This topic defines key terms used at Optimizely Full Stack.
Optimizely's SDKs provide a general interface for running experiments throughout your applications and services. Because you will likely have many teams running experiments in different parts of your stack with varying requirements, we have designed Full Stack for maximum customization. You use projects, environments, datafiles, and clients to adapt a Full Stack SDK to your developmental workflow.
A Full Stack project lets you isolate each of your teams or applications in their own separate shared workspace. Projects are where a team builds experiments, manages feature flags, defines target audiences, and more. Each project has its own set of permissions.
Projects have a many-to-many relationship with your application stack. You can have many different projects to manage different parts of a single application or use a single project to manage omnichannel experiments across your website backend and mobile app.
Because your account already includes a project, creating another project is an optional step.
Use environments in Optimizely to develop and validate your experiment internally before displaying changes to your production website, whether you use a formal deployment environment or not. Each project can have one or more environments.
For example, it is common to set up both staging and production environments in Optimizely. You will often develop and QA your experiments in staging, and deploy to production when you are ready. You can set up different permissions for who can make changes in each of these environments.
Each environment in a project has a corresponding datafile. This file captures the configuration data of all your experiments, such as feature flags and event tracking, in a JSON format. When you make changes in a project, each environment's datafile is automatically updated with the new configuration. By synchronizing a local copy of this datafile, the SDK can run experiments without making blocking network requests to an outside API, ensuring microsecond-latency.
Datafile changes are also uploaded to the Optimizely content delivery network (CDN), and this process generally takes a few minutes.
When Optimizely actually fetches the updated datafile from the CDN depends on the specific SDK and version, the synchronization method and the local cached copy version.
Optimizely generates a different version of the datafile for each environment you configure on your account. This allows you to toggle a feature flag in one environment while keeping it paused in another. You do not need to duplicate your code, your Optimizely project, or experiments within your project.
A client is an instance of the Optimizely SDK running a specific datafile and other configuration settings. To use the SDK, get the appropriate datafile and then instantiate a client with it. This client exposes all the methods you need to activate experiments, track events, and perform other tasks.
The Android and Swift SDKs (also called the mobile SDKs) offer the additional abstraction of a client manager. The manager handles synchronizing datafiles and generating the associated clients for you, along with other optimizations around event dispatching and persisting user state on the device. Using the manager is optional, and you can instantiate a client directly if you prefer complete control.
An impression is a unit of measurement of usage. In Full Stack, Optimizely counts an impression each time an experiment is activated and a decision event is sent. See Implement impressions for more information about:
- When we send impressions and when we do not.
- How we use impressions to calculate data for the Results page and keep track of your account's impression quota.
- Which method to use to generate or not generate impressions for certain use cases.
Our support documentation article What is an impression in Optimizely provides additional information about impressions, including the differences between how impressions are counted in Full Stack versus Web.
Updated about 1 year ago