Interview with Márton Balassi
summary
Contributes to Apache Flink for about three years, helped develop the first streaming API at the Hungarian Academy of Sciences and became a Flink PMC, maintains community projects and prototypes a streaming machine learning API. Highlights an upcoming release feature: dynamic scaling with state that lets long‑running jobs resize safely. Notes current use is mostly community work rather than daily production, points to industrial pilot users, and gives practical onboarding advice: join the developer mailing list, read docs and pick starter issues.
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