DLDropLock
Aurora DSQLTransactionally consistent under distributed load

Global scarcity audit

Aurora Launch Edition Hoodie

00000000-0000-4000-a000-000000000001

Global Inventory Invariant

PASSED

Key Insight

Million-scale drops need more than one inventory counter. DropLock shards the global cap across Aurora DSQL rows so concurrent reservations spread instead of colliding on a single hot row — and distributed transactions keep the cap strongly consistent worldwide.

System Explanation

Problem

Global scarcity events — tickets, game items, sneakers, creator drops — fail when concurrent demand oversells a shared cap.

Solution

DropLock uses Aurora DSQL with sharded reservations and distributed transactions so million-scale bursts cannot exceed configured inventory.

Guarantee

Successful reservations ≤ configured global cap — provable from the audit trail after every burst.

How this scales

Inventory shards

Each drop splits its global cap across shard rows so concurrent writes spread instead of hammering one hot counter.

Aurora DSQL transactions

Distributed, conditional updates enforce the cap inside the database. Successful reservations commit only when capacity remains.

Stateless Vercel API routes

Frontend and API handlers hold no inventory state. They scale horizontally while DSQL remains the single source of truth.

Audit trail after every burst

Purchase attempts, conflict retries resolved, and oversold units are recorded so the invariant can be verified after flash-sale load.

Inventory ledger

Configured cap

100

Global inventory limit for this scarcity event

Reservations confirmed

26

Committed orders in Aurora DSQL

Failed Attempts

0

Total rejected requests

Oversold Units

0

Must remain 0

Contention Under Load

Conflict Retries

9

Handled by the conflict retry mechanism during bursts

Reservation Conflicts Resolved

26

Conflicts reconciled without overselling

Rejected At Capacity

0

Requests denied when inventory shards are full

Inventory Shard Grid

Inventory is split across 10 inventory shards so concurrent buyers never fight over a single hot row. Each shard holds its own slice of the global cap.

26 / 100

global reserved

Shard 01Available

3 / 10

Capacity 1030%
Shard 02Available

5 / 10

Capacity 1050%
Shard 03Available

2 / 10

Capacity 1020%
Shard 04Available

2 / 10

Capacity 1020%
Shard 05Available

3 / 10

Capacity 1030%
Shard 06Available

3 / 10

Capacity 1030%
Shard 07Available

3 / 10

Capacity 1030%
Shard 08Available

2 / 10

Capacity 1020%
Shard 09Available

2 / 10

Capacity 1020%
Shard 10Available

1 / 10

Capacity 1010%

Naive vs DropLock

Traditional inventory counters break under global flash-sale pressure. DropLock is built for high-concurrency scarcity events — Aurora DSQL distributed transactions, inventory shards, and a conflict retry mechanism enforce the configured cap.

Invariant Proof

PASSED

Post-commit audit confirming purchases never exceed the global inventory cap.

The rule

Successful purchases must stay at or below configured inventory

Right now

26 purchases out of 100 units allowed

Result

PASSED — no overselling

Oversold check

0 unit(s) oversold

No overselling detected — distributed inventory invariant holds

Architecture

Stateless Vercel API routes accept reservation requests at scale. Aurora DSQL shards the global cap and commits orders with distributed transactional integrity — no single hot inventory row.

  1. 1

    Buyer Request

    Millions of concurrent buyers worldwide

  2. 2

    Regional API Route

    Stateless Vercel handler, no inventory state

  3. 3

    Aurora DSQL Transaction

    Distributed, strongly consistent commit

  4. 4

    Inventory Shard

    Global cap split across shard rows

  5. 5

    Order Commit

    Reservation persisted transactionally

  6. 6

    Invariant Audit

    Sold ≤ cap proven after every burst

Demo only

Clear orders and purchase attempts, then restore full inventory so you can rerun the flash-sale simulation.