37. Reservation with a TTL, and a Unique Constraint

The brief

Reservation with a TTL, and a Unique Constraint. Scarce inventory — a seat, a room, the last unit — with far more buyers than units. Holding a database row for the minutes someone takes to pay does not scale, and checking availability before writing is a race that sells the same seat twice. 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: What is the scarce item, and may it ever be reserved twice? How long does a reservation remain valid?
• Define the contract: What happens when payment completes near the expiry boundary? Can the same caller retry or extend a reservation?
• Test the boundaries: How is an expired reservation released after a worker outage?

Constraints

Explicit scope and guarantees

Resolve the scoping questions for Reservation with a TTL, and a Unique Constraint. 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: Can the same caller retry or extend a reservation? How is an expired reservation released after a worker outage?

What to cover

1. 01

   Scope and behavior contract

   Identify users, required behavior and exclusions. Answer: What is the scarce item, and may it ever be reserved twice? How long does a reservation remain valid?

2. 02

   State and interfaces

   Define the information owned by the system and the inputs, outputs and errors at its boundaries. Resolve: What happens when payment completes near the expiry boundary? Can the same caller retry or extend a reservation?

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 Reservation with a TTL, and a Unique Constraint. 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: How is an expired reservation released after a worker outage?

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

Reservation with a TTL, and a Unique Constraint

A short-lived hold makes checkout feel fast; a unique constraint in the database is what actually makes double-selling impossible.

Explore the design

Review rubric

AI feedback uses these criteria. Scores are practice feedback.