Toggly

Build Better Software Faster Using Feature Flags

81 followers

Build Better Software Faster Using Feature Flags

81 followers

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Testing and QA software

Innovate continuously the way Uber and Netflix do using feature flags in a developer and manager-friendly platform that lets you toggle features, A/B test, and view insights and metrics.

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Launch tags:Analytics•A/B Testing•Developer Tools

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Toggly

Maker

Hello Product Hunt Friends! I'm Alex, the founder of opsAI, and I'm thrilled to launch our tech baby Toggly – a software engineering tool designed to help developers build better software faster! Building software is tough, and it gets even tougher when the code base starts growing. Feature flags allow developers to change their code without having to worry about the release. With these flags, developers can update the code without impacting the broader functionality of the product. This way, features can be deployed in stages, making it easier to test and debug them before making them available on the live version of the product. Don’t settle for low productivity and time-consuming launch techniques, reach for the stars with Toggly: A feature flags UI that allows your development, product teams or QA to switch on certain features and see how they perform, prior to launch, without having to re-deploy. We designed Toggly to help you achieve its goals faster and safer like the big guys. Companies like Facebook and Google rely on feature flags to test features and applications before they are rolled out to everyone, and collect user feedback from a target audience. Now it’s your turn to join the elite and aim higher. Start working smarter and enhance your productivity with the right tool! Toggly Helps You: 👉 Separate releasing features from deployments. You can switch feature flags (feature toggles/switches) on and off at any time in production, instantly, without making any changes to your webpage 👥 Release a new feature to a specific group of people/audience - choose who your audience is based on user claims, part of a group, time of day, and more. 👀 Test new features, see how they behave, rope them back in at any time – you can turn features on for a specific time frame, collect metrics and feedback, turn them off, and fix bugs before turning them on again. ✨ Create Feature flags for every application – with Toggly, you can create as many feature flags as you want, and we support many of the most popular programming languages, and happy to add more. All our client libraries are open-source, and where possible we try to build on existing libraries to ease adoption. If there isn't one, we'll create it open source and with an option to be used standalone or with Toggly 👔 Know when a feature was turned on/off in each environment

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4yr ago

@alexandru11 Looks nice, will definitely take a closer look !

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4yr ago

Toggly

Maker

@andrei_chirila get in touch when you’re ready and we’ll help you get up and running

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4yr ago

Questo

@alexandru11 congrats!

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4yr ago

@alexandru11 what an awesome product, good luck! 🤞 ✨

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4yr ago

Careerflow LinkedIn Optimization Tool

A good portion of developers (especially ones that might be target customers of Toggly) use Firebase (or PostHog, etc.) which has feature flagging built in. While some alternatives like Supabase don't, I'm sure it's on their roadmap. Given the above points, I'm curious what your thoughts have been on Toggly's competitive landscape?

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4yr ago

Toggly

Maker

@puneet_kohli I image ease of use, and feature level analytics are going to be our competitive edge even competing with those platforms. We have something brewing that might make that clear. Feel free to join our mailing list, we promise to never spam, or just keep an eye on us.

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4yr ago

Careerflow LinkedIn Optimization Tool

@alexandru11 I see. From a personal perspective, as long as I can run A/B