Anusha Vuppala

Project: Healthcare Application Management

Technologies Used: AWS EC2, Amazon S3, Amazon RDS, Elastic Load Balancer (ELB), Amazon CloudWatch, AWS IAM, AWS Route 53, Terraform, Docker, Kubernetes (AWS EKS), and Jenkins.

The Telemedicine Platform was developed to enable seamless and secure real-time video consultations between healthcare providers and patients, while also managing patient information efficiently. The platform was designed to meet the rising demand for remote healthcare by ensuring high availability, robust security, and scalable performance, especially during peak usage. It integrates video communication, appointment scheduling, and secure storage for sensitive medical data, offering a comprehensive healthcare solution.

Day-to-Day Work:

• EC2: Hosted the core application and services, including video consultation APIs and patient management systems. Scaled compute power efficiently during high-demand periods.
• Amazon S3: Stored sensitive medical files with fast retrieval for healthcare providers, ensuring secure access through IAM policies.
• Amazon RDS: Managed structured data like patient records, appointments, and billing information, ensuring reliable storage and retrieval.
• Elastic Load Balancer (ELB): Distributed incoming traffic to instances during peak consultation hours, preventing outages and ensuring a smooth user experience.
• Amazon CloudWatch: Monitored the performance of EC2 instances, RDS databases, and Kubernetes clusters, generating alerts for system anomalies.
• AWS IAM: Implemented role-based access controls for healthcare professionals and administrators to maintain compliance with security standards.
• AWS Route 53: Managed DNS routing, ensuring seamless access for healthcare providers and patients.
• Terraform: Automated provisioning and management of AWS resources, reducing errors and ensuring consistent infrastructure deployment.
• Docker: Containerized services like video consultation and API servers to streamline deployment and reduce dependency issues.
• Kubernetes (AWS EKS): Managed containerized applications, ensuring high availability and scalability for real-time consultations.
• Jenkins: Automated the build, test, and deployment pipelines for the telemedicine platform, reducing time to market and ensuring application stability.

Project: Migration from Monolithic to Microservices Architecture

Technologies Used: AWS EC2, Amazon S3, Amazon RDS, Elastic Load Balancer (ELB), Amazon CloudWatch, AWS IAM, AWS Route 53, Terraform, Docker, Kubernetes (AWS EKS), and Jenkins.

The Customer Support Ticketing System was originally built as a single monolithic application, which had difficulty handling increased traffic and scaling efficiently. To overcome these issues, we migrated to a microservices architecture. This change allowed us to scale the system, improve performance, and make it easier to manage.

Day-to-Day Work:

• EC2: Hosted the main services of the system, allowing us to quickly scale computing power during high-demand periods.
• Amazon S3: Stored customer tickets and related files securely, with fast access for support teams.
• Amazon RDS: Managed structured data like customer ticket details and user information, ensuring secure and reliable data storage.
• Elastic Load Balancer (ELB): Balanced the traffic across multiple servers to prevent overload during peak hours, ensuring smooth service for users.
• Amazon CloudWatch: Monitored the system's performance and alerted us to any issues, helping us fix problems quickly before they impacted users.
• AWS IAM: Controlled who could access the system, ensuring only authorized users could see sensitive data.
• AWS Route 53: Managed domain names, ensuring customers could access the system without any interruptions.
• Terraform: Automated the setup of AWS resources, reducing manual errors and ensuring consistent infrastructure across different environments.
• Docker: Containerized each part of the system (like ticket management and notifications) so they could be deployed easily and independently.
• Kubernetes (AWS EKS): Managed the containers, ensuring they scaled automatically based on demand and stayed available.
• Jenkins: Automated the process of building, testing, and deploying new features, making updates faster and more reliable.

• Led the 2G and 3G Performance Management (PM) module in the FCAPS framework, optimising network performance.
• Managed end-to-end processing of network performance data, standardising it for the common PM database.
• ● Handled customer requests for C++ Modules, including enhancements, customizations, and problem reports.
• ● Participated in feature testing, troubleshooting in live environments, and mentoring new team members.
• ● Owned the ETLOAD engine, overseeing Software Configuration Management (SCM) and manual testing.
• ● Adapted the ETLOAD engine from HP-Unix to Linux, demonstrating cross-platform versatility.
• Established strong working relationships with clients to ensure clear communication of expectations and requirements throughout the project lifecycle.