, problem-solving skills, and communication/articulation skills**.
*\*Terms & Conditions Apply. Subject to program milestones, attendance, project defense, topic mastery criteria, and active participation in placement drives.*
### 🎯 Target Engineering Roles & Audience
Aspiring AWS Cloud Engineers, Cloud Solutions Architects, Cloud Infrastructure Engineers, DevOps Engineers, Site Reliability Engineers, Systems Administrators, and Software Engineers seeking enterprise cloud architecture mastery.
Enterprise Technologies & Toolchain Mastered
Production-level toolchain and engineering ecosystems practiced during hands-on lab sessions, code reviews, and capstone engineering.
Structured Learning Path Roadmap (10 Phases)
Progressive pedagogical journey designed by staff engineers to transition candidates from fundamentals to enterprise defense.
Phase 1: Cloud Paradigms & Systems Architecture Foundations
Phase 2: Linux Administration & Enterprise Network Engineering
Phase 3: AWS Core Services, IAM Governance & VPC Networking
Phase 4: Elastic Compute, Scalable Storage & Managed Databases
Phase 5: Serverless Architecture & Asynchronous Event-Driven Systems
Phase 6: Containers, Orchestration & Amazon EKS Kubernetes
Phase 7: Infrastructure as Code, DevOps & CI/CD Pipelines
Phase 8: Cloud Security, Full-Stack Observability & Disaster Recovery
Phase 9: Well-Architected Framework, System Design & 12 Architecture Cases
Phase 10: SAA-C03 Certification Prep, Capstone Defense & Career Placement
Daily Topic Mastery (>98%), AI Interviews & Exit Benchmark (≥95%)
Our goal is never simple rote memorization. MockAttempt is engineered to forge elite software professionals with world-class logical skills, problem-solving skills, and architectural communication clarity. For each topic and before graduating, students must clear our rigorous multi-dimensional evaluation pipeline:
For every single day's lesson/topic, candidates must score over 98% in proctored mock assessments. Students have access to 100+ dedicated Mock Tests per topic to practice edge cases, algorithmic variations, and syntax nuances until full clarity is proven.
Students undergo daily interactive, topic-specific AI voice and coding technical interviews. The AI strictly focuses on that day's concept, posing Socratic follow-ups to evaluate depth, articulation, and reasoning speed with a >98% score benchmark.
At the conclusion of the program, students must achieve a minimum of 95% in the comprehensive Final AI Technical Interview and Grand Mock Assessment to certify completion and qualify for corporate recruitment drives and the 100% Fees Refund Guarantee*.
Students receive multiple opportunities to re-attempt tests and interviews. The objective is not punitive but pedagogical: detailed telemetry, Big-O feedback, and AI hints help candidates learn from mistakes and cement true conceptual mastery.
Comprehensive Curriculum & Modules (63 Modules)
Hands-on engineering syllabus with real production implementations, daily mock tests & AI defense.
In this module, students master Introduction to Cloud Computing & AWS Global Infrastructure through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Core definitions of cloud computing, traditional data centers vs cloud economics, CAPEX to OPEX transition, cloud deployment models (public, private, hybrid, multi-cloud), and the AWS shared responsibility model.
Key architectural tenets: vertical vs horizontal scalability, elasticity dynamics, high availability metrics, fault tolerance boundaries, disaster recovery objectives (RPO/RTO), and pay-as-you-go financial models.
Global cloud footprint: AWS Regions, Availability Zones (AZs), Local Zones, Wavelength Zones, Edge Locations (Points of Presence), Regional Edge Caches, and global low-latency backbone connectivity.
In this module, students master IT Infrastructure, Virtualization & Systems Fundamentals through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Bare-metal architecture: CPU architectures (x86 vs ARM/Graviton), memory hierarchies, storage buses, Type-1 (bare-metal) vs Type-2 hypervisors, and virtualization overhead.
VM abstractions, guest operating systems, kernel architecture, block storage vs object storage vs file systems, inode mechanics, and application runtime isolation.
Process lifecycles, daemon services, system threads, TCP/UDP port binding, client-server handshake, reverse proxies, and tiered application infrastructure architecture.
In this module, students master Linux Fundamentals & Cloud Operating System Mechanics through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Enterprise distributions (Amazon Linux 2023, Ubuntu, RHEL), Filesystem Hierarchy Standard (/etc, /var, /opt, /proc, /sys), navigation, file creation, and directory operations.
Users, groups, /etc/passwd, /etc/shadow, standard POSIX permissions (read, write, execute), octal modes (chmod), ownership (chown, chgrp), and sudo privilege escalation.
Essential Linux command-line tools: ls, cd, cp, mv, rm, find, grep, awk, sed, curl, wget, ps, top, df, du, netstat, ss, and environment variables.
In this module, students master Enterprise Linux Administration, Troubleshooting & Shell Mastery through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
SSH daemon configuration (/etc/ssh/sshd_config), key pair generation (ed25519, RSA), ssh-agent, bastion jumping, secure file copy (scp, sftp), and remote command execution.
Service lifecycles, unit files (/etc/systemd/system/), systemctl operations, journalctl log inspection, automated job scheduling with crontab, and at daemon execution.
Block storage management, fdisk, parted, Logical Volume Management (PV, VG, LV), formatting (ext4, XFS), fstab auto-mounting, memory pressure triage, and system rescue modes.
In this module, students master Networking Essentials, OSI/TCP-IP Models & Network Protocols through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Encapsulation and de-encapsulation, physical transmission, data link frames, MAC addressing, network IP routing, transport segment multiplexing, and application protocols.
IPv4 classful vs classless addressing, IPv6 128-bit architecture, port ranges (well-known, registered, dynamic), TCP three-way handshake, connection teardown, and UDP stateless streaming.
Domain Name System resolution hierarchy (root, TLD, authoritative), DHCP lease allocation, HTTP request/response semantics, status codes, and TLS 1.3 handshake cryptographic negotiation.
