Erdi Aslan
About Me
I am a Electrical and Electronics Engineer with a growing focus on AWS cloud technologies and DevOps fundamentals. I have hands-on experience with AWS services through internships and personal projects, where I worked on containerized applications, serverless workflows, and basic CI/CD pipelines. I am currently preparing for the AWS Solutions Architect β Associate certification and actively improving my skills in cloud infrastructure, automation, and reliability. I am eager to learn, open to feedback, and motivated to start my career as a Junior Cloud Engineer where I can grow by working closely with experienced teams.
Skills
βοΈ Cloud Technologies
π§ DevOps & Tools
Work Experience
Cloud Engineer Intern
- Deployed containerized backend services on AWS Fargate with ALB routing, IAM, and ECR, enabling scalable production-ready workloads.
- Built a serverless automation pipeline using Lambda, API Gateway, S3, and Aurora to process data and trigger AI-powered tasks.
- Developed Python automation scripts to streamline internal workflows and reduce manual operational steps.
- Implemented CI/CD pipelines using GitHub Actions and Docker, automating build and deployment stages.
Projects
Fargate PoC
This PoC shows how a Node.js application is deployed on AWS ECS Fargate without managing servers. User traffic is secured and distributed via AWS managed services, the application runs in private subnets, connects to a managed database, and is deployed automatically through CI/CD.
- Amazon CloudFront β CDN, SSL, caching
- AWS WAF β Web application security
- Application Load Balancer (ALB) β Traffic routing
- Amazon VPC β Public & private subnet isolation
- Amazon ECS (Fargate) β Serverless container runtime
- Amazon ECR β Docker image registry
- Amazon RDS (MySQL) β Managed relational database
- NAT Gateway β Controlled outbound internet access
- VPC Endpoints (ECR / S3) β Private AWS service access
- Amazon CloudWatch β Logs, metrics, alarms
- Amazon SNS β Alert notifications
AI Avatar β AI-Driven Video Automation
This project is a serverless AI video generation pipeline. It is triggered by EventBridge (scheduled) or API Gateway (on-demand) and runs on AWS Lambda. Lambda generates personalized text with OpenAI, converts it to MP3, stores it in S3, and sends it to Heygen to create an avatar video. The video is watermarked using ffmpeg, saved to S3, and a webhook notifies the Imona platform when the video is ready.
- EventBridge
- API Gateway
- AWS Lambda
- OpenAI API
- Amazon S3
- Heygen API
- Webhook (Imona Platform)
Education
Bachelor's Degree in Electrical and Electronics Engineering
Certifications
AWS Certified Cloud Practitioner
β View Credential
AWS Certified Solutions Architect β Associate
Currently Preparing