(March 2025 - Present)
Web Instructor
Programming Hero
ABOUT ME
Who I am?
Hi, I’m Bayajid Alam Joyel, a full-stack developer and cloud enthusiast with hands-on experience in Next.js, React, Node.js, NestJS, Express, PostgreSQL, MongoDB, and Redis. I’ve built scalable, cloud-native applications like VisionSync, an AWS video streaming system. I’m passionate about system design, performance optimization, and DevOps automation, and I enjoy solving complex problems while staying up-to-date with emerging technologies. I’m looking for opportunities that leverage my expertise in full-stack development, distributed systems, and cloud-driven solutions.
Experiences
(December 2023 - January 2025)
Full Stack Developer
Pii Marketer
August 2024 - Present
Backend Co-Lead(Volunteer)
Uddhar
Skills
Language
C
C++
TypeScript
Cloud, DevOps & Testing
AWS
Docker
Kubernetes
Nginx
CI/CD
Pulumi
Ansible
Prometheus
Grafana
Backend Techs
Node JS
Express JS
GraphQL
RabbitMQ
Database And ORM
MongoDB
PostgreSQL
Redis
Mongoose
Prisma
Frontend Techs
React
Next JS
Redux
Tailwind
ShadcnUI
Ant Design
Firebase
Others
Git
Figma
VS CODE
Postman
Linux
PROJECTS
VisionSync - Video Streaming Platform
constproject={name:'VisionSync - Video Streaming Platform',tools: ['React', 'TypeScript', 'Tailwind CSS', 'shadcn/ui', 'Node.js', 'Express', 'MongoDB', 'Socket.IO', 'AWS S3', 'AWS ECS', 'AWS Lambda', 'AWS SQS', 'CloudFront', 'Redis', 'FFmpeg', 'Pulumi],myRole:Full Stack Developer,Description: I built a scalable video streaming platform with real-time processing updates. Users upload videos via pre-signed URLs directly to S3, triggering automated ECS containers that compress videos, convert to multiple resolutions (1080p, 720p, 480p), split into 10-second chunks, and generate MPEG-DASH manifests. The platform delivers content through CloudFront CDN with signed URLs for security. Real-time upload and processing status updates are handled via Socket.IO with Redis as the backplane. The entire infrastructure is provisioned with Pulumi on AWS, achieving 48% cost reduction through optimizations like S3 Intelligent Tiering, lifecycle policies, and Spot instances for ECS tasks.,};SimplyDone To-Do Application
constproject={name:'SimplyDone To-Do Application',tools: ['React.js', 'Tailwind CSS', 'Shadcn UI', 'Firebase', 'Node.js', 'Express', 'TypeScript', 'Docker', 'Docker Hub', 'AWS EC2', 'AWS ALB', 'AWS Auto Scaling', 'AWS VPC', 'AWS CloudWatch', 'AWS NAT Gateway', 'MongoDB', 'Pulumi', 'Ansible', 'JWT],myRole:Full Stack DevOps Engineer,Description: SimplyDone is an enterprise-grade, cloud-native To-Do application built with React.js (with Tailwind CSS, Shadcn UI, Firebase authentication) and Node.js/Express backend. The application implements JWT-based authentication and uses MongoDB for data persistence. The architecture features Docker containerization with images hosted on Docker Hub, automated AWS infrastructure provisioning via Pulumi (IaC), and deployment orchestration through Ansible. The backend is deployed across multiple AWS EC2 instances within private subnets using an Auto Scaling Group (min: 1, desired: 2, max: 5) with CloudWatch-based CPU metrics triggering scale-up/down policies. An Application Load Balancer distributes traffic with health checks, while the frontend runs on a dedicated EC2 instance in a public subnet. The infrastructure includes VPC with public/private subnets across multiple AZs, NAT Gateway for outbound traffic, and a dedicated MongoDB instance in a private subnet. Security is enforced through AWS Security Groups with least-privilege access patterns.,};R-Queue - Distributed Job Queue System
constproject={name:'R-Queue - Distributed Job Queue System',tools: ['React.js', 'TypeScript', 'Node.js', 'Express', 'Redis Cluster', 'Bull Queue', 'Docker', 'Docker Compose', 'AWS EC2', 'AWS VPC', 'AWS NAT Gateway', 'AWS Security Groups', 'AWS CloudWatch', 'Pulumi', 'Ansible', 'Vite],myRole:Full Stack DevOps Engineer,Description: R-Queue is a production-grade, fault-tolerant distributed job queue system built with React.js/TypeScript frontend and Node.js/Express backend, utilizing Redis Cluster for high-availability task management. The system implements priority-based job scheduling with automatic worker scaling (1-10 workers per instance), exponential backoff retry logic, dead letter queue for failed jobs, and real-time progress tracking. The architecture features a 6-node Redis Cluster (3 masters, 3 replicas) deployed across separate EC2 instances for data redundancy and horizontal scalability. Infrastructure provisioning is fully automated via Pulumi IaC, managing AWS VPC with public/private subnets across multiple AZs, NAT Gateway for outbound connectivity, and Security Groups with least-privilege access. Ansible orchestrates the deployment pipeline, handling Redis cluster formation, backend/frontend configuration, and service initialization. The frontend monitoring dashboard provides real-time insights into worker health, queue metrics, job statuses (pending, processing, completed, failed), and system throughput. The system implements circuit breaker patterns for fault isolation, job dependency management for complex workflows, and dynamic workload distribution with CloudWatch metrics integration for observability.,};Educations
2021 - Present
Bachelor in Computer Science And Engineering
CCN University of Science & Technology
2018 - 2020
Higher Secondary Certificate
Government Shaheed Suhrawardy College
2016 - 2018
Secondary School Certificate
Bangodda Iqra Model School