In this module, students master Enterprise Network Design, CIDR, Subnetting & Routing Architecture through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Classless Inter-Domain Routing (CIDR) notation, subnet masks, binary arithmetic, calculating network IDs, broadcast addresses, usable host capacity, and non-overlapping IP address planning.
Dual-tier and three-tier network topologies, default gateways, route table evaluation order, destination targets, local routing, and internet egress isolation.
Stateful vs stateless inspection, network firewalls, NAT gateways, load balancer concepts, ping, traceroute, mtr, tcpdump, and netcat network diagnostic triage.
In this module, students master AWS Account Management, Organizations, Billing & CLI / SDK through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
AWS account boundaries, multi-account strategy, root user hardening, AWS Organizations, Organizational Units (OUs), and Service Control Policies (SCPs) guardrails.
Console navigation, AWS CloudShell browser-based terminal, service quota management, requesting limit increases, and AWS Health Dashboard notifications.
Installing AWS CLI v2, named profiles, credentials management (~/.aws/credentials), session tokens, AWS SDK concepts (Boto3, Node.js AWS SDK), and AWS pricing dimensions.
In this module, students master AWS Identity & Access Management (IAM), Least Privilege & Security Governance through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
IAM entities, root vs IAM users, group memberships, assume-role trust policies, service-linked roles, and EC2 instance profiles for zero-credential compute access.
IAM JSON policy anatomy (Version, Statement, Effect, Action, Resource, Condition), explicit deny evaluation, identity-based vs resource-based policies, and permission boundaries.
Cross-account STS AssumeRole delegation, enforcing Multi-Factor Authentication via IAM conditions, access key lifecycle, automated credential rotation, and IAM Credential Reports.
In this module, students master Amazon VPC Fundamentals, Subnetting, Gateways & Security Groups through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
VPC CIDR block allocation (/16 to /28), creating public and private subnets across multiple AZs, reserving AWS networking IPs (.0 to .3 and .255), and VPC flow logs.
Attaching Internet Gateways (IGWs), allocating Elastic IPs, provisioning highly available NAT Gateways in public subnets, and configuring public/private route tables.
Stateful Security Groups (allow-only, instance level) vs stateless Network ACLs (allow/deny, subnet level, numbered rule evaluation), and egress filtering patterns.
In this module, students master Advanced VPC Architecture, Peering, Transit Gateway & PrivateLink through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Non-overlapping VPC peering connections, routing table updates, inter-region peering encryption, non-transitive peering limitations, and traffic costs.
Transit Gateway (TGW) attachments, route tables, multi-VPC hub-and-spoke topologies, cross-account RAM sharing, and centralized internet egress architecture.
Gateway VPC Endpoints (S3, DynamoDB) with route table integration, Interface Endpoints (PrivateLink) with ENI injection, Site-to-Site IPsec VPN, and AWS Direct Connect dedicated fiber.
In this module, students master Amazon EC2 Architecture, Compute Instances, AMIs & Lifecycle through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
General Purpose (T4g, M6i), Compute Optimized (C7g), Memory Optimized (R6i), Storage Optimized (I3en), x86 vs AWS Graviton3 ARM silicon, and vCPU sizing.
Custom AMIs, AWS Marketplace AMIs, automated AMI creation with EC2 Image Builder, SSH key pairs, User Data boot scripts, and Instance Metadata Service (IMDSv2) token security.
Pricing optimization: On-Demand flexible workloads, Spot Instances for fault-tolerant batch processing, Standard vs Convertible Reserved Instances (RIs), and Compute vs EC2 Instance Savings Plans.
In this module, students master Elastic Compute Auto Scaling, Launch Templates & Scaling Policies through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Launch configuration deprecation, Launch Templates (versioning, mixed instance types, spot allocation strategies), Auto Scaling Group min/max/desired capacities, and cooldown timers.
Target tracking policies (CPU utilization, ALB request count per target), step scaling with CloudWatch alarms, scheduled scaling for predictable traffic, and predictive scaling algorithms.
EC2 status checks vs ELB health checks, graceful instance termination, lifecycle hooks (launching/terminating states), zero-downtime rolling instance refreshes, and capacity rebalancing.
In this module, students master Elastic Load Balancing (ALB, NLB, GLB) & High Availability Traffic Management through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
ALB listeners, target groups, path-based routing, host-based routing, HTTP header matching, HTTP to HTTPS redirection, and WebSockets / gRPC support.
NLB connection handling, millions of requests per second, static Elastic IPs per AZ, TCP/UDP/TLS termination, and preserving source client IP addresses.
ACM SSL certificate integration, Server Name Indication (SNI) multi-domain hosting, sticky sessions (cookie affinity), and Gateway Load Balancers for third-party virtual appliance inspection.
In this module, students master Amazon S3 Object Storage, Storage Classes, Lifecycle & Security through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Bucket naming rules, global namespace, object keys, metadata, versioning, multipart uploads for multi-gigabyte files, and static website hosting.
S3 Standard, Intelligent-Tiering, Standard-IA, One Zone-IA, Glacier Instant Retrieval, Glacier Flexible Retrieval, Glacier Deep Archive, and automated transition/expiration lifecycle policies.
Server-Side Encryption (SSE-S3, SSE-KMS, SSE-C), Bucket Policies, Block Public Access controls, Access Control Lists (ACLs), S3 Object Lock, and generating time-limited presigned URLs.
In this module, students master Amazon Elastic Block Store (EBS) Volumes, Snapshots & Performance through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
General Purpose SSD (gp3 baseline 3,000 IOPS / 125 MB/s), Provisioned IOPS SSD (io2 Block Express for sub-millisecond latencies), Throughput Optimized HDD (st1), and Cold HDD (sc1).
Point-in-time incremental snapshots, S3 snapshot durability, fast snapshot restore (FSR), Amazon Data Lifecycle Manager (DLM) backup automation, and cross-region snapshot copying.
KMS envelope encryption, encrypting unencrypted volumes via snapshots, EBS Multi-Attach on io2 volumes, and elastic volume modifications (size, IOPS, throughput) without downtime.
