How to calculate search units in Azure AI Search ?

Question

How is the number of search units determined? According to this Microsoft documentation : https://learn.microsoft.com/en-us/training/modules/create-azure-cognitive-search-solution/2-manage-capacity , the number of search units is calculated by multiplying the number of replicas by the number of partitions (R x P = SU). However, Azure AI Search's S tier has 36 search units, despite having 12 replicas and 12 partitions. Why does the S tier have 36 search units instead of 144 search units ?

Answer 1

That's a great question!

I'm going to give you two answers:

1. The technical answer
2. And an analogy because I think it makes these types of things easier to remember

The technical answer

R x P = SU (TRUE)

BUT the S tier, you can configure up to 12 replicas and 12 partitions, but Azure caps the total active search units at 36, not 144.

So why would tier S allows up to 12 replicas and partitions if it caps your SU's at 36?

Because it allows combinations of replicas and partitions that total 36 SU or less while still allowing 12 partitions OR replicas as needed.

For example:

• 3 replicas x 12 partitions = 36 SU
• 6 replicas x 6 partitions = 36 SU

The goal is to max out performance and cost efficiency.

The Analogy

It's Hell's kitchen and there are 12 chefs (replicas) and 12 stations (partitions), but to make sure every chef can be properly evaluated only 36 active UNITS can be activated.

• You can have multiple chefs sharing a station
• Or one chef operating multiple stations

Does that clear it up? 😊 If so please accept the answer so others can benefit from it as well!

Answer 2

Hello Narongrit Pooket, the discrepancy arises because the S tier in Azure AI Search uses larger partitions compared to other tiers. While you're correct in calling out the R*P=SU calculation, the S tier's partitions are significantly larger, which means fewer search units are needed to achieve the same capacity and performance. In the S tier, each partition is designed to handle more data and queries, so the effective number of SU is adjusted to reflect this increased capacity.

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