Anastasia Vela is a Senior Software Engineer II based in Berkeley with nine years of hands-on experience building backend systems at Confluent and early-stage companies. A UC Berkeley graduate in Data Science and Cognitive Science, she blends strong data-driven reasoning with practical distributed-systems engineering. At Confluent she progressed from intern to senior levels working on Kafka-related infrastructure and contributed metrics and tests to the upstream Apache Kafka project to improve visibility into group and transaction metadata load times. Her background includes embedded systems work—developing Android apps and firmware update services for IoT sensors—which gives her a pragmatic edge when designing robust, observable services. Colleagues know her for shipping reliable backend features and for bringing a researcher’s attention to instrumentation and testability.
9 years of coding experience
6 years of employment as a software developer
Bachelor’s Degree, Data Science and Cognitive Science, Bachelor’s Degree, Data Science and Cognitive Science at University of California, Berkeley
High School, General Studies, 4.1 GPA, High School, General Studies, 4.1 GPA at Granada Hills Charter High School
Contributions:30 reviews, 6 commits, 8 PRs in 2 years 8 months
Contributions summary:Anastasia contributed to the Apache Kafka project by implementing and testing metrics for group and transaction metadata loading duration. This involved adding metrics to provide visibility into consumer group inactivity and writing unit tests to mock load times and verify metric values. The changes included modifications to `GroupMetadataManagerTest.scala` and `TransactionStateManagerTest.scala` to incorporate metrics for partition load times. Additionally, changes were made to the `GroupCoordinator.scala` file to include the new metrics.
Contributions:70 pushes, 15 branches in 3 years 8 months
kafka-streamsapache-kafkasinkkafka-consumerapache
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Anastasia Vela - Senior Software Engineer II at Confluent