# vegeta

Published articles for vegeta.

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## Load Testing for Expected Increases in Traffic with Vegeta

DevFeed: [Load Testing for Expected Increases in Traffic with Vegeta](<https://devfeed.tech/articles/load-testing-for-expected-increases-in-traffic-with-vegeta-26521.md>)

Original publisher: [Read original article](<http://engineering.curalate.com/2017/12/21/expected-traffic-load-testing.html>)

Author: Reid Knight was a Software Engineer

Published: 2017-12-21T13:00:00Z

Content type: tutorial

Language: en

Sources: [Curalate](<https://devfeed.tech/sources/curalate.md>)

Topics: [Testing](<https://devfeed.tech/topics/testing.md>), [API](<https://devfeed.tech/topics/api.md>), [Caching](<https://devfeed.tech/topics/caching.md>), [rate-limiting](<https://devfeed.tech/topics/rate-limiting.md>)

Tags: [api](<https://devfeed.tech/tags/api.md>), [caching](<https://devfeed.tech/tags/caching.md>), [load-testing](<https://devfeed.tech/tags/load-testing.md>), [rate-limiting](<https://devfeed.tech/tags/rate-limiting.md>), [testing](<https://devfeed.tech/tags/testing.md>), [vegeta](<https://devfeed.tech/tags/vegeta.md>)

### AI overview

This article explains how Curalate plans and performs load testing for predictable increases in service and API traffic, including holiday peaks. It discusses dependencies, caching, staging versus production environments, rate limiting, and expected load across services.

### Source excerpt

At Curalate, our service and API traffic is fairly tightly coupled to e-commerce traffic, so any increase is reasonably predictable. We expect an increase in request rate towards the beginning of November each year, with traffic peaking at 10x our steady rate on Black Friday and Cyber Monday. Why Load Test? Curalate works directly with retail brands to drive traffic to their sites. The holiday shopping period is the most important time of the year for most of them, and we need to ensure that our experiences continue to operate at a high standard throughout. More generally, though, load testing is critical for services and APIs, especially in cases where load is expected to increase. It uncovers potential points of failure, during business hours, and hopefully prevents people from needing to wake up at 2 a.m. on a weekend. Creating a Test Plan In cases of expected load increases, it's important to understand as much as possible before diving into it. There are a few questions to ask: Is there any data available so I can understand the expected load? Is it a yearly increase - are previous years a good indication? If it's a brand new launch, what are the expectations? What are the hard and soft dependencies of the service or API that I'm testing? What sort of caching is in place? Does a 10x increase on my service cause a 10x increase on everything downstream, as well? Should we test against the active production environment, or is it feasible to spin up a staging environment with the same scaling behavior? Depending on the breadth of dependencies, it may not be possible to spin up a new duplicated environment. If I test against production, how can I ensure I don't negatively affect live traffic? Am I expecting an increase in load across services? If there are any core dependencies, what does the combined load look like at peak? How much of a buffer do I provide against the expected peak? Does my service have any rate limiting that I need to bypass or keep in mind? How