Integration with Launch Darkly
Has anyone attempted an integration between Launch Darkly and Pega?
The goal would be to use LaunchDarkly's feature management platform as a way to enable functionality across a business area without having to specifically release anything.
I've considered the possibility of an implementation that links with toggles in Pega or perhaps sourcing feature flagging data to a data page and using webhooks to update them.
@rwtaylor Yes, integrating LaunchDarkly with Pega is possible and can enhance your feature management without needing new releases. You can start by using LaunchDarkly’s APIs to fetch feature flags and store them in Pega’s data pages. This allows Pega applications to access and utilize these flags to control different functionalities. To keep the flags updated, set up webhooks in LaunchDarkly that notify Pega whenever there’s a change in a feature flag, ensuring your data remains current. Alternatively, you might link LaunchDarkly toggles directly with Pega’s decision rules, enabling dynamic feature control based on the flags. By sourcing feature flag data into Pega, you can manage which features are active across various business areas seamlessly. This setup allows you to enable or disable features in real-time, perform A/B testing, and roll out changes gradually without disrupting the entire system. Make sure to handle authentication and secure the communication between LaunchDarkly and Pega to protect your data. Additionally, refer to both LaunchDarkly’s and Pega’s integration documentation for detailed steps and best practices. Collaborating with both platforms’ support teams can also provide tailored solutions for your specific needs. Overall, this integration can lead to more flexible and controlled feature deployments within your business processes.
@SairohithHave you integrated with Launch Darkly previously? While it is possible API, Launch Darkly specifically recommends against that in their documentation. Although it does sounds as if it may have more to do with ensuring user get proper caching and updates models via the SDKs vs repeatedly calling the API.
@rwtaylor I haven't integrated with Launch Darkly myself, but I went through their documentation, and it clearly recommends using the SDK over the API. The docs explain that while the API is available, the SDK is specifically built to handle caching and update models, ensuring your application always gets the most current feature flag settings without constant API calls. This design minimizes network overhead and helps avoid performance issues that can occur with repeated API requests
@SairohithI appreciate the feedback but AI summaries of Launch Darkly documentation that I've already read doesn't really help to answer my question.