Projects
Cloud Infrastructure Deployment for Scalable Web Applications Using Terraform.
A growing web application needed scalable, reliable, and cost-effective cloud infrastructure. The manual setup of cloud resources was error-prone, time-consuming, and not reproducible across environments. The application required high availability, auto-scaling, and infrastructure as code (IaC) for better management.
Task:
Design and implement infrastructure automation using Terraform for AWS-based deployment.
Implementation:
Developed and deployed an automated, scalable cloud infrastructure on AWS using Terraform, ensuring consistency, efficiency, and maintainability across environments.
The following tasks were executed using Terraform to achieve the desired infrastructure setup:
- Remote State storage with AWS S3 and DynamoDB Locking
- ALB context path-based path routing or ALB Host Header based routing
- AWS Network Load Balancer with Auto-scaling groups
- AWS CloudWatch Alarms, Synthetics
- Develop Local Terraform reusable modules
Therefore, by implementing the above tasks, achieved 100% infrastructure automation, reducing deployment time from hours to minutes. Enabled cost optimization by implementing auto-scaling, shutting down non-production instances during off-hours. Facilitated faster rollbacks and disaster recovery through version-controlled infrastructure.
Click the below button to view the templates used.
Engineered the pipeline for developing the Java web application.
The Tools used are as follows:
Jenkins - CICD implementation.
SonarQube - Source code Analysis.
Maven - Artifact creation and unit testing.
Amazon S3 - Artifact storage.
Nexus - Artifact storage.
This pipeline includes the following tasks:
fetching the source code from GitHub repository.
Building the artifact using Maven.
Unit testing after creation of artifact.
Check style analysis was utilized.
Source code Analysis using SonarQube Server / Sonar Cloud and Quality gates are also utilized.
Uploading the generated artifact into S3 or Nexus.
Click the below link for the pipeline script of this project.
Continuous Delivery of Java web application.
CICD for containers
Continuous Integration and Continuous Delivery of Containers.
Why Docker images?
Docker is a tool which is used to isolate the service/application and is widely used in microservice architecture.
Docker containers provide complete isolation of the web application which is an advantage over normal process. So, packaging the web application of type Nodejs or Java or any other type in Docker images is necessary in today's world.
Docker allows us to update on 1 microservice while the rest of them working/running as usual (without stopping them). This is Loosely coupled architecture.
Instead of storing the generated artifact in S3 or Nexus. The same artifact is utilized to create the Docker image.
This project is all about Continuously building docker images and deploying the newly generated image from Docker Hub / Amazon ECR to Kubernetes cluster.
There are several tools are available in the market for Container Orchestration like Docker Swarm, Kubernetes, AWS EKS & ECS, Mesosphere Marathon, Azure container service, Google container engine, OpenShift, Nomad...
In this project, below tools are utilized:
Docker - For creating Docker images.
Docker Hub or Amazon ECR - For storing the Docker image.
Kops in AWS - Kubernetes Cluster.
Helm charts - For deploying the container / pod in K8 cluster.
Click the below link for the pipeline script used for this project:
The following are some of the projects which involve AWS EKS:
1. Kubernetes Auto Scaling in AWS EKS
Implemented Horizontal Pod Autoscaler (HPA) and Vertical Pod Autoscaler (VPA) to dynamically scale workloads based on CPU/memory utilization.
Configured Cluster Autoscaler to automatically adjust the number of worker nodes based on demand, optimizing cost and performance.
2. Microservices Observability with AWS X-Ray
Integrated AWS X-Ray for distributed tracing across microservices running on EKS.
Enhanced application monitoring and debugging by visualizing request flows and latency issues.
3. Serverless Kubernetes with AWS EKS Fargate
Deployed microservices on AWS EKS Fargate, enabling a serverless Kubernetes architecture with zero node management.
Optimized cost and operational overhead by running workloads without provisioning EC2 instances.
4. ALB Ingress Controller – Advanced Routing
Configured AWS Application Load Balancer (ALB) Ingress with context path-based routing, efficiently directing traffic to appropriate microservices.
Implemented host-based routing (name-based virtual hosting) to serve multiple domains from a single ALB.
5. Secure Traffic Management & SSL Implementation
Enforced HTTPS with SSL certificates for all ingress traffic using ALB Ingress and redirected HTTP to HTTPS to enhance security.
Integrated External DNS to dynamically update DNS records based on Kubernetes services, ensuring seamless domain resolution.
6. Microservices Deployment on AWS EKS
Designed and deployed containerized microservices on Amazon EKS with rolling updates, blue-green deployments, and canary releases using Helm and Customize.
Optimized application resilience with Kubernetes-native features like Liveness and Readiness probes.
Click the below link to view the projects: