About

Manikanda Krishnan is a Research Engineer at Philips with a passion for automating tasks and experimenting with different scenarios. He believes in using data to draw inferences and has a keen interest in data modeling and analysis. Manikanda is a functional programming enthusiast and applies this knowledge while writing MapReduce/Spark programs or analyzing Hive queries. He has a good understanding of Solr and Spark internals and continues to learn as he works with them. Manikanda has worked as a Senior Software Engineer at Visa, where he primarily worked on predictive platform analytics, building ways to predict job runtimes and wait times. He built a comprehensive test suite for testing Solr and Spark to avoid post-maintenance issues and automated large parts of post-maintenance validations and pre-maintenance backups. Manikanda was the Solr SME for an application that would stamp location details for transactions, helping improve the throughput for the application to reach 3200 TPS in a collection with a single shard-single replica. He also helped test and find issues with the fair scheduler as part of their migration from capacity scheduler and enabled master-slave for their KDC servers. Manikanda has a Bachelor of Technology (Hons) in Electronics Engineering from the Indian Institute of Technology (Banaras Hindu University), Varanasi. He has 7.20 years of relevant experience and has authored several papers, including a validation paper of a model developed by him, and two first-author (joint) papers. Manikanda's tech stack includes Research Scientist, Spark, test, MapReduce, Apache Hive, and Hadoop.