Swetha Banagiri

MAJOR PROJECTS

• Automated the ISO creation process for Ubuntu 22.04 Upgrade on more than 1000 Client Devices. This provided error-free and reduced manual hours for creating the iso file.
• Enhanced application reliability by establishing an end-to-end monitoring service, leveraging data analysis to configure proactive alerts through platforms like Chronosphere and Spinnaker.
• Employed Terraform in conjunction with Spacelift to seamlessly provision AWS resources and automate the deployment of containerized applications within AWS EKS clusters. This approach streamlined infrastructure management and deployment workflows, optimizing efficiency and reliability

Created an interactive and real-time Utilization Dashboard to monitor server capacity through Kubernetes pod scheduling for 50+ teams running hundreds of application per hour. The analysis of metrics revealed a significant number of underutilized servers, contributing to a 30% reduction in the allocated budget for adding additional capacity.

Technologies: ELK Stack, Python3, Kubernetes

Major Accomplishments:

1. “Big Data Orchestration”- A Touchless CI-CD Deploy pipeline for Software and OS upgrades. Saved 80% of manual deployment hours by by auto-scheduling and upgrading clusters by implementing service controller framework.

2. Accelerated batch-wise system deployment by 90% i.e 2 days per upgrade to 5 hours per upgrade by automating the pipeline on around 5k+ remote servers.

3. “Exploiting Machine Learning to Keep Hadoop Clusters Healthy” was presented at Hadoop DataWorks Summit, San Jose (2018). Achieved prediction of potential Disk failures to ensure high Data availability based on SMART stats emitted by each disk.

Job Roles and Responsibilities:

1. Maintain Big Data applications hosting Hadoop, Storm, HBase, Spark and low latency services like Hive, HCatalog, Oozie, Presto and more

2. Develop CI/CD pipelines across cross-functional teams with non uniform deploy environments

3. Build in-house tools to accelerate the System/Software upgrades on clusters

4. Schedule and run cluster/component deployments

5. Design scripts for monitoring various services and functionalities

6. Support Oncall rotation for handling critical customer and system issues

Graduate Assistant for the following courses:

1. [CS461] Artificial Intelligence - LISP, Prolog & Python

2. [CS221] Computer Organization & Assembly Language - MIPS Assembly Language

AR Project using Hololens on Object Detection and Tagging

Technologies: Unity, MRTK, Python - Numpy, Keras, Theano

Teaching Instructor [CS101] Computer Science I - Python Programming Language