85. Design a Change Data Capture Pipeline

The brief

Design a Change Data Capture Pipeline. Every committed change in Aurora and DynamoDB, read from the log and delivered in order per row to search, caches, Redshift and an S3 lake. 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.

• Set the scope: Which sources? How many changes?
• Define the contract: Who consumes? How fresh?
• Test the boundaries: Do schemas change? Order? Largest table? Events for other teams?

Constraints

Explicit scope and guarantees

Resolve the scoping questions for a Change Data Capture Pipeline. Separate stated behavior from assumptions, and identify what is outside your design.

Supported operating targets

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.

Failure and boundary behavior

Explain how your guarantees hold in a difficult case relevant to this subject. Address: Largest table? Events for other teams?

What to cover

1. 01

   Scope and behavior contract

   Identify users, required behavior and exclusions. Answer: Which sources? How many changes?

2. 02

   State and interfaces

   Define the information owned by the system and the inputs, outputs and errors at its boundaries. Resolve: Who consumes? How fresh?

3. 03

   Capacity and operating targets

   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.

4. 04

   Architecture and central flow

   Draw or describe the responsibilities needed for a Change Data Capture Pipeline. Trace a representative request, event or job from its input to a visible result; identify durable state owners.

5. 05

   Failure and boundary walkthrough

   Walk through a difficult case step by step, including detection and recovery. Consider: Do schemas change? Order? Largest table? Events for other teams?

6. 06

   Tradeoffs and operations

   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.

Worked designs

Explore the architecture and decisions, then build on an example with Coach.

Official design

Design a Change Data Capture Pipeline

Every committed change in Aurora and DynamoDB, read from the log and delivered in order per row to search, caches, Redshift and an S3 lake: one-hour boards for junior, senior and staff, with the theory behind them.

Explore the design

Review rubric

AI feedback uses these criteria. Scores are practice feedback.