Distributed-Systems Reasoning for Data Workloads

Distinguish throughput, latency, scalability, and availability requirements in a production data workload.

Select a data-partitioning strategy for a specified access pattern and workload distribution.

Explain how replication and quorum choices affect consistency and availability.

Analyze the CAP and PACELC trade-offs in a concrete failure scenario.

Trace at-most-once, at-least-once, and effectively-once processing behavior under retries.

Identify failure domains and blast radius in a distributed data architecture.