In this module, students master Amazon Elastic File System (EFS) Shared Distributed Cloud Storage through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Fully managed elastic NFSv4 shared file system, mount targets across multiple AZs, POSIX compliance, Linux permissions, and concurrent multi-EC2 instance access.
General Purpose vs Max I/O performance modes, Bursting Throughput vs Elastic Throughput vs Provisioned Throughput, and latency optimization for distributed workloads.
Automated tiering to EFS Infrequent Access (EFS IA) and EFS Archive, lifecycle transition policies, backup integration with AWS Backup, and hybrid on-premises mounting via Direct Connect.
In this module, students master Managed Relational Databases: Amazon RDS & High Availability Amazon Aurora through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Supported engines (PostgreSQL, MySQL, MariaDB, SQL Server, Oracle), instance classes, storage auto-scaling, DB parameter groups, and option groups.
Synchronous physical replication to standby instance in secondary AZ, automatic DNS failover, zero data loss, maintenance windows, and automated snapshots.
Distributed log-structured storage architecture, 6 storage copies across 3 AZs, up to 15 auto-scaling read replicas, sub-second failover, Aurora Serverless v2, and Aurora Global Database replication.
In this module, students master NoSQL Databases at Scale: Amazon DynamoDB Architecture & Global Tables through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Key-value and document data model, primary key design (partition key only vs composite partition + sort key), partitions, hash distribution, and schema-less item attributes.
Local Secondary Indexes (LSI - shared partition key, alternative sort key, created at table creation) vs Global Secondary Indexes (GSI - custom partition and sort key, asynchronous replication).
Provisioned capacity with auto-scaling vs On-Demand capacity, Read/Write Capacity Units (RCUs/WCUs), Time to Live (TTL) automated expiration, DynamoDB Streams, and multi-region active-active Global Tables.
In this module, students master In-Memory Distributed Caching: Amazon ElastiCache (Redis & Memcached) through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Sub-millisecond read latency, caching design patterns (Cache-Aside / Lazy Loading vs Write-Through), cache stampede mitigation, and TTL expiration strategies.
Redis data structures (strings, hashes, lists, sets, sorted sets), primary-replica cluster topologies, Multi-AZ with automatic failover, cluster mode enabled (sharding across slots), and backups.
Distributed session storage for stateless compute, Redis Pub/Sub capabilities, comparing Redis (rich data structures, persistence, replication) vs Memcached (pure multi-threaded simple caching).
In this module, students master Serverless Compute: AWS Lambda Architecture, Runtime & Concurrency through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Function anatomy: entry point handler, event and context objects, supported runtimes (Python, Node.js, Java, Go, custom runtimes), and memory/vCPU proportional allocation.
Function virtualization lifecycle, cold start latency mitigation, init phase optimization, reusing execution context connections, and Provisioned Concurrency for zero-cold-start performance.
Function execution roles vs resource-based invocation policies, modular Lambda Layers for shared dependencies, VPC ENI attachment mechanics, and ephemeral storage (/tmp up to 10 GB).
In this module, students master Modern API Management: Amazon API Gateway (REST, HTTP & WebSocket) through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Comparing feature sets, HTTP APIs (low latency, cost-effective, CORS, OIDC), REST APIs (advanced caching, request validation, WAF, API keys), and WebSocket APIs for full-duplex communication.
Resources, HTTP methods, stage deployments (dev, stage, prod), stage variables, mapping templates (VTL), and canary release deployments with gradual traffic shifting.
Securing API endpoints using IAM credentials, Amazon Cognito User Pool authorizers, custom Lambda authorizers (token / request-based), usage plans, and token bucket rate throttling.
In this module, students master Event-Driven Serverless Architectures & Asynchronous Decoupling through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Coupling hazards in synchronous HTTP architectures, microservices decoupling, eventual consistency, idempotency keys, and error handling in event-driven systems.
Push invocation models (API Gateway, SNS, S3, CloudWatch Events) vs poll-based Event Source Mappings (SQS, DynamoDB Streams, Kinesis, Kafka), and batch window tuning.
Asynchronous failure handling, maximum retry attempts, message age limits, configuring Dead-Letter Queues (SQS/SNS), and Lambda On-Failure / On-Success Destinations.
In this module, students master Message Queuing: Amazon SQS (Standard, FIFO & Dead-Letter Queues) through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Distributed message queue, nearly unlimited throughput, at-least-once message delivery, best-effort message ordering, message deduplication challenges, and payload limits.
Strict First-In-First-Out delivery, exactly-once processing, Message Group ID for partitioned ordering, Message Deduplication ID, and throughput scaling with high-throughput FIFO.
Visibility timeout mechanics, extending message visibility during processing, short polling vs long polling (WaitTimeSeconds = 20), redrive policies, and DLQ error analysis.
In this module, students master Pub/Sub Messaging: Amazon SNS Fan-Out & Multi-Channel Notifications through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Publish/Subscribe design pattern, SNS topics (Standard vs FIFO), message publication, subscriber protocols (SQS, Lambda, HTTP/HTTPS endpoints, Email, SMS, Mobile Push).
Decoupling microservices by fanning out a single published message to multiple SQS queues for parallel asynchronous consumption by different downstream systems.
Subscription filter policies based on message attributes, FIFO SNS ordering, message encryption with KMS, and topic access policies restricting publishing rights.
In this module, students master Enterprise Event Streaming: Amazon EventBridge Buses & Rules through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Serverless event bus, default event bus for AWS service events, custom event buses for enterprise applications, partner event sources (Datadog, PagerDuty), and global endpoints.
Declarative JSON event pattern matching (source, detail-type, prefix, numeric range), routing events to 30+ AWS targets (Lambda, Step Functions, SQS, ECS tasks, API destinations).
Transforming event payloads before dispatching to targets, target-level DLQs, Amazon EventBridge Pipes for point-to-point integrations with built-in filtering and enrichment, and Schema Registry.
In this module, students master Distributed Event Streaming: Apache Kafka & Amazon Managed Streaming for Kafka (MSK) through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Distributed commit log architecture, event publishing, topics partitioned for parallel consumption, consumer groups, offsets, replication factor, and high-throughput streaming.
