Ajmal Khan

• Designed and deployed a production-grade Kubernetes cluster using kubeadm, containerd with worker nodes across regions for fault tolerance and redundancy. • Prior to deployment and infrastructure provisioning, the Kubernetes (k8s) cluster was created using kubeadm as the core tool, containerd as the container runtime, and kubelet as the service. Other essential k8s components were provisioned using static pods, configured in the `/etc/kubernetes/manifests` directory. • Secured k8s components with self-signed and CA-signed certificates, and established secure SSH for cluster management. • Automated CI/CD pipelines using Jenkins to extract application code from GitHub, containerize microservices (authentication, payments, scheduling, etc.) with Docker, to ensure high availability. • Provisioned infrastructure using Terraform (IaC) and deployed the multi-tier application on AWS, ensuring zero downtime and seamless integration. • Conducted stress testing and containerized dependencies to maintain uninterrupted application performance. • Provisioned AWS infrastructure using Terraform and deployed a multi-tier application on AWS EKS with a microservices architecture, integrated hybrid nodes from on-premises infrastructure. • Developed secure REST APIs using Python's Django REST Framework, integrated with Celery and Redis for asynchronous task processing and scalability. • Designed a secure VPC with public/private subnets, leveraging AWS CloudWatch, NAT/Internet Gateways, ACM, IAM, and EC2 bastion hosts for robust and secure deployments. • Utilized AWS EKS managed control plane and worker nodes to deploy containerized applications with restricted network policies for enhanced security. • Monitored and troubleshooted Kubernetes clusters and applications using Prometheus, Grafana, and DaemonSets, deploying Prometheus within the cluster to reduce costs and centralize monitoring.

• Developed a production-grade Kubernetes cluster using kubeadm and deployed a multi-tier application on it. Worker nodes from different regions were joined to Master nodes to enhance fault tolerance and geographic redundancy. • Prior to deployment and infrastructure provisioning, the Kubernetes (k8s) cluster was created using kubeadm as the core tool, containerd as the container runtime, and kubelet as the service. Other essential k8s components were provisioned using static pods, configured in the `/etc/kubernetes/manifests` directory. • The k8s components were secured using self-signed and CA-signed certificates, and a secure SSH connection was established for cluster and application management. • The application code was extracted from GitHub using Git cloning, facilitated by Jenkins, a DevOps tool used to create the CI/CD pipeline. • After code extraction, the application was split into multiple independent pieces of software (microservices) in collaboration with software engineers. These included separate modules for authentication, payments, scheduling, email notifications, and more, adhering to the principles of microservices architecture. • Each microservice was containerized using Docker as the image-building tool, ensuring that if one service failed, others would continue to function as expected. This approach aligns with DevOps best practices. • The lifecycle of the application was tracked, and all necessary components and dependencies were containerized to ensure the main application process ran seamlessly without interruptions. • Before deploying the application using Kubernetes and AWS, the infrastructure was provisioned using Terraform as an Infrastructure as Code (IaC) tool. • By following these DevOps practices, the infrastructure, Kubernetes cluster, applications, and databases were provisioned securely, with a robust pipeline that ensured zero downtime for the cluster and its associated applications.

• Provisioned AWS infrastructure using Terraform and deployed a multi-tier application on AWS EKS with a microservices architecture, integrated hybrid nodes from on-premises infrastructure. • Developed secure REST APIs using Python's Django REST Framework, integrated with Celery and Redis for asynchronous task processing and scalability. • Designed a secure VPC with public/private subnets, leveraging AWS CloudWatch, NAT/Internet Gateways, ACM, IAM, and EC2 bastion hosts for robust and secure deployments. • Utilized AWS EKS managed control plane and worker nodes to deploy containerized applications with restricted network policies for enhanced security. • Configured Application Load Balancer (ALB) using AWS Load Balancer Controller (LBC) for efficient traffic routing and scalability. • Monitored and troubleshooted Kubernetes clusters and applications using Prometheus, Grafana, and DaemonSets, deploying Prometheus within the cluster to reduce costs and centralize monitoring.

• Developed and deployed a full-stack monolithic application on a Debian-based Linux server using JavaScript, Python, and PostgreSQL. • Designed a decoupled architecture with React frontend and Django REST Framework backend, integrated via CORS, and deployed as individual services on Ubuntu. • Built dynamic UIs with React, Redux, Yup, Axios, and Recharts, and implemented secure REST APIs with JWT/OAuth (Google) authentication. • Optimized SQL queries to ensure efficient database design and management. • Utilized PostgreSQL database performance, managed application files and directories following Linux filesystem hierarchy (FHS) standard, and configured backups using pgBackRest for disaster recovery.