Alyssa Huang is a software infrastructure engineer with seven years of experience building and hardening distributed systems at Confluent, backed by a BS in Electrical Engineering and Computer Science from UC Berkeley. She contributes to core Kafka projects—working on REST proxy backends and KRaft controller improvements—bringing practical expertise in consumer group lag analysis, metadata versioning, and test modernization. Proficient in Python, Java, Scala, Go and C/C++, she pairs systems-level coding with strong data skills (SQL, R) and a history of applying ML/OCR to automate security workflows. Based in Mountain View, she blends production-facing backend engineering with a careful attention to reliability and observability that comes from working on mission-critical messaging infrastructure. An early maker, she also has experience in bioinformatics tooling and interactive visualization, showing a knack for translating complex data into actionable insights.
6 years of coding experience
1 year of employment as a software developer
Bachelor of Science (BS) Electrical Engineering and Computer Science, Bachelor of Science (BS) Electrical Engineering and Computer Science at University of California, Berkeley
Contributions:284 reviews, 8 commits, 50 PRs in 9 months
Contributions summary:Alyssa primarily contributed to the Kafka backend, focusing on enhancements related to the KRaft (Kafka Raft) controller and broker functionality. Their work involved refactoring code related to metadata versions, supporting KRaft in various tests like ReplicaFetchTest, and addressing issues related to controlled shutdown delays. They also worked on improving the tests by adding support for KRaft, and updating the tests to use latest stable metadata version.
Contributions:41 reviews, 105 commits, 19 PRs in 11 months
Contributions summary:Alyssa primarily contributed to the backend of the Confluent REST Proxy for Kafka project. The commits show changes related to consumer group lag, including the implementation of lag summary resources and data models. The user also made changes to the ConsumerOffsetsDao, which interacts with Kafka's admin client to retrieve consumer group offset information. This involved adding enhancements for calculating the lag of consumer groups.
schema-registryproxyconfluent-cloudrest-proxyrest
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