For most organizations, there’s a better way to load test!

The way we load testing is done today made sense for the time, but it’s time to rethink it.

A Brief History of Load Testing

Late 1990s

As commerce slowly trickled online, companies needed to know if a web application would scale before it was released.

A reasonable first proposal for scalability testing was to make many browsers hit your site. In 1996, this meant buying servers powerful enough to run many automated web browsers and paying monthly data center bills. Servers weren’t powerful, so setting up, monthly hosting, and running this could cost hundreds of thousands of dollars.

Labor was cheap, hardware was expensive.

Hardware was very expensive, time-consuming, and cumbersome to source and maintain. In comparison, salaries were cheaper. HTTP server traffic was simple and transactional, so it was easy to write scripts to mimic browser requests.

Trading labor costs for lower hardware costs was a good trade!

So HTTP-protocol level testing became the dominant load testing paradigm. Dynamic session variables and cookies were handled through correlation, a torture method technique to mimic browser requests.

What are the downsides of using labor hours to create highly efficient scripts to reduce machine costs?

Labor-intensive processes does not lend itself to CI. A human has to be in the loop to create and maintain the scripts.

  • Because HTTP level scripts go stale when an application is updated, creating or capturing scripts for code changes requires labor for every change. This slows releases and shifts testing later in the development cycle
  • Scripting and correlating takes labor hours, and drives up costs
  • A separate toolset and set of expertise are required
  • We maintain two separate implementations of page-walking logic. One in the load testing tool, and another in our system, acceptance, and integration tests With every new feature, page-logic must be implemented twice
  • Typically, this delays our releases, often by a full Sprint or more.

Things have changed…

  • The cloud means server time no longer requires “hosting costs”
  • Cloud time is rentable, by the second, for pennies
  • Rising demand and a skills shortage have raised labor costs
  • Testers often maintain page object libraries that hold the logic for how to walk a website
  • For REST APIs, we have client libraries or postman collections that hold the logic for how to talk to our API’s
  • Servers are cheap, people are expensive

Trading labor to save ~server~ cloud costs has become a bad tradeoff.

The future of load testing

What would an ideal load testing tool for today’s world look like? It would:

  • reuse our page walking logic so that we only had a single implementation. For API tests,
  • reuse our REST API client, or Postman libraries
  • work with our language of choice and not force a new tool or language

It wouldn’t require HTTP level playback, because this forces a brittle, low-level understanding and implementation of our app’s requests. We don’t want the extra headaches that come from correlation.

We don’t want the staleness of HTTP-protocol snapshots.

We want to maintain one “source of truth” for talking to our REST API’s, rather than two.

There are tools which can capture or import traffic from functional tests, but they recommend you then maintain the outputted HTTP-level script. That means you’re back to maintaining two implementations of your page walking logic. That’s the problem we want to avoid because you have to re-update, re-test, and re-work for every change.

We think we have a better approach with BrowserUp. What does that look like?

  • Instead of importing, run your code, so programmatic logic and smarter scripts are possible.
  • The code can live right in your repo if you want--in your language of choice.
  • For browser tests, reuse your page objects libraries for load testing. Or your end-to-end tests.
  • For API tests, reuse your postman libraries, or your own REST API client libraries.
  • Traffic is captured with full reporting and metrics
  • Execute in your own AWS account, so there's no data privacy issues.
  • Anything that makes requests, can drive load!

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