Real questions from top companies in System Design/Architecture
Discuss data replication strategies in Kafka for fault tolerance.
Discuss designing a data pipeline for a specific use case
Discuss the deployment process for real-time applications using CI/CD pipelines.
Discuss trade-offs between serverless and traditional cloud data architectures.
Discuss trade-offs when designing a batch vs. real-time processing system.
Discuss your experience with ETL (Extract, Transform, Load) processes. What tools and techniques have you used to ensure efficient data extraction and transformation?
Explain AWS Glue Data Catalog.
Explain Spark's fault tolerance mechanisms.
Explain batch vs real-time processing choices and their trade-offs.
Explain deployment architecture for big data.
Explain how Spark handles fault tolerance. How does it recover from node failures?
Explain how serverless computing impacts modern data architecture.
Explain how you would design a pipeline for streaming real-time order status updates.
Explain how you would optimize a data lake architecture for performance and cost-efficiency
Explain project architecture, technical contributions, and value delivered.
Explain the CAP theorem and its relevance in distributed systems.
Explain why lineage in Spark is crucial for fault tolerance.
Given a problem statement, collaborate with your team to design the entire pipeline architecture.
Handle schema evolution in production.
Handling pipeline bugs
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