Anusha Vuppala

Project: Healthcare Application Management

Description:
This project involves managing a highly available and scalable AWS cloud infrastructure for a telemedicine platform, which supports real-time video consultations for healthcare professionals and patients. The project required automating deployments, optimizing system performance, and ensuring the security of sensitive medical data.
Responsibilities & Achievements:

• Led the automation of cloud infrastructure for a high-traffic telemedicine platform, ensuring 24/7 availability and optimal performance for real-time video consultations.
• Designed and implemented CI/CD pipelines in Jenkins, leading to a 40% reduction in deployment failures and a significant improvement in release efficiency.
• Migrated workloads to AWS Fargate, streamlining microservices deployment and improving scalability for unpredictable traffic spikes.
• Automated configuration management and infrastructure setup using Ansible for Linux environments significantly reduces provisioning time and human error.
• Developed Ansible playbooks and roles for application deployments, system updates, and service restarts across hybrid infrastructure.
• Automated infrastructure provisioning with Terraform, enabling faster resource scaling and reducing manual intervention.
• Implemented security best practices for sensitive data protection, including IAM policies, S3 encryption, and RDS automated backups, ensuring compliance with industry standards.

Impact:

Successfully optimized the cloud infrastructure for the healthcare platform by leveraging Ansible for automated provisioning and configuration management, enhancing operational efficiency and security. This led to a 10% reduction in infrastructure costs while improving application uptime and performance during peak traffic.
Technologies: AWS (EC2, S3, RDS, Route 53, IAM, CloudWatch, Auto Scaling, Fargate, EKS),Terraform, Docker, Kubernetes, Jenkins, ELB and Ansible.

Project: Migration from Monolithic to Microservices Architecture

Description: This project focused on migrating a legacy monolithic system to a microservices architecture on AWS for improved scalability, reliability, and performance. The migration involved containerizing services, implementing Kubernetes for orchestration, and setting up automated CI/CD pipelines for continuous delivery. Responsibilities & Achievements:

• Led the migration of a legacy customer support system from a monolithic architecture to microservices hosted on AWS, resulting in improved system modularity and faster release cycles.
• Designed highly available EC2 instances and utilized Kubernetes (EKS) for container orchestration, resulting in a 20% improvement in resource utilization and a reduction in cloud costs.
• Designed and implemented Ansible-based automation for provisioning, patching, and managing infrastructure across Linux, and VMware.
• Automated cloud infrastructure provisioning using Terraform, enabling consistent deployments across environments.
• Implemented performance monitoring using AWS CloudWatch and cost optimization strategies, reducing operational overhead by 15%.

Impact:
Enabled the client to reduce time to market for new features and enhanced system reliability, resulting in an improved customer satisfaction score and reduced downtime.

Technologies: AWS (EC2, S3, RDS, Route 53, IAM, CloudWatch), Terraform, Docker, Kubernetes (EKS), Jenkins, ELB

Client: T-Mobile US

Project: Network Performance Monitoring and Optimization

Description:
As part of the FCAPS (Fault, Configuration, Accounting, Performance, Security) framework, this project focused on optimizing network performance for T-Mobile US, specifically in the 2G and 3G networks. The work involved developing C++ modules to enhance network analysis and migrating systems to more efficient platforms to improve system performance.
Responsibilities & Achievements:

• Led the development and optimization of C++ modules for network performance analysis in the FCAPS framework, enhancing network reliability and reducing downtime.
• Migrated the ETLOAD engine from HP-Unix to Linux, improving compatibility, performance, and scalability.
• Developed automated monitoring solutions using Perl and Unix shell scripts to ensure continuous system health monitoring.

Impact:
Improved network performance by 25%, enabling higher service availability and contributing to a more reliable communication system.

Technologies: C++, Linux, Perl, Unix, Network Performance Monitoring