zae-limiter is a rate limiting library using the token bucket algorithm. Prior to version 0.10.1, all rate limit buckets for a single entity share the same DynamoDB partition key (`namespace/ENTITY#{id}`). A high-traffic entity can exceed DynamoDB's per-partition throughput limits (~1,000 WCU/sec), causing throttling that degrades service for that entity — and potentially co-located entities in the same partition. Version 0.10.1 fixes the issue.

Affected: PyPI: zae-limiter

## Summary

All rate limit buckets for a single entity share the same DynamoDB partition key (`namespace/ENTITY#{id}`). A high-traffic entity can exceed DynamoDB's per-partition throughput limits (~1,000 WCU/sec), causing throttling that degrades service for that entity — and potentially co-located entities in the same partition.

## Details

Each `acquire()` call performs a `TransactWriteItems` (or `UpdateItem` in speculative mode) against items sharing the same partition key. For cascade entities, this doubles to 2-4 writes per request (child + parent). At sustained rates above ~500 req/sec for a single entity, DynamoDB's adaptive capacity may not redistribute fast enough, causing `ProvisionedThroughputExceededException`.

The library has no built-in mitigation: - No partition key sharding/salting - No write coalescing or batching - No client-side admission control before hitting DynamoDB - `RateLimiterUnavailable` is raised but the caller has already been delayed

## Impact

- **Availability**: High-traffic entities experience elevated latency and rejected requests beyond what their rate limits specify - **Fairness**: Other entities sharing the same DynamoDB partition may experience collateral throttling - **Multi-tenant risk**: In a shared LLM proxy scenario, one tenant's burst traffic could degrade service for others

## Reproduction

1. Create an entity with high rate limits (e.g., 100,000 rpm) 2. Send sustained traffic at 1,000+ req/sec to a single entity 3. Observe D…

Affected: PyPI: zae-limiter

## Summary

All rate limit buckets for a single entity share the same DynamoDB partition key (`namespace/ENTITY#{id}`). A high-traffic entity can exceed DynamoDB's per-partition throughput limits (~1,000 WCU/sec), causing throttling that degrades service for that entity — and potentially co-located entities in the same partition.

## Details

Each `acquire()` call performs a `TransactWriteItems` (or `UpdateItem` in speculative mode) against items sharing the same partition key. For cascade entities, this doubles to 2-4 writes per request (child + parent). At sustained rates above ~500 req/sec for a single entity, DynamoDB's adaptive capacity may not redistribute fast enough, causing `ProvisionedThroughputExceededException`.

The library has no built-in mitigation: - No partition key sharding/salting - No write coalescing or batching - No client-side admission control before hitting DynamoDB - `RateLimiterUnavailable` is raised but the caller has already been delayed

## Impact

- **Availability**: High-traffic entities experience elevated latency and rejected requests beyond what their rate limits specify - **Fairness**: Other entities sharing the same DynamoDB partition may experience collateral throttling - **Multi-tenant risk**: In a shared LLM proxy scenario, one tenant's burst traffic could degrade service for others

## Reproduction

1. Create an entity with high rate limits (e.g., 100,000 rpm) 2. Send sustained traffic at 1,000+ req/sec to a single entity 3. Observe D…