During August 2025, Teja Gudivada focused on enhancing the stability and observability of Spark’s Shuffle Service within the apache/spark repository. He addressed a critical issue in the deserialization of Push-Based Shuffle metrics, ensuring accurate logging and retrieval in the Spark History Server. By correcting the metrics deserialization process, Teja improved the reliability of monitoring and troubleshooting for Spark pipelines, reducing discrepancies across runs. His work maintained compatibility and performance with existing workflows, demonstrating a strong command of Scala, Spark, and unit testing. The depth of his contribution lay in resolving a nuanced bug that directly impacted operational transparency and reliability.