Fully managed Apache Kafka clusters on AWS, broker distribution across multiple AZs, automatic broker replacement, storage auto-scaling, and Zookeeper vs Kraft metadata mode.
Authentication via IAM, TLS encryption in transit and at rest with KMS, VPC networking, connecting Lambda triggers, and streaming data with MSK Connect.
In this module, students master Docker Containerization Fundamentals, Dockerfile & Multi-Stage Builds through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Linux namespaces (PID, NET, IPC, MNT, UTS), cgroups resource throttling, container immutability, image layer caching, and comparing containers to virtual machines.
Writing minimal, hardened Dockerfiles: base image selection (Alpine, Distroless), multi-stage compilation builds, non-root user execution, .dockerignore, and layer minimization.
Bridge, host, and overlay networks; bind mounts vs managed volumes for persistent data; and orchestrating multi-container stacks with Docker Compose.
In this module, students master Container Image Management: Amazon Elastic Container Registry (ECR) through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Private and public container registries, authentication tokens via AWS CLI (aws ecr get-login-password), pushing and pulling container images, and tag immutability.
Enhanced vulnerability scanning powered by Amazon Inspector (CVE detection, severity scoring), automated scan-on-push, and continuous vulnerability monitoring.
Automating repository hygiene: purging untagged images, retaining last N images via lifecycle rules, cross-region replication for global deployments, and cross-account access policies.
In this module, students master Container Orchestration: Amazon ECS, Task Definitions & AWS Fargate through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
ECS control plane, Task Definitions (JSON blueprint specifying CPU, memory, container definitions, port mappings, log drivers), Tasks vs continuous Services.
Managing container compute: EC2 instance clusters with Capacity Providers and Auto Scaling vs serverless AWS Fargate (zero server management, pay-per-vCPU-second).
awsvpc network mode (dedicated ENI per task), Application Load Balancer target group registration, dynamic port mapping, and Target Tracking Service Auto Scaling based on CPU/memory.
In this module, students master Enterprise Kubernetes on Cloud: Amazon Elastic Kubernetes Service (EKS) through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Kubernetes architectural components: API server, etcd, scheduler, controller-manager, kubelet, kube-proxy; AWS managed control plane across 3 AZs; and kubectl CLI configuration.
Pod lifecycles, declarative Deployments with rolling updates, Service abstractions (ClusterIP, NodePort, LoadBalancer), and Ingress controllers (AWS Load Balancer Controller).
Managed Node Groups vs Karpenter dynamic auto-provisioning, IAM Roles for Service Accounts (IRSA) with OIDC federation, ConfigMaps, and AWS Secrets Store CSI Driver integration.
In this module, students master Infrastructure as Code (IaC): AWS CloudFormation Templates & Drift Detection through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
CloudFormation template anatomy: Parameters, Resources, Outputs, Mappings, Conditions, and Metadata; intrinsic functions (Ref, Fn::GetAtt, Fn::Sub, Fn::Join).
Creating, updating, and deleting stacks; previewing changes with Change Sets; modularizing architecture with Nested Stacks; and cross-stack references via exported outputs.
Detecting manual infrastructure changes with drift detection, automated rollback on CloudWatch alarm breaches, deletion policies (Retain, Snapshot), and multi-account StackSets.
In this module, students master Enterprise Infrastructure as Code: HashiCorp Terraform Architecture & State Management through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Terraform architecture: init, plan, apply, destroy lifecycle; HCL syntax; variables, outputs, local values; and configuring the official AWS Provider with default tags.
The terraform.tfstate file, remote backend configuration with Amazon S3, state locking and concurrency control using Amazon DynamoDB, state inspection, and terraform import.
Building reusable, versioned infrastructure modules; managing multi-environment isolation (dev, staging, prod) via Terraform Workspaces and directory layouts; and dynamic blocks.
In this module, students master Centralized Monitoring: Amazon CloudWatch Metrics, Logs, Dashboards & Alarms through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Standard hypervisor metrics (EC2 CPU, Network, Disk), metric statistics (Average, Sum, p90, p99), custom application metrics via PutMetricData, and metric math expressions.
Log groups, log streams, CloudWatch Unified Agent installation for OS memory/disk metrics, metric filters generating alarms from regex patterns, and CloudWatch Logs Insights querying.
Static threshold alarms vs anomaly detection alarms, alarm states (OK, ALARM, INSUFFICIENT_DATA), composite alarms grouping multiple signals, and building real-time operational dashboards.
In this module, students master Governance, Auditing & Compliance: AWS CloudTrail API Logging through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Continuous recording of AWS management and data events, event history lookup, management events (IAM changes, EC2 launches) vs data events (S3 object access, Lambda invocations).
Creating organization-wide trails delivering to an encrypted centralized S3 bucket, log file integrity validation with SHA-256 hashing, and CloudWatch Logs stream integration.
Investigating unauthorized API calls, identifying root-cause actors (access key, IAM role, source IP), streaming events to CloudWatch for automated SNS alerting on critical security events.
In this module, students master Distributed Observability: OpenTelemetry, AWS X-Ray & Incident Triage through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
The three pillars of observability (metrics, logs, traces), trace IDs, spans, propagation headers (W3C Trace Context, X-Amzn-Trace-Id), and isolating microservice latency bottlenecks.
Instrumenting applications with AWS X-Ray SDK, X-Ray daemon running on EC2/ECS/EKS, generating interactive Service Maps, and filtering traces using filter expressions.
Vendor-neutral telemetry collection with OpenTelemetry Collector, routing traces and metrics to Amazon CloudWatch, X-Ray, and Prometheus; correlation IDs; and incident root-cause triage.
In this module, students master Version Control & Collaborative Git Workflows for Cloud Engineers through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Git object model (blobs, trees, commits, tags), staging area mechanics, branching pointers, stash, cherry-pick, merge vs rebase, and resolving merge conflicts.
Comparing GitFlow (feature, develop, release, hotfix) vs Trunk-Based Development with feature flags for high-frequency cloud deployments, pull requests, and peer reviews.
