● Collaborated with data scientists to provide a reliable continuous updating ML model forecasting service to end-users. github.com/cy235/CICD_ML_AWS● Used Terraform to build development, staging, and production environments with AWS EC2s in AWS VPC cloud. Built a CI/CD infrastructure to automatically build, test, and deliver/deploy the ML model. ● Automated continuous integration processes with CircleCI including unit test, source code test, QA test, and failure notifications. Continuously deployed the ML model into AWS EC2 servers with a blue/green deployment strategy (by employing the auto-scaling scheme and a load balancer). ● Managed GitHub repositories and permissions, including branching, merging, and tagging.● Eliminated 80% of the manual work of the data scientist, reduced human error, mitigated the risk of new features in production, and achieved zero-downtime deployment.

● Collaborated with developers to build a CI/CD pipeline with Jenkins and Ansible to continuously integrate a web application image and delivered it into the Docker Hub, then continuously deployed this application at scale into the Kubernetes cluster with high availability and reliability. Actively monitor the application service using Prometheus and Grafana. github.com/cy235/Jenkins_K8S_Grafana● Developed a full stack social media web application with Django framework with Python, HTML, JavaScript, CSS, Bootstrap. Performed version control with the GIT. Deployed the web application into the AWS EC2. github.com/cy235/SocialApp | www.starsocial.club ● Developed a real practical ticket ordering web application consisting of 6 microservices built with React, Node, Express, and MongoDB, leveraged Github Actions to continuously integrate, test and deliver microservice images into the Docker Hub, then continuously deploy them into the Kubernetes cluster with high availability. github.com/cy235/ticketing● Wrote Ansible Playbooks and shell script to deploy, configure, and manage servers, reducing deployment times from 5+ hours to less than 2 minutes. ● Worked with colleges to deploy a scalable and highly available PostgreSQL database on Amazon Elastic Kubernetes Service (EKS) using Kubernetes persistent volumes. github.com/cy235/PostgreSQL_EKS● Instructed the students with hands-on practice to provision a MongoDB sharded on-premise cluster with Ansible in Centos in an easy-understanding way github.com/cy235/Ansible_MongoDB_Cluster● Built an ETL (extract, transform, load) pipeline that extracts the data from the buckets hosted on S3, processes them using Spark which will be deployed on an EMR cluster using AWS, and loads the data back into S3 as a set of dimensional tables in parquet format. ​github.com/cy235/DE_AWS_S3_Spark