A merchant is planning a camping for each of their 500 partners. Each will receive a unique set of prices for a catalog of 10,000 products. How will…

In an Adobe Commerce architecture, each website can have a different base currency and price scope. With 500 websites, each having unique prices for 10,000 products, the full-page cache (FPC) must store a distinct version of each product and category page for every single website. This results in an exponential growth of cache variations (500 websites × 10,000 products = 5,000,000+ cached pages). This massive volume of data will rapidly consume available cache storage, whether it is disk space (for file-based cache) or memory (for Redis), leading to resource exhaustion, a poor cache-hit ratio, and severe performance degradation.

A. The re-index process will become very slow

While true that the price index will be massive and slow to rebuild, this is primarily a background operational issue. The cache failure is a more critical, system-wide problem affecting every user request.

C. The sort by price feature will become very stow

This is a direct consequence of the large price index. However, it is a symptom of the data scale, whereas cache exhaustion is a more fundamental system resource failure.

D. Static content deployment time will increase considerably

Static content deployment is primarily affected by the number of themes and locales, not by data scope like pricing. This area would see a much smaller performance impact.

1. Adobe Commerce Developer Documentation

Performance best practices

Catalog: "The number of websites

stores

and store views affects the performance of many operations... The size of index tables grows in proportion to the number of websites

stores

and store views

which makes indexes take longer to update." This supports that A and C are valid concerns

but the documentation also highlights the broader impact.

2. Adobe Commerce Developer Documentation

Scalability

General principles: The documentation frequently advises on minimizing complexity. A large number of websites is a primary axis of complexity. It states

"Reindexing becomes slower

and full page cache has more variations

which means a lower cache hit ratio." This directly points to the problem of cache variation explosion

which leads to the outcome described in option B.

3. Adobe Commerce Developer Documentation

Configure caching

Full-page caching: This section explains that the cache stores a complete page output. For pages with price differences (a key part of the page content)

a separate version must be cached for each context (in this case

each website)

validating the premise of cache variation explosion.