Protecting branches, requiring status checks and PR approvals, GPG commit signing, pre-commit hooks, and preventing credential leaks using git-secrets and Trufflehog.
In this module, students master Continuous Integration & Continuous Delivery (CI/CD) Principles & Pipelines through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Core tenets of continuous integration (automated unit/integration tests, linting, packaging), continuous delivery vs continuous deployment, artifact immutability, and rollback mechanics.
Rolling updates with capacity management, Blue/Green zero-downtime traffic switching via load balancers, Canary gradual percentage shifts, and automated health check rollbacks.
Embedding security into CI/CD: Static Application Security Testing (SAST), Software Bill of Materials (SBOM), dependency vulnerability scanning, and container CVE gates.
In this module, students master Native AWS DevOps Tooling: AWS CodeBuild, CodeDeploy & CodePipeline through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Managed serverless build environment, custom container build runtimes, buildspec.yml lifecycle phases (install, pre_build, build, post_build), artifacts, and cache management.
Deployment configurations (AllAtOnce, HalfAtATime, OneAtATime, Canary10Percent5Minutes), appspec.yml lifecycle hooks, in-place vs blue/green deployments, and rollback triggers.
Orchestrating source, build, test, manual approval gates, and deployment stages; integration with GitHub; pipeline triggers; and cross-account pipeline deployments.
In this module, students master Automated Cloud Deployments with GitHub Actions & AWS OpenID Connect (OIDC) through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Workflow syntax (.github/workflows/), GitHub-hosted vs self-hosted runners, job dependencies (needs), step execution, environment variables, and GitHub Secrets.
Eliminating hardcoded long-lived AWS IAM access keys: configuring AWS IAM OIDC Identity Provider for GitHub, assume-role trust policies with subject claims (sub: repo:org/repo:ref).
Building a complete production pipeline: checkout, lint, test, build Docker image, authenticate to ECR, push image, update ECS Task Definition / Helm chart, and deploy with automated rollback.
In this module, students master AWS Cloud Security Architecture & Enterprise Defense-in-Depth through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Customer responsibility (in the cloud - data, IAM, OS, network configuration) vs AWS responsibility (of the cloud - hardware, software, networking, facilities) across IaaS, PaaS, and serverless.
Multi-layered security boundaries: Edge protection (Route 53, CloudFront, Shield, WAF), Network perimeter (VPC, NACL, SG), Compute (hardened AMIs, patching), and Data (KMS, Macie).
Aligning architectures with CIS AWS Foundations Benchmark, SOC 2, ISO 27001, HIPAA, PCI-DSS, AWS Artifact audit reports, and security posture monitoring.
In this module, students master Cloud Security & Compliance Services: KMS, Secrets Manager, WAF, GuardDuty & Security Hub through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Customer Managed Keys (CMK) vs AWS Managed Keys, symmetric vs asymmetric keys, key policies, grants, envelope encryption (Data Keys), and automated annual key rotation.
Secrets Manager automated rotation with Lambda, Parameter Store (Standard vs Advanced parameters), and SSH-free secure terminal access via AWS Systems Manager Session Manager.
AWS WAF Web ACL rules (SQLi, XSS, rate limiting, IP reputation), AWS Shield Standard vs Advanced DDoS defense, GuardDuty intelligent threat detection, and Security Hub compliance posture.
In this module, students master Cryptography, Key Management & Zero-Trust Cloud Architecture through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Enforcing TLS 1.2+ for in-transit traffic, default encryption for S3, EBS, RDS, DynamoDB; client-side vs server-side encryption; and enforcing SSL/TLS via bucket policies (aws:SecureTransport).
Eliminating perimeter trust assumptions, continuous verification of identity and device health, micro-segmentation of workloads, and mutual TLS (mTLS) service-to-service communication.
Discovering personally identifiable information (PII) and sensitive financial data in S3 using Amazon Macie machine learning, generating findings, and automated remediation workflows.
In this module, students master High Availability Design Patterns, Multi-AZ Architectures & Distributed Systems through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Calculating system availability across serial vs parallel components, understanding downtime budgets (99.9% = 8.76 hrs/yr vs 99.999% = 5.26 mins/yr), and designing out single points of failure.
Decoupling compute from state, multi-AZ Auto Scaling across 3 availability zones, synchronous database replication, stateless web tiers, and session offloading to distributed caches.
Stateless microservices scaling, state externalization, distributed consensus principles, and navigating CAP theorem trade-offs (Consistency vs Availability vs Partition tolerance) on AWS.
In this module, students master Fault Tolerance, Failure Domains & Self-Healing Cloud Systems through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Defining failure boundaries (instance, rack, AZ, region), designing cell-based architectures to contain outages, partition isolation, and preventing cascading systemic failures.
Designing N+1 and 2N hardware redundancy, comparing Active-Active multi-AZ traffic distribution vs Active-Passive hot/warm standby failover topologies.
EC2 auto-recovery based on hardware CloudWatch alarms, ALB health check eviction, ASG instance replacement, and automated self-healing workflows via EventBridge and Lambda.
In this module, students master Resilience Engineering, Bulkheads, Circuit Breakers & Chaos Principles through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Preventing thread exhaustion: configuring aggressive client timeouts, retries with exponential backoff and randomized jitter to prevent thundering herd problems.
Circuit breaker state machine (Closed, Open, Half-Open) to fail fast on downstream service degradation, and bulkhead isolation partitioning thread pools and database connections.
Leveling traffic spikes with SQS queue-based load leveling, degrading non-critical features during peak load, and injecting deliberate failures with AWS Fault Injection Service (FIS).
In this module, students master Business Continuity & Disaster Recovery (RPO, RTO, Pilot Light & Multi-Region DR) through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Recovery Point Objective (RPO - acceptable data loss window) and Recovery Time Objective (RTO - acceptable downtime window), business impact analysis, and DR tier selection.
Detailed comparative analysis: 1. Backup & Restore (hours RPO/RTO), 2. Pilot Light (minimal core running), 3. Warm Standby (scaled-down duplicate), 4. Multi-Region Active-Active (sub-second RPO/RTO).
