Full Stack allows product teams to run experiments anywhere in your technology stack. You can deploy code-behind feature flags, experiment with A/B tests, and rollout or rollback features immediately. All of this functionality is available with zero performance impact via easy-to-use SDKs.
Want to get started building and running experiments, and learning from your results? Check out our Full Stack documentation for in-depth coverage of every stage of the Full Stack experimentation lifecycle. Or start with a six-minute Full Stack demo.
Meet Optimizely Full Stack
Read our whitepaper on feature flagging to learn how to ship products faster, with less risk and more control.
Wondering about the basic differences between Web and Full Stack? Check out our article on Web to Full Stack migration to learn what to expect after you’ve made the switch.
Setup
- Review the core concepts to find out what Full Stack is all about.
- What is the datafile, and why is it so important?
- Find out how to create and manage Full Stack environments.
Define & debug experiments
- Design and run A/B tests and feature tests.
- What’s the difference between feature flags and feature variables?
- Define your audiences and attributes.
- Roll out and roll back features to subsets of your customers.
- Fine-tune your experiments by previewing your experiment variations.
- Learn how to use forced bucketing and whitelisting.
- Here’s how to do troubleshooting for Full Stack.
Get results
- Learn how to read and analyze the Results page.
- Choose the right metrics for your experiment.
- Find out how to integrate external analytics platforms, like Google Analytics or Amplitude.
Best practices
- Learn how to leverage CDNs.
- Find out how datafile versioning and management works in Full Stack.
- Here's how to work with microservices.
- Add staging environments to your projects for QA.
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