Shards of fixed capacity, partition keys hashed to ranges, three copies in three AZs, live resharding, polling and push readers with KCL leases.
Data engineers building storage, streaming and processing systems.
Your approach: Use diagrams or prose for data contracts, state ownership, throughput, ordering and recovery where the brief requires them.
Design a Data Stream like Amazon Kinesis. Shards of fixed capacity, partition keys hashed to ranges, three copies in three AZs, live resharding, polling and push readers with KCL leases. Work from the scoping questions below. State assumptions for any unspecified load, guarantee or target, then trace your design end to end. Explain one difficult case and a credible alternative; the worked example is a reference, not a required implementation.
Resolve the scoping questions for a Data Stream like Amazon Kinesis. Separate stated behavior from assumptions, and identify what is outside your design.
Declare relevant volume, latency, freshness, quality or cost targets with units. Show calculations or an evaluation plan that can test them; unspecified targets are your assumptions, not hidden pass criteria.
Explain how your guarantees hold in a difficult case relevant to this subject. Address: Retention? Exactly once?
Identify users, required behavior and exclusions. Answer: Who uses it? What does a shard promise?
Define the information owned by the system and the inputs, outputs and errors at its boundaries. Resolve: What does an ack mean? How fast?
Estimate the dominant workload and resource demand with units and explicit assumptions. For a learned system, also state how quality is measured and what data is available.
Draw or describe the responsibilities needed for a Data Stream like Amazon Kinesis. Trace a representative request, event or job from its input to a visible result; identify durable state owners.
Walk through a difficult case step by step, including detection and recovery. Consider: How many readers? Does capacity change live? Retention? Exactly once?
Compare a credible alternative using your chosen workload and guarantees. Explain a remaining risk, a signal to watch and when you would change the design.