S3 Cross-Region Replication (CRR), Aurora Global Database replication, RDS cross-region read replicas, Route 53 DNS failover routing policies, and running regular disaster recovery game days.
In this module, students master AWS Economics, Pricing Models, Savings Plans & Spot Strategies through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Unpacking AWS pricing models, identifying hidden cost drivers: inter-AZ data transfer fees, internet data egress, NAT Gateway hourly and data processing charges, and public IPv4 fees.
Compute Savings Plans vs EC2 Instance Savings Plans, 1-year vs 3-year commitments, All Upfront vs Partial Upfront vs No Upfront payment options, and RI marketplace liquidity.
Spot pricing mechanics, Spot Advisor interruption frequency, configuring Auto Scaling Spot Fleets with capacity-optimized allocation strategies, and handling rebalance recommendations.
In this module, students master Cloud FinOps, Resource Right-Sizing & AWS Cost Optimization through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
The FinOps lifecycle (Inform, Optimize, Operate), mandatory cost allocation tagging strategies, consolidated billing in AWS Organizations, and department chargebacks.
Forecasting spend with AWS Cost Explorer, setting proactive threshold alerts in AWS Budgets (actual and forecasted spend), and detecting sudden bill shocks with AWS Cost Anomaly Detection.
Right-sizing over-provisioned EC2/RDS instances using AWS Compute Optimizer recommendations, eliminating unattached EBS volumes/snapshots, and tuning S3 lifecycle transition rules.
In this module, students master AWS Well-Architected Framework: The 6 Pillars of Excellence through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Operational Excellence (infrastructure as code, small reversible changes, preparing for failures) and Security (identity foundations, traceability, protecting data at rest/transit, incident response).
Reliability (recovering automatically from failure, testing recovery procedures, horizontal scaling) and Performance Efficiency (democratizing advanced technologies, serverless, selecting optimal resources).
Cost Optimization (measuring efficiency, paying for consumption, expenditure analysis) and Sustainability (understanding environmental impact, maximizing utilization, adopting efficient hardware).
In this module, students master Cloud Architecture Patterns: 3-Tier, Microservices, Event-Driven & Multi-Account through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Presentation tier (CloudFront, S3, ALB), Application tier (EC2 Auto Scaling in private subnets), and Database tier (Multi-AZ RDS in isolated subnets) with end-to-end security.
Decomposed domain-driven microservices, asynchronous pub/sub messaging, choreography vs orchestration with AWS Step Functions, and API Gateway fronting Lambda and DynamoDB.
Multi-account separation (core security, log archive, shared services, dev, staging, prod), AWS Control Tower landing zones, Direct Connect hybrid connectivity, and AWS Outposts.
In this module, students master Enterprise Cloud Governance, AWS Organizations & Control Tower Landing Zones through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Automated Landing Zone setup, Account Factory for provisioning compliant new accounts, baseline VPCs, and centralized identity federation with AWS IAM Identity Center (Single Sign-On).
Writing preventive SCP guardrails (disabling non-allowed regions, enforcing encryption, preventing deletion of CloudTrail logs, restricting root user usage), and tag enforcement policies.
Continuously auditing AWS resource configurations, managed vs custom AWS Config rules, evaluating compliance status against benchmarks, and automated remediation via SSM documents.
In this module, students master Cloud System Design Fundamentals: Scalability, Availability & CAP Theorem through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Clarifying functional vs non-functional requirements, estimating Daily Active Users (DAU), read/write ratios, queries per second (QPS), bandwidth, and multi-year storage capacity requirements.
Horizontal vs vertical scaling, identifying system bottlenecks, Amdahl's law, latency percentiles (p50, p99, p99.9), network throughput constraints, and caching hierarchies.
Strong consistency vs eventual consistency, ACID vs BASE transactions, CAP theorem trade-offs in distributed cloud databases, PACELC theorem, and distributed leader election.
In this module, students master Distributed System Components: Load Balancers, Caches, Queues & Global CDNs through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
CloudFront distribution architecture, Edge Locations, Origin Access Control (OAC), origin failover, caching policies, CloudFront Functions vs Lambda@Edge for edge logic.
Redis caching layers, cache eviction algorithms (LRU, LFU), consistent hashing, horizontal database sharding, partition keys, and read/write connection splitters.
Decoupling ingest from processing using message queues (SQS, Kafka), worker pooling, backpressure handling, dead-letter redrive, and idempotency in distributed workers.
In this module, students master High-Level (HLD) & Low-Level (LLD) Cloud Architecture Design & Blueprints through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Drafting comprehensive HLD documents: system overview, architectural topology diagrams, service boundaries, technology rationale, security model, and failover workflows.
Drafting low-level specifications: API endpoint contracts (OpenAPI/Swagger), database schemas (ER diagrams, DynamoDB single-table design), class/component interfaces, and network port matrices.
Presenting and defending cloud architectures to engineering leadership: articulating trade-offs (cost vs latency vs availability), risk registers, and migration roadmaps.
In this module, students master AWS Certified Solutions Architect – Associate (SAA-C03) Exam Mastery & Strategy through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Comprehensive review of the 4 exam domains: Design Secure Architectures (30%), Design Resilient Architectures (26%), Design High-Performing Architectures (24%), Design Cost-Optimized Architectures (20%).
Dissecting tricky scenario questions: identifying key constraints ('most cost-effective', 'least operational overhead', 'lowest latency', 'highest availability'), and ruling out distractors.
Simulating actual 130-minute 65-question proctored exam conditions, in-depth question-by-question review, score gap analysis, and final revision cheat-sheets.
In this module, students master Enterprise Cloud Troubleshooting, Incident Workflows & Production Support through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Diagnosing high CPU utilization, memory leaks triggering OOM-killer, disk space exhaustion on root volume, recovering corrupted fstab files, and SSH connectivity triage.
Debugging network connectivity issues: isolating Security Group vs NACL blocks, asymmetric routing, NAT Gateway connection exhaustion, Route 53 DNS propagation delays, and ALB 502/504 errors.
