# Surprising Scalability of Multitenancy

DevFeed: [Surprising Scalability of Multitenancy](<https://devfeed.tech/articles/surprising-scalability-of-multitenancy-12535.md>)

Original publisher: [Read original article](<http://brooker.co.za/blog/2023/03/23/economics.html>)

Author: Marc Brooker

Published: 2023-03-23T00:00:00Z

Content type: article

Language: en

Sources: [Marc Brooker's Blog](<https://devfeed.tech/sources/marc-brooker-s-blog.md>), [Marc Brooker's Blog](<https://devfeed.tech/sources/marc-brooker-s-blog-2.md>)

Topics: [Multitenancy](<https://devfeed.tech/topics/multitenancy.md>), [Scalability](<https://devfeed.tech/topics/scalability.md>), [Amazon S3](<https://devfeed.tech/topics/amazon-s3.md>), [Cloud](<https://devfeed.tech/topics/cloud.md>)

Tags: [architecture](<https://devfeed.tech/tags/architecture.md>), [cloud](<https://devfeed.tech/tags/cloud.md>), [cost](<https://devfeed.tech/tags/cost.md>), [economics](<https://devfeed.tech/tags/economics.md>), [multitenancy](<https://devfeed.tech/tags/multitenancy.md>), [performance](<https://devfeed.tech/tags/performance.md>), [s3](<https://devfeed.tech/tags/s3.md>), [scalability](<https://devfeed.tech/tags/scalability.md>), [storage](<https://devfeed.tech/tags/storage.md>), [systems](<https://devfeed.tech/tags/systems.md>)

## AI overview

The article explains how multi-tenancy improves the economics and scalability of cloud systems by reducing the overall peak-to-average traffic ratio. Using Amazon S3 as an example, it describes how distributing customer workloads across many storage devices can support high individual workload peaks without making the overall system disproportionately expensive.

## Source excerpt

Surprising Scalability of Multitenancy When most folks talk about the economics of cloud systems, their focus is on automatically scaling for long-term seasonality: changes on the order of days (fewer people buy things at night), weeks (fewer people visit the resort on weekdays), seasons, and holidays. Scaling for this kind of seasonality is useful and important, but there's another factor that can be even more important and is often overlooked: short-term peak-to-average. Roughly speaking, the cost of a system scales with its (short-term1) peak traffic, but for most applications the value the system generates scales with the (long-term) average traffic. The gap between "paying for peak" and "earning on average" is critical to understand how the economics of large-scale cloud systems differ from traditional single-tenant systems. Why is it important? It's important because multi-tenancy (i.e. running a lot of different workloads on the same system) very effectively reduces the peak-to-average ratio that the overall system sees. This is highly beneficial for two reasons. The first-order reason is that it improves the economics of the underlying system, by bringing costs (proportional to peak) closer to value (proportional to average). The second-order benefit, and the one that is most directly beneficial to cloud customers, is that it allows individual workloads to have higher peaks without breaking the economics of the system. Most people would call that scalability. Example 1: S3 Earlier this month, Andy Warfield from the S3 team did a really fun talk at OSDI'23 about his experiences working on S3. There's a lot of gold in his talk, but there's one point he made that I think is super important, and worth diving deeper into: heat management and multi-tenancy. Here's the start of the relevant bit on heat2 management: Andy makes a lot of interesting point here, but the key one has got to do with the difference between the per object heat distribution, the per aggregat