Github Code References

Github Code References is an integration that enables you to discover feature flag and configuration references within your codebase. By leveraging the Github API, it provides visibility into where these references are used without storing sensitive information.

This integration is crucial for streamlining feature management and maintaining organized code. It allows you to easily identify which parts of your codebase are impacted by specific feature flags or configurations. With Github Code References, you can:

  • Quickly locate feature flag and config usage across your repositories

  • Understand the scope and impact of each feature flag or config

  • Maintain a clean and organized codebase by identifying unused or stale references

By integrating Github Code References into your development workflow, you can ensure that your feature flags and configurations are properly managed. This helps prevent technical debt and makes it easier to reason about your codebase as it evolves over time.

Key benefits of Github Code References include:

  • Improved code organization and maintainability

  • Faster troubleshooting and debugging of feature flag issues

  • Easier collaboration among team members working on the same codebase

  • Reduced risk of deploying unintended changes or outdated feature flags

Ultimately, Github Code References provides a powerful tool for teams looking to optimize their feature management practices. By leveraging the Github API and providing clear visibility into flag and config usage, it helps ensure a more efficient and effective development process.

Configuration and setup process

To get started with the Github Code References integration, you'll need to create a Github developer token. This token should have read access to the organization or repositories where you use Statsig. You can find this option in Github under Settings > Developer Settings > Personal Access Token.

Once you have your token, log in to the Statsig Console and navigate to the Github Code References integration on the Integrations page. This can be found in Project Settings > Integrations Tab > Github Code References. The integration will provide additional instructions on how to enable it.

Input your Github token and organization name into the integration. It will then verify that it can access your repositories and notify you if there are any issues. After successful verification, you're ready to view your code references!

To access your code references, navigate to the Feature Gates or Dynamic Configs pages on the Statsig Console. Select a specific gate or config, then click on the Diagnostics tab. Here, you'll find a "View Code References" link that will display all the places in your code where that gate or config is referenced.

You can filter the code references by repository and file extension, making it easy to find exactly what you're looking for. This integration helps you quickly identify where your feature gates and dynamic configs are being used across your codebase.

The Github Code References integration is a powerful tool for understanding how your feature flags and dynamic configurations are being utilized. By setting it up, you gain valuable insights into your codebase and can make more informed decisions about your Statsig implementation.

Advanced features and best practices

The Github Code References Action automates scanning and PR creation for stale gates. This powerful feature streamlines the process of updating your codebase.

You can easily filter code references by repository and file extension on the Statsig Console. This allows you to quickly find the relevant code references for your feature gates and dynamic configs.

When moving from POC to production with Github Code References, follow best practices:

  • Ensure your Github token has appropriate permissions

  • Configure the action to run on a regular schedule

  • Review and merge PRs in a timely manner

Take advantage of additional resources to get the most out of Github Code References:

  • Statsig documentation provides in-depth guides and examples

  • The Github Marketplace listing includes usage instructions and configuration details

  • Join our community support channels to ask questions and share tips with other users

By leveraging the advanced features of Github Code References and following best practices, you can efficiently manage your feature gates and dynamic configs directly from your codebase. The automated scanning and PR creation saves valuable engineering time, while the filtering capabilities provide quick access to the references you need.

As you move from POC to production, lean on the wealth of resources available—from comprehensive documentation to helpful community support. With Github Code References, you have a powerful tool to streamline your feature management workflow and keep your codebase up-to-date.

