AWS Solutions Architect Mastery Course

1.1 Core Concepts:

• Overview of Cloud Computing Models (Public, Private, Hybrid)
• AWS Global Infrastructure: Regions, Availability Zones, and Edge Locations
• Cloud Benefits: Scalability, High Availability, and Cost Efficiency

1.2 Introduction to AWS:

• Setting Up AWS Accounts and Billing Alerts
• Understanding AWS Free Tier Limitations and Usage

1.3 Core AWS Services Overview

• Compute: EC2, Lambda
• Storage: S3, EBS, EFS
• Databases: RDS, DynamoDB

1.4 Hands-On

• Deploy and Configure an EC2 Instance with Security Groups
• Create and Configure an S3 Bucket with Versioning and Lifecycle Rules

2.1 Deep Dive into EC2:

• Instance Types: General Purpose, Compute Optimized, Memory Optimized
• Configuring Key Pairs, Elastic IPs, and AMIs
• Understanding Instance Metadata and Role Assignment for EC2

2.2 Scaling and Availability:

• Auto Scaling Groups: Launch Templates, Target Tracking Policies
• Load Balancers: ALB, NLB, and CLB Use Cases
• Placement Groups: Cluster, Spread, and Partition Strategies

2.3 Hands-On:

• Build a High-Availability Architecture Using Auto Scaling and ALB
• Perform Load Testing to Optimize Auto Scaling Policies

3.1 Networking Basics:

• VPC: Subnets, Route Tables, Internet Gateways, NAT Gateways
• Configuring Security Groups vs Network ACLs

3.2 Advanced Networking:

• VPC Peering, Transit Gateway, and Direct Connect
• Using PrivateLink for Secure Service Integration

3.3 Security Best Practices:

• Data Encryption at Rest and In Transit with KMS and CloudHSM
• Monitoring with AWS Config and CloudTrail

3.4 Hands-On:

• Design and Implement a Multi-VPC Architecture
• Set Up a Secure VPN Connection for a Hybrid Cloud Environment

4.1 Relational Databases:

• Amazon RDS: Automated Backups, Multi-AZ Deployments, Read Replicas
• Aurora for High Performance and Scalability

4.2 NoSQL Databases:

• DynamoDB: Indexing, Partitioning, Global Tables
• DynamoDB Accelerator (DAX) for High-Performance Use Cases

4.3 Storage Solutions

• S3: Storage Classes, Lifecycle Management, Cross-Region Replication
• EBS vs EFS: Performance Tuning and Use Cases

4.4 Hands-On:

• Configure an RDS Multi-AZ Database with Backup Policies
• Build a NoSQL Table for Real-Time Analytics

5.1 AWS Lambda:

• Deployment, Event Sources, Monitoring
• Advanced Features: Concurrency, Provisioned Concurrency, and DLQs

5.2 Orchestration and Workflows:

• Event-Driven Architectures with SNS, SQS, and EventBridge
• Using Step Functions for Complex Workflow Automation

5.3 Hands-On:

• Build a Serverless REST API with API Gateway and Lambda
• Create an Event-Driven Data Processing Pipeline Using Lambda and S3

6.1 Container Basics with Docker:

• Building, Running, and Managing Docker Containers
• Creating and Optimizing Docker Images for Applications

6.2 Kubernetes Fundamentals:

• Amazon EKS: Setting Up Clusters and Deploying Applications
• Kubernetes Resources: Pods, Deployments, Services, and Ingress
• Scaling and Auto-Healing in Kubernetes

6.3 Hands-On:

• Deploy a Dockerized Application to EKS
• Configure Kubernetes Ingress for Load Balancing and Secure Access/li>

7.1 Cost Management:

• Right-Sizing Resources and Leveraging Reserved Instances
• Optimizing S3 Storage with Lifecycle Rules
• Using Trusted Advisor for Cost and Performance Recommendations

7.2 Business Alignment:

• ROI Analysis and Total Cost of Ownership (TCO)
• Presenting Cost-Effective Cloud Strategies to Stakeholderss

7.3 Hands-On:

• Conduct a Cost Optimization Review for a Simulated AWS Account
• Prepare and Present a Business Case for Cloud Migration Savings

8.1 AI Services:

• Rekognition: Image and Video Analysis
• Comprehend: Sentiment Analysis and NLP
• Lex: Building Conversational Interfaces

8.2 Machine Learning with SageMaker:

• Building, Training, and Deploying ML Models
• Integrating Real-Time Predictions Using SageMaker Endpoints

8.3 Hands-On:

• Build an AI-Powered Chatbot with Lex and Lambda
• Develop a Sentiment Analysis Application Using Comprehend

9.1 Migration Fundamentals:

• AWS Migration Strategies: The 6 R’s (Rehost, Replatform, Refactor, etc.)
• AWS Migration Hub for Centralized Migration Management

9.2 Migration Tools:

• Database Migration Service (DMS): Planning and Execution
• Server Migration Service (SMS): Automating Server Migration to AWS

9.3 Hands-On Projects:

• Migrate a Multi-Tier Web Application from On-Premises to AWS
• Validate and Optimize Migration Results for Performance and Cost

This module immerses participants in hands-on, practical projects that simulate real-world challenges faced by AWS Solution Architects. By the end of this module, participants will have completed multiple end-to-end projects, preparing them for enterprise-grade AWS roles.

