Shyam Sabhaya is a software engineer with nine years of experience building reliable backend systems and cloud infrastructure, currently working at Google in New York. He has strong hands-on experience with cloud platforms—contributing to the widely used PerfKit Benchmarker by adding AWS and Azure features like VPC peering, placement groups, quota handling, and spot-instance support to improve multi-cloud benchmarking fidelity. Prior roles include product-focused engineering at Trustwork, an internship building transfer workflows for Amazon Flex, and systems-level work at AT&T and Broadcom that improved testing automation and network routing. Comfortable across DevOps, backend services, and infrastructure automation, he leans toward robust, production-ready solutions that account for real-world limits and failure modes. An early background in computer engineering and teaching recitation sections reflects both technical depth and a knack for mentoring and clear documentation. Notably, his open-source contributions improve cross-cloud comparability, a subtle but impactful focus that benefits cloud users and researchers alike.
9 years of coding experience
1 year of employment as a software developer
Bachelor of Science - BS, Computer Engineering, Bachelor of Science - BS, Computer Engineering at The University of Texas at Austin
PerfKit Benchmarker (PKB) contains a set of benchmarks to measure and compare cloud offerings. The benchmarks use default settings to reflect what most users will see. PerfKit Benchmarker is licensed under the Apache 2 license terms. Please make sure to read, understand and agree to the terms of the LICENSE and CONTRIBUTING files before proceeding.
Role in this project:
Back-end & DevOps Engineer
Contributions:16 reviews, 75 commits, 14 PRs in 2 years 7 months
Contributions summary:Shyam primarily contributed to the AWS and Azure infrastructure for the PerfKit Benchmarker project. They added support for VPC peering and placement groups, enhancing the network configurations for various cloud environments. Additionally, the user implemented features to handle quota limits, spot instances, and other cloud-specific resource handling. The changes demonstrate a focus on improving the functionality and reliability of the benchmarking tool across different cloud platforms.
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