Innovate
Your Software
Faster without Risk

FeatBit, a Fast, Scalable, and Open-source Feature Flags Management Service. For Cloud & Self-hosting.

Innovate Your Software Faster without Risk

FeatBit, a Fast, Scalable, and Open-source Feature Flags Management Service. For Cloud & Self-hosting.

FeatBit 2.1.0 Release

Last updated date:

Today we are excited to bring the FeatBit 2.1.0 release, this new version is so packed full of feature announcements.

New SDKs

We feel ashamed to not providing dotnet SDK while announcing FeatBit as a dotnet open source project. We have been hard at work for the past weeks, now we finally bring the SDKs for .Net and Golang.

Here is the full list of SDKs supported for the current day:

Lite version

Previously, it was a bit difficult to deploy FeatBit as it has too many dependencies. Many of them are not necessary for small businesses. With the current release, we've made a lite version by removing the dependencies to ClickHouse, Kafka and Zookeeper. We made the lite version as the default standard version and renamed the full version to FeatBit Professional.

Here is the key differences:

  • The standard version is ideal for small businesses, while the Professional version is ideal for medium and large businesses.
  • Both the Standard and Professional versions are scalable and fast, and have identical features.
  • The Standard version is a more lightweight option that only relies on Redis and MongoDB.
  • The Professional version is heavier and depends on Redis, MongoDB, Kafka, Zookeeper, and ClickHouse.
  • Redis is the message queue of choice for the Standard version, while Kafka is used in the Professional version.
  • MongoDB is the data analytics tool of choice for the Standard version, while ClickHouse is used in the Professional version.

Integrations

FeatBit is pleased to offer our first feature for integrations: Access Tokens. It allows programmatically interactions with FeatBit. For more details, please read the documentation.

Third party software can now integrate with FeatBit: adding a rule to an existing feature flag, adding new targeting users, archiving a feature flag etc. More Open APIs will be available in the coming releases.

Benchmark

With a minimum hardware setting: AWS EC2 t2.micro (1 vCPU + 1 G RAM), the Server is capable of providing a reliable service for until 1100 new connections per second, the maximum number of connections held for a given time reaches 22000 (this is not the limit). The web server resource utilization measured during the testing shows that the bottleneck of the hardware is the CPU, which is comprehensible as CPU is intensely used to evaluate the feature flags during the data synchronization stage. By using an instance with more vCPUs (or compute optimized instances), we can surely increase the capacity. We believe the reported performance is largely enough for small businesses with a negligible cost (free tier eligible). The capacity can be multiplied easily by scaling the service horizontally when the business grows.

To read the full report, please refer to FeatBit Benchmark

Try it online


The best way to introduce a product is through an online demo with easy access. Please check it out here.

You would be automatically logged in with the default admin user account: test@featbit.com. A default project and environment is already created for you.

The audit log and history tabs


The Audit log is a running tally of changes made to feature flags and segments in a given environment, it displays changes to feature flags and segments for your current environment only.

The feature is accessible in two ways:

  • Audit logs in the Sidenav
  • History tab of feature flag and segment

LLM-Powered Dead Feature Flag Removal

In this Release, we unveil an experimental feature utilizing ChatGPT-3.5-turbo to reduce dead feature flags in your codebase, helping to decrease technical debt from feature flags. This innovative solution automates the identification and removal of dead feature flags and associated code, minimizing human error and enhancing code quality.

Our Python CLI program interacts with ChatGPT-3.5-turbo, streamlining the process of cleaning up dead feature flags with simple commands. This LLM-powered approach boosts developer productivity and brings new accessibility to code management for non-engineers while reducing technical debt.

Explore this groundbreaking feature in FeatBit Release 2.1.0 and experience the future of programming and software engineering powered by ChatGPT and Large Language Models. Stay tuned for more updates and improvements as we continue to refine our platform. Check our blog article to get more information.

Enhancements of existing features

In addition to these new features, the FeatBit 2.1.0 release also includes several improvements to existing functionalities, which make the user experience more smooth and straight forward.

  • Added the filter parameters of feature flag list page to query string: make it easier to share the filtered flags with co-workers
  • Introduced the breadcrumb: navigation between features becomes much easier
  • Added a description field to feature flags: you would never forget the purpose of a feature flag
  • Create new user property when editing a targeting rule
  • Feature flag rollout with custom key: now you can roll out a flag with any user property
  • Allow users to send feedback to FeatBit maintainers

Big thanks to community

We feel really honor to get support from the community. Many thanks to the new contributors: