Cloud & DevOps Engineer | 3+ Years Experience | ML Enthusiast

Passionate about building scalable, secure, and automated cloud infrastructure. Specialized in implementing DevOps best practices and MLOps pipelines that bridge the gap between development and operations.

• 🔭 Currently working on Enterprise Kubernetes platforms & MLOps automation
• 🌱 Learning Service Mesh architectures & Advanced MLOps patterns
• 👯 Open to collaborate on Cloud-native applications & ML infrastructure
• 💬 Ask me about AWS/Multi-cloud, Kubernetes, Infrastructure as Code, ML Pipelines
• 📫 Reach me: [email protected]
• 📍 Location: Dhaka, Bangladesh
• ⚡ Philosophy: "Automate everything, monitor everything, secure everything"

• Cloud Platforms: AWS (Advanced), Azure, Google Cloud Platform
• Container Orchestration: Kubernetes, Docker, Helm, Service Mesh
• Infrastructure as Code: Terraform, Ansible, CloudFormation
• CI/CD & GitOps: Jenkins, GitLab CI, GitHub Actions, ArgoCD
• Observability: Prometheus, Grafana, ELK Stack, Distributed Tracing
• MLOps: MLflow, Kubeflow, Apache Airflow, Model Deployment

• 🎯 AWS Certified Solutions Architect - Associate (2023)
• 🎯 AWS Certified Cloud Practitioner (2022)
• 🎯 Kubernetes Administrator (CKA) - In Progress
• 🎯 Terraform Associate - Planned 2024

Tech Stack: Kubernetes, MLflow, Apache Airflow, AWS EKS

• Automated ML model training and deployment pipeline reducing deployment time by 70%
• Implemented GitOps workflow with ArgoCD for continuous delivery
• View Project

Tech Stack: Terraform, Ansible, AWS/Azure/GCP

• Infrastructure as Code solution managing 50+ cloud resources across multiple providers
• Implemented security best practices with HashiCorp Vault integration
• View Project

Tech Stack: Prometheus, Grafana, Jaeger, ELK Stack

• Complete observability solution with distributed tracing and log aggregation
• Reduced MTTR by 60% through comprehensive monitoring and alerting
• View Project