Diagnosing RDS max connections exceeded, CPU spikes from missing database indexes, read replica replication lag, storage auto-scaling limits, and Aurora failover analysis.
The enterprise incident workflow: automated alert triage, establishing incident bridges, root-cause isolation, emergency mitigation, service recovery, and writing blameless postmortems.
In this module, students master Cloud Automation with Linux Bash Scripting & Systems Tooling through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Shebang, variable scoping, command substitution, exit codes, if/else conditionals, loops (for, while), functions, and command-line arguments ($1, $2, $@).
Writing robust production shell scripts: trap signals (ERR, EXIT), defensive flags (set -euo pipefail), validating dependencies, input sanitization, and structured logging.
Automating Linux administrative tasks: log parsing with awk/sed, disk space monitors with email alerting, automated tar backups to S3 via AWS CLI, and user onboarding automation.
In this module, students master Cloud Automation with Python, Boto3 SDK & Infrastructure Scripting through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Python fundamentals: lists, dictionaries, string formatting, file I/O, error handling with try/except, parsing JSON payloads, and making REST API calls with requests.
Boto3 architecture: low-level Clients vs high-level Resources, authentication via IAM instance profiles/credentials, handling paginated API responses (Paginators), and Collections.
Building real-world operational scripts: automated EC2 instance stopping/starting schedules, auditing unattached EBS volumes, purging old S3 versions, and automated security reporting.
In this module, students master AWS Cloud Migration Framework (6R Model) & Enterprise Modernization through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Cloud readiness assessment, total cost of ownership (TCO) analysis, application dependency mapping with AWS Application Discovery Service, and migration wave planning.
Detailed evaluation of the 6R framework: Rehost (lift-and-shift via AWS Application Migration Service), Replatform (lift, tinker & shift), Repurchase (drop-and-shop SaaS), Refactor (re-architect), Retire, and Retain.
Modernization roadmaps: decomposing monolithic applications into containerized microservices, migrating self-hosted databases to Amazon Aurora/RDS, and adopting serverless event architectures.
In this module, students master Solutions Architect Real-World Architecture Exercises (12 Industry Scenarios) through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Hands-on architectural designs: 1. High-traffic global e-commerce with flash sale spikes, 2. Global video streaming CDN with DRM, 3. High-concurrency job portal with resume indexing and search.
Compliant cloud architectures: 4. Core banking system with multi-region zero-RPO failover, 5. HIPAA-compliant healthcare data platform, 6. PCI-DSS Level 1 compliant payment processing gateway.
Complex distributed architectures: 7. Airline reservation engine with distributed locking, 8. Global IoT telemetry ingestion with Kinesis/MSK, 9. Multi-tenant B2B SaaS platform with tenant data isolation.
In this module, students master Cloud Engineering Coding & Automation (75+ Hands-on Problems) through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Automated log parsing, detecting brute-force IP attacks from auth logs, identifying top memory/CPU consumers, auditing file permissions, and directory tree deduplication.
Scripted multi-VPC provisioning, automated AMI backup rotations, finding public S3 buckets, snapshot cleanup scripts, and IAM key expiration scanners.
Serverless automated tagging enforcers, real-time Slack alerting for AWS Health events, dynamic Route 53 failover automation, and automated multi-account cost audit reports.
In this module, students master AWS Cloud Solutions Architect & DevOps Technical Interview Preparation through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Comprehensive interview defense: EC2 vs Fargate vs Lambda trade-offs, RDS vs DynamoDB data modeling, SQS vs SNS vs EventBridge, and ALB vs NLB routing decisions.
Solving live scenario questions: 'How do you design a system to survive an AWS region outage?', 'How do you connect private on-premises subnets to AWS with zero public exposure?', and 'How do you cut AWS cloud bills by 40%?'
Simulated whiteboard interviews: sketching architecture diagrams, explaining trade-offs, addressing capacity estimations, and demonstrating deep knowledge of AWS failure modes.
In this module, students master MockAttempt Placement Preparation, Resume Engineering & Technical Mock Interviews through hands-on cloud labs, architecture diagrams, and real-world configuration exercises.
Engineering an ATS-proof resume highlighting production AWS architecture, Terraform IaC repos, Docker/Kubernetes deployments, cost optimizations, and verifiable metrics.
Showcasing production architecture diagrams on GitHub, publishing technical blog teardowns, LinkedIn recruiter visibility, and networking strategies for cloud engineering roles.
Comprehensive multi-round mock interviews (Linux, Networking, AWS Architecture, Terraform, Live Whiteboarding, HR), IRT benchmark assessments, and 100% Placement Drives.
Portfolio Capstone & Production Projects (13 Projects)
Build and defend production repositories featuring clean architecture, CI/CD, and benchmark testing.
Linux Server Administration & Hardened Cloud Infrastructure Lab
Deploy, harden, and administer an enterprise-grade Linux server on AWS. Configure SSH key authentication, non-root users, systemd services, automated cron jobs, LVM storage, firewalls with UFW/iptables, and system monitoring.
Multi-Account IAM Security Architecture & Least-Privilege Governance Lab
Design and implement a secure multi-account IAM access architecture across Development, Staging, and Production environments with AWS Organizations, SCPs, cross-account AssumeRole delegation, and enforced MFA.
Production 3-Tier High-Availability AWS Network & VPC Peering Infrastructure
Design and provision a highly available, multi-AZ custom Amazon VPC with isolated public, private application, and private database subnets, dual NAT Gateways, Gateway VPC Endpoints, and secure inter-VPC peering.
Highly Available Auto-Scaling Web Application with ALB, Route 53 & RDS Multi-AZ
Architect and deploy a fault-tolerant, auto-scaling web application across multiple AZs utilizing Route 53 DNS, an Application Load Balancer with SSL/TLS termination, EC2 Auto Scaling Groups, and an Amazon RDS PostgreSQL Multi-AZ database.
Secure Enterprise Cloud Storage & Document Distribution System
Build an enterprise document management and storage platform leveraging Amazon S3, KMS customer-managed encryption, automated lifecycle policies to Glacier, presigned URLs for secure temporary downloads, and Amazon EFS shared storage.
