Cloud & DevOps Engineer - AWS & IaC Expert

SRIVARDHAN VALLABHANENI

Cloud & DevOps Engineer

+91-733******* ************@*****.***

LinkedIn: https://in.linkedin.com/in/srivardhan1228 Portfolio: https://vardhan1228.github.io/Portfolio/ PROFESSIONAL SUMMARY

Detail-oriented Cloud & DevOps Engineer with experience in AWS cloud services, CI/CD pipelines,Infrastructure as Code (Terraform), containerization, and monitoring tools. Strong background in automating cloud infrastructure, deploying scalable applications, and mentoring learners in real-world DevOps practices. Passionate about continuous learning, cloud optimization, and implementing DevOps best practices in production-like environments.

TECHNICAL SKILLS

Cloud Platforms: AWS, Azure, Google Cloud Platform (GCP) Amazon Web Services (AWS): EC2, S3, RDS, VPC, IAM, Lambda, CloudWatch, CloudTrail, Auto Scaling, Route 53, CloudFront, AWS Database Migration Service (DMS), Elastic Container Registry (ECR), Elastic Kubernetes Service (EKS), AWS Systems Manager.

Microsoft Azure: Azure Virtual Machines, Azure Blob Storage, Azure SQL Database, Azure Virtual Network

(VNet), Azure Active Directory (AAD), Azure Monitor, Azure Kubernetes Service (AKS), Azure DevOps. Google Cloud Platform (GCP): Compute Engine, Cloud Storage, Cloud SQL, Virtual Private Cloud (VPC), Identity and Access Management (IAM), Cloud Monitoring and Logging. Infrastructure as Code: Terraform, CloudFormation, OpenTofu CI/CD & Automation: Jenkins, GitHub Actions, GitLab CI/CD, Argo CD Containers & Orchestration: Docker, Kubernetes, Helm, EKS, ECS, AKS, GKE Configuration Management: Ansible

Monitoring & Logging: Prometheus, Grafana, ELK Stack, CloudWatch, New Relic, AWS CloudTrail Security & DevSecOps: IAM, WAF, KMS, GuardDuty, Trivy, SonarQube Networking: VPC, Load Balancers, Route 53, Nginx, Ingress Controller, Reverse proxy Version Control: Git, GitHub, GitLab

Scripting : Bash, Python, Shell script

Operating Systems: Linux (Ubuntu, Amazon Linux), Windows Migration services : Aws Glue (Etl), Dms, Aplication migration service PROFESSIONAL EXPERIENCE

DevOps Intern

Techeazy Consulting May 2025 – June 2025

• Automated AWS infrastructure provisioning using Terraform, including custom VPCs and EC2 instances.

• Developed user data scripts to automate application deployment and Git repository cloning.

• Implemented EC2 shutdown automation to archive application code and logs to Amazon S3.

• Gained strong hands-on experience with AWS services, IaC, and DevOps automation workflows. DevOps Intern

Elevate Labs Oct 2025 – Dec 2025

• Worked with DevOps teams to build and enhance CI/CD pipelines.

• Assisted in deploying applications on AWS and Azure cloud platforms.

• Implemented containerization workflows using Docker.

• Supported monitoring and logging setup to improve system reliability and performance.

• Collaborated in an Agile environment, ensuring smooth DevOps and development integration. PROJECTS

Seamless Database Migration from EC2 to RDS using AWS DMS

• Migrated on-premises databases to AWS RDS using Database Migration Service (DMS).

• Configured DMS replication instances and validated source and target endpoints.

• Monitored migration tasks to ensure data integrity and minimal downtime. Containerized Application Deployment on AWS EKS with RDS

• Built CI/CD pipelines using Jenkins, Terraform, Argo CD, and Kubernetes (EKS).

• Containerized and deployed Node.js applications using Docker and Kubernetes.

• Implemented monitoring using Prometheus and Grafana for application health and performance. Microservices Application Deployment & Database Management on AWS

• Designed and deployed infrastructure using Terraform, EC2, RDS, Auto Scaling Groups, Route 53, and CloudFront.

• Implemented a three-tier architecture with high availability and multi-region resilience.

• Ensured application reliability through CloudWatch monitoring and optimization. Cross-Cloud ETL Pipeline Using AWS Glue (GCP to AWS)

• Built a cross-cloud ETL pipeline using AWS Glue (PySpark) to extract data from GCP Cloud SQL and land raw data in Amazon S3 via JDBC.

• Performed data cleansing and transformations in Glue, storing curated datasets in a separate S3 processed layer.

• Loaded transformed data from S3 into Amazon RDS, with monitoring and scheduling via CloudWatch and Glue Triggers.

AI-Driven Loan Approval & Risk Prediction System on AWS

• Developed and trained an AI-based loan approval and risk prediction model using customer financial data.

• Built a REST API using Flask/FastAPI and deployed the model on AWS EC2 for real-time predictions.

• Implemented data preprocessing, feature engineering, and model evaluation to improve prediction accuracy.

EDUCATION

Bachelor of Technology (B.Tech)

Sree Vahini institute of science and technology tiruvuru 2023 DECLARATION

I hereby declare that the information provided above is true and correct to the best of my knowledge and belief.

Srivardhan Vallabhaneni

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