Loved by customers at every stage of growth

See what our users have to say about building with Statsig
OpenAI
"At OpenAI, we want to iterate as fast as possible. Statsig enables us to grow, scale, and learn efficiently. Integrating experimentation with product analytics and feature flagging has been crucial for quickly understanding and addressing our users' top priorities."
Dave Cummings
Engineering Manager, ChatGPT
SoundCloud
"We evaluated Optimizely, LaunchDarkly, Split, and Eppo, but ultimately selected Statsig due to its comprehensive end-to-end integration. We wanted a complete solution rather than a partial one, including everything from the stats engine to data ingestion."
Don Browning
SVP, Data & Platform Engineering
Recroom
"Statsig has been a game changer for how we combine product development and A/B testing. It's made it a breeze to implement experiments with complex targeting logic and feel confident that we're getting back trusted results. It's the first commercially available A/B testing tool that feels like it was built by people who really get product experimentation."
Joel Witten
Head of Data
"We knew upon seeing Statsig's user interface that it was something a lot of teams could use."
Laura Spencer
Chief of Staff
"The beauty is that Statsig allows us to both run experiments, but also track the impact of feature releases."
Evelina Achilli
Product Growth Manager
"Statsig is my most recommended product for PMs."
Erez Naveh
VP of Product
"Statsig helps us identify where we can have the most impact and quickly iterate on those areas."
John Lahr
Growth Product Manager
"The ability to easily slice test results by different dimensions has enabled Product Managers to self-serve and uncover valuable insights."
Preethi Ramani
Chief Product Officer
"We decreased our average time to decision made for A/B tests by 7 days compared to our in-house platform."
Berengere Pohr
Team Lead - Experimentation
"Statsig is a powerful tool for experimentation that helped us go from 0 to 1."
Brooks Taylor
Data Science Lead
"We've processed over a billion events in the past year and gained amazing insights about our users using Statsig's analytics."
Ahmed Muneeb
Co-founder & CTO
SoundCloud
"Leveraging experimentation with Statsig helped us reach profitability for the first time in our 16-year history."
Zachary Zaranka
Director of Product
"Statsig enabled us to test our ideas rather than rely on guesswork. This unlocked new learnings and wins for the team."
David Sepulveda
Head of Data
Brex
"Brex's mission is to help businesses move fast. Statsig is now helping our engineers move fast. It has been a game changer to automate the manual lift typical to running experiments and has helped product teams ship the right features to their users quickly."
Karandeep Anand
President
Ancestry
"We only had so many analysts. Statsig provided the necessary tools to remove the bottleneck. I know that we are able to impact our key business metrics in a positive way with Statsig. We are definitely heading in the right direction with Statsig."
Partha Sarathi
Director of Engineering
"Statsig has enabled us to quickly understand the impact of the features we ship."
Shannon Priem
Lead PM
Ancestry
"I know that we are able to impact our key business metrics in a positive way with Statsig. We are definitely heading in the right direction with Statsig."
Partha Sarathi
Director of Engineering
"Working with the Statsig team feels like we're working with a team within our own company."
Jeff To
Engineering Manager
"[Statsig] enables shipping software 10x faster, each feature can be in production from day 0 and no big bang releases are needed."
Matteo Hertel
Founder
"We use Statsig's analytics to bring rigor to the decision-making process across every team at Wizehire."
Nick Carneiro
CTO
Notion
"We've successfully launched over 600 features behind Statsig feature flags, enabling us to ship at an impressive pace with confidence."
Wendy Jiao
Staff Software Engineer
"We chose Statsig because it offers a complete solution, from basic gradual rollouts to advanced experimentation techniques."
Carlos Augusto Zorrilla
Product Analytics Lead
"We have around 25 dashboards that have been built in Statsig, with about a third being built by non-technical stakeholders."
Alessio Maffeis
Engineering Manager
"Statsig beats any other tool in the market. Experimentation serves as the gateway to gaining a deeper understanding of our customers."
Toney Wen
Co-founder & CTO
"We finally had a tool we could rely on, and which enabled us to gather data intelligently."
Michael Koch
Engineering Manager
Notion
"At Notion, we're continuously learning what our users value and want every team to run experiments to learn more. It's also critical to maintain speed as a habit. Statsig's experimentation platform enables both this speed and learning for us."
Mengying Li
Data Science Manager
Whatnot
"Excited to bring Statsig to Whatnot! We finally found a product that moves just as fast as we do and have been super impressed with how closely our teams collaborate."
Rami Khalaf
Product Engineering Manager
"We realized that Statsig was investing in the right areas that will benefit us in the long-term."
Omar Guenena
Engineering Manager
"Having a dedicated Slack channel and support was really helpful for ramping up quickly."
Michael Sheldon
Head of Data
"Statsig takes away all the pre-work of doing experiments. It's really easy to setup, also it does all the analysis."
Elaine Tiburske
Data Scientist
"We thought we didn't have the resources for an A/B testing framework, but Statsig made it achievable for a small team."
Paul Frazee
CTO
Whatnot
"With Warehouse Native, we add things on the fly, so if you mess up something during set up, there aren't any consequences."
Jared Bauman
Engineering Manager - Core ML
"In my decades of experience working with vendors, Statsig is one of the best."
Laura Spencer
Technical Program Manager
"Statsig is a one-stop shop for product, engineering, and data teams to come together."
Duncan Wang
Manager - Data Analytics & Experimentation
Whatnot
"Engineers started to realize: I can measure the magnitude of change in user behavior that happened because of something I did!"
Todd Rudak
Director, Data Science & Product Analytics
"For every feature we launch, Statsig saves us about 3-5 days of extra work."
Rafael Blay
Data Scientist
"I appreciate how easy it is to set up experiments and have all our business metrics in one place."
Paulo Mann
Senior Product Manager
We use cookies to ensure you get the best experience on our website.
Privacy Policy