Resilient E-Commerce Database Architecture (Aurora Multi-Master, DynamoDB & ElastiCache)
Construct a polyglot persistence database tier for an e-commerce platform combining Amazon Aurora PostgreSQL with auto-scaling read replicas, Amazon DynamoDB for cart and session management, and Amazon ElastiCache for Redis caching.
Serverless Event-Driven Order Processing & Notification System
Build a serverless asynchronous order processing architecture using Amazon API Gateway, AWS Lambda, Amazon SQS FIFO queues, Amazon SNS for customer notifications, Amazon EventBridge, and DynamoDB.
Production Microservices & Container Platform on Amazon ECS & Amazon EKS
Containerize a multi-tier microservices application, store optimized container images in Amazon ECR with vulnerability scanning, and deploy dual production orchestrations across Amazon ECS (AWS Fargate) and managed Amazon EKS (Kubernetes).
Complete AWS Infrastructure as Code with Terraform & GitHub Actions CI/CD
Codify an entire enterprise AWS cloud footprint using modular HashiCorp Terraform with S3 remote state and DynamoDB state locking. Implement automated linting, security scanning (tfsec), plan preview, and zero-downtime deployment pipelines in GitHub Actions.
Centralized CloudWatch Observability, Distributed Tracing & Automated Incident Remediation
Deploy enterprise-wide observability across compute, network, and database layers using Amazon CloudWatch agent, Logs Insights, composite alarms, AWS X-Ray distributed tracing, and automated EventBridge self-healing remediation.
Enterprise Security Hardening with AWS KMS, WAF, GuardDuty & Security Hub Audit
Implement enterprise-wide defense-in-depth security: AWS WAF rate-limiting and OWASP Top 10 protection on ALBs, KMS envelope encryption, AWS Secrets Manager rotation, continuous threat detection with Amazon GuardDuty, and compliance auditing with AWS Security Hub.
Multi-Region Active-Passive Disaster Recovery Architecture
Architect and validate a warm standby multi-region disaster recovery solution for a business-critical financial platform with strict RPO < 1 minute and RTO < 5 minutes using Route 53 health-check failover, S3 Cross-Region Replication, and Aurora Global Database.
Enterprise Multi-Tier Cloud Platform Capstone
Design, codify in Terraform, deploy, and defend an end-to-end enterprise cloud platform: Route 53 latency routing, CloudFront CDN, AWS WAF, multi-AZ VPC, containerized microservices on Amazon EKS, Aurora Global Database, ElastiCache Redis, SQS/SNS event streaming, centralized CloudWatch observability, CI/CD with GitHub Actions, and FinOps cost optimization audit.
Progressive Certification Ladder (5 Verified Levels)
Candidates earn industry shareable digital credentials as they clear milestone coding rounds and architecture reviews.
Certified AWS Cloud Practitioner & Linux Operations Specialist
CAP-LOSCertified AWS Networking & Security Infrastructure Associate
CAN-SIACertified AWS Serverless & Cloud Database Specialist
CAS-CDSCertified AWS DevOps & Terraform Infrastructure Engineer
CAD-TIECertified Enterprise AWS Solutions Architect & Platform Engineer
CEA-SPE🎯 Target Audience & Career Persona
Aspiring AWS Cloud Engineers, Cloud Solutions Architects, Cloud Infrastructure Engineers, DevOps Engineers, Site Reliability Engineers, Systems Administrators, and Software Engineers seeking enterprise cloud architecture mastery.
📋 Academic & Technical Prerequisites
No prior AWS cloud experience required. Basic computer literacy and fundamental logic are recommended. Linux and networking fundamentals are taught from ground zero as part of Stage 1-3.
Frequently Asked Questions & Placement Refund Policy
Everything you need to know about the 6-Month 100% Fees Refund Policy, curriculum structure, and placement drives.
How does the 100% Fees Refund Policy* work if I am not placed within 6 Months? ↓
Every enrolled candidate is covered by our legally backed 100% Fees Refund Guarantee*. To qualify for refund claims if not placed in an IT role within 6 Months post-completion, students must complete the training and satisfy our rigorous mastery benchmarks:
- Daily Topic Mastery (>98%): Complete daily topic mock tests scoring greater than 98% (with 100+ mock tests available per topic).
- Daily AI Topic Interview (>98%): Clear topic-wise AI interviews scoring greater than 98% evaluating conceptual depth, logical problem-solving, and articulation.
- Final Exit Evaluation (≥95%): Score at least 95% on the Grand Mock Test and comprehensive Final AI Technical Interview.
- Multiple Retake Opportunities: Students are provided multiple re-test opportunities so the objective is true concept mastery, not high-stress one-shot testing.
If these academic benchmarks are met and you do not secure a verified IT placement within 6 Months after graduation, MockAttempt refunds 100% of your paid course tuition fees directly to your bank account with zero deductions.* Read our full refund policy terms here.
What companies recruit from this MockAttempt career track? ↓
Our candidates are actively hired by 150+ tier-1 IT consulting enterprises, Fortune 500 GCCs (Global Capability Centers), and high-growth technology product firms across India and overseas. We coordinate exclusive placement drives, resume shortlisting, and direct interview scheduling.
How does the MockAttempt AI Teleprompter and AI Mock Interview feature work? ↓
Students receive complimentary unlimited access to the MockAttempt AI Virtual Interview platform. You can practice real-time technical voice interviews, receive instant Big-O complexity feedback, and utilize our Windows desktop stealth teleprompter HUD to polish your problem-solving speech and live coding articulation before company interviews.
Can I learn this program if I am a non-CS student or complete beginner? ↓
Yes. Module 0 and Phase 1 start directly from fundamental computer concepts, operating systems, and basic programming logic. Our dedicated discord teaching assistants and weekly live doubt-clearing sessions ensure every candidate masters every concept thoroughly.
Backed by our 100% money-back guarantee: if not placed within 6 months post-training, your complete tuition is refunded.
Enroll with 6-Month Placement Assurance
Speak with a technical advisor and receive your complete syllabus roadmap and legal guarantee agreement.
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