10.1 Project 1: E-Commerce Platform Architecture

• Objective: Design a scalable, secure, and highly available architecture for an e-commerce platform.

Key AWS Services:

• EC2 with Auto Scaling for web and application tiers.
• Elastic Load Balancer (ALB) for traffic distribution.
• RDS (Multi-AZ) for the transactional database.
• S3 and CloudFront for static content storage and delivery.

Key Deliverables:

• Architecture diagram with detailed service configurations.
• Cost optimization plan for resource usage.

10.2 Project 2: Serverless Data Processing Pipeline

Objective: Build a real-time data processing pipeline for analytics or IoT use cases

Key AWS Services:

• Kinesis Data Streams for data ingestion.
• AWS Lambda for real-time data transformation.
• S3 and DynamoDB for storage.
• Amazon QuickSight for data visualization.

Key Deliverables:

• End-to-end functional pipeline with monitored data flow.
• Dashboards showcasing processed data insights.

10.3 Project 3: Multi-Region Disaster Recovery

Objective: Architect a multi-region disaster recovery (DR) setup for critical enterprise workloads.

Key AWS Services:

• Route 53 for DNS failover.
• S3 with Cross-Region Replication for data durability.
• RDS with read replicas in a secondary region.
• CloudFormation for automated DR configuration deployment.

Key Deliverables:

• Fully functional DR strategy and setup.
• Test reports documenting failover scenarios.

10.4 Project 4: Cloud Migration of a Monolithic Application

Objective: Migrate a monolithic application from an on-premises data center to AWS.

Key AWS Services:

• AWS Migration Hub for tracking progress.
• DMS for database migration.
• AWS SMS for server migration.
• EC2, RDS, and S3 for application deployment.

Key Deliverables:

• Migration plan, architecture diagrams, and timeline.
• Post-migration testing and optimization reports.

Project 5: Cost Optimization Challenge

Objective: Analyze and optimize the AWS cost structure of a simulated enterprise workload.

Key AWS Services:

• Trusted Advisor for cost and performance recommendations.
• AWS Cost Explorer for detailed cost analysis.

Savings Plans and Reserved Instances for cost reduction.

Key Deliverables:

• Cost optimization report with actionable recommendations.
• Presentation on cost savings for stakeholders.

11.1 Understanding the Interview Process:

• Common Stages: Screening, Technical Interview, Behavioral Interview, Bar-Raiser
• Expectations for AWS Solution Architect Roles at Top Companies
• Key Skills Evaluated: Technical Expertise, Problem-Solving, and Communication

11.2 Technical Interview Preparation

a. Scenario-Based Problem Solving:

• Designing High-Availability Architectures
• Architecting Cost-Optimized and Scalable Solutions
• oTroubleshooting Multi-Tier Architectures

b. Core AWS Services Deep-Dive:

• Networking (VPC, Load Balancers, Transit Gateway)
• Compute (EC2, Auto Scaling, Lambda)
• Storage (S3, EBS, EFS) and Databases (RDS, DynamoDB)

c. Hands-On Practice:

• Real-Time Architecture Whiteboarding (Lucidchart/Miro)
• Troubleshooting Common AWS Deployment Issues

11.3 Behavioral Interview Preparation

a. Amazon Leadership Principles:

• Customer Obsession, Ownership, Deliver Results, and more

b. STAR Method:

• Structuring Responses with Situation, Task, Action, Result

c. Common Behavioral Questions:

• Tell me about a time you handled an unexpected challenge.
• Describe how you proposed a cost-saving solution.

11.4 Mock Interviews

a. Technical Mock Interviews:

• Simulated Problem-Solving for Real-World AWS Use Cases
• Feedback on Accuracy, Creativity, and Communication

b. Behavioral Mock Interviews:

• Scenarios Tailored to Leadership Principles
• Peer and Mentor Feedback for Improvement

11.5 Post-Interview Strategy

• Writing Impactful Follow-Up Emails
• Best Practices for Negotiating Offers and Defining Role Expectations

12.1 Understanding the C-Suite Perspective

• Business-First Approach: Connecting Technical Solutions to Strategic Goals
• Focusing on Metrics that Matter: ROI, TCO, and Cost Savings
• Building Trust with Executives Through Data-Driven Insights

12.2 Crafting Executive-Level Presentations:

a. Structuring Presentations:

• Problem Definition, Proposed Solution, Business Benefits

b. Visual Storytelling:

• Using Graphs, Diagrams, and Real-Time Metrics to Build Confidences

c. Simplifying Complexity

• Breaking Down Technical Concepts for Non-Technical Stakeholderss

12.3 Delivering Impactful Presentations:

a. Persuasive Communication:

• Storytelling Techniques to Highlight Business Value

b. Handling Questions and Objections Confidently:

• Techniques to Respond to Stakeholder Concerns

c. Time Management for High-Stakes Presentations