hello, I'm Praneeth.

At Prodapt, I worked on a large-scale network monitoring project, collecting telemetry data from thousands of devices with varying data rates and formats. I built the infrastructure to manage this data, keeping the architecture simple and strong. A major task was decoding a specific IPFIX data stream format. After existing decoders failed, I found a suitable one on GitHub and collaborated with its developers in the Czech Republic to configure it correctly.

After setting up the data flow, I developed Go and Kafka pipelines to process millions of data points hourly, using minimal dependencies for reliability. I also wrote Python validation functions to ensure data quality, which led to cleaner analytics. To complete the project, I set up a simple and reliable CI/CD pipeline using GitHub Actions.

At Wells Fargo, I worked on critical payment processing systems. My main focus was building APIs for thousands of daily payment requests, emphasizing clean and maintainable code. I also concentrated on improving database performance. I optimized PostgreSQL by refining indexing strategies and query patterns, which significantly reduced query times and improved the user experience.

I created a GraphQL gateway to combine several microservices into a single, clean interface. This simplified the process for clients, allowing them to get all necessary data in one request instead of making multiple calls. I also built a Kubernetes deployment pipeline designed for high availability and simplicity, ensuring our financial transaction systems ran without downtime.

In my first major role at Lumen, I worked on monitoring telecom infrastructure. I built a real-time dashboard to visualize network outages by pulling data from SNMP traps and syslog streams. The interface was minimal, showing only the essential information engineers needed. I improved our Node.js backend by adding Redis caching, which greatly increased the API's capacity to handle traffic.

My first project with AWS Lambda taught me about the simplicity and scalability of serverless architecture. I optimized our alert functions to lower costs and reduce latency. Using Terraform for infrastructure as code was another key learning. It allowed me to create repeatable, version-controlled environments with just a few commands, applying a minimalist approach to cloud infrastructure.