Worklog
This page documents the entire Worklog carried out throughout the First Cloud Journey (FCJ) internship program at AWS. This document details the process of learning, implementing the Bandup IELTS project, troubleshooting system errors, and participating in specialized events over 12 weeks (approximately 3 months).
During these 12 weeks, I transitioned from familiarizing myself with core Cloud concepts to building and optimizing a complete AI-powered Serverless application on AWS, completing 50+ AWS Skill Builder courses along the way.
Summary of Work by Week:
| Week | Focus Area |
|---|
| Week 1 | Completed mid-term exam, began implementing foundational CRUD functionalities, researched serverless architecture (Lambda, API Gateway, DynamoDB), and set up development environment. |
| Week 2 | Resolved AWS account issues, configured Hybrid DNS with Route 53 Resolver and VPC Peering, learned CloudFormation and Cloud9 for IaC development. |
| Week 3 | Finalized AI-powered Lambda functions, integrated Gemini API for IELTS evaluation, completed RAG pipeline for flashcard generation, and attended the final AWS Cloud Mastery Series. |
| Week 4 | Familiarization with FCJ, AWS account creation, basic Cloud concepts, and foundational network setup (VPC, Subnets, Internet Gateway). |
| Week 5 | Transitioned to AWS SAM, refactored CRUD functionalities, integrated Docker for build environment, and successfully deployed project to AWS overcoming local debugging challenges. |
| Week 6 | Mastered AWS Transit Gateway for centralized network management, deep dive into EC2 Auto Scaling, Lightsail, and Migration services (DMS, VM Import/Export). |
| Week 7 | Comprehensive review and knowledge consolidation of core AWS services (Compute, Storage, Networking, Database, Security) in preparation for the mid-term exam. |
| Week 8 | Mastered AWS Storage services (S3, Glacier, Storage Gateway), enhanced Python skills, finalized project architecture, and attended DevSecOps & Amazon Q Developer Webinar. |
| Week 9 | Mastered Amazon EC2 and VPC fundamentals, completed AWS Skill Builder courses on IAM, Budgets, EC2, and attended Cloud Day event for AI/Data insights. |
| Week 10 | Debugged CORS and template validation errors, integrated Frontend/Backend, completed Read/Delete functions, resolved Cognito authentication issues, and attended AWS Cloud Mastery Series #1. |
| Week 11 | Analyzed and optimized AWS costs, designed Serverless infrastructure architecture, learned RDS, DynamoDB, ElastiCache, and set up AWS Toolkit for VS Code. |
| Week 12 | Implemented Multi-Stack architecture for optimization, fixed the persistent CORS error, and began integrating AI Services (Lambda, Bedrock). |
AWS Skill Builder Learning Path (Weeks 2-5)
| Category | Courses Completed |
|---|
| Networking | VPC, Route 53, VPC Peering, Transit Gateway, Networking Workshop |
| Compute | EC2, EC2 Auto Scaling, Lightsail, Lightsail Containers |
| Security | IAM, IAM Roles for EC2 |
| Database | RDS, DynamoDB, ElastiCache |
| Migration | VM Import/Export, DMS, SCT, Elastic Disaster Recovery |
| DevOps | CloudFormation, Cloud9, AWS CLI, AWS Toolkit for VS Code |
| Cost Management | AWS Budgets, Cost Explorer, Service Quotas, Right-Sizing |
| Architecture | Building Highly Available Web Applications |
AWS Skill Builder Learning Path (Weeks 6-10)
| Category | Courses Completed |
|---|
| Storage | Static Website Hosting with S3, AWS Backup, CloudFront |
| Reliability | Data Protection with AWS Backup |
| Development | AWS Toolkit for VS Code, Serverless patterns |
Learning Progression
Weeks 1-5: Foundation & Exploration
- Core AWS services (EC2, S3, VPC, IAM)
- Networking fundamentals (VPC, Route 53, Transit Gateway)
- Cost optimization and architecture design
- Infrastructure as Code (CloudFormation, Cloud9)
Weeks 6-7: Consolidation & Assessment
- Storage services mastery (S3, Glacier, Storage Gateway)
- Disaster recovery and backup strategies
- Comprehensive exam preparation
- Mid-term exam completion
Weeks 8-10: Implementation & Deployment
- Serverless architecture implementation (Lambda, API Gateway, DynamoDB)
- AWS SAM framework adoption
- Docker integration for consistent builds
- Frontend-Backend integration
- Production deployment and debugging
Weeks 11-12: Advanced Features & AI Integration
- Multi-stack architecture optimization
- AI services integration (Bedrock, Gemini API)
- RAG pipeline implementation
- Final project completion