Start by naming 2-3 frameworks you know well, then briefly explain their core model (e.g., batch vs. stream, micro-batch vs. true streaming) and a trade-off you've encountered. Tailor your answer to the role by connecting frameworks to real-world use cases like real-time analytics or ETL pipelines.
Pro tip: Don't just list frameworks—show depth by comparing two (e.g., Kafka Streams vs. Flink) on a specific dimension like latency or state management. This demonstrates you understand trade-offs, not just buzzwords.
List 3-4 frameworks you know, grouping them by processing model (batch, stream, or hybrid) to show structured knowledge.
Pick one or two frameworks you've used in production and describe a concrete project or problem you solved with them.
Compare frameworks on dimensions like latency, throughput, fault tolerance, or ease of use, referencing specific scenarios.
Explain how you'd choose a framework for a given system design problem, considering requirements like exactly-once semantics or backpressure.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Define each delivery semantic clearly, then walk through implementation strategies for each, and finally compare their trade-offs in terms of reliability, complexity, and performance. Use real-world examples like message queues or RPC to ground your explanation.
Pro tip: Emphasize that exactly-once is often achieved through idempotency and deduplication rather than true end-to-end guarantees, and mention that the choice depends on the system's requirements and constraints.
Clearly state what at-most-once, at-least-once, and exactly-once mean in terms of message delivery guarantees.
Describe how each semantic can be implemented, including techniques like acknowledgments, retries, idempotency, and transactional messaging.
Compare the trade-offs: at-most-once is simple but may lose messages; at-least-once ensures delivery but may duplicate; exactly-once is ideal but complex and costly.
Give examples of systems that use each semantic, such as UDP for at-most-once, TCP for at-least-once, and Kafka transactions for exactly-once.
Summarize how to choose the right semantic based on application needs, such as tolerance for loss vs. duplication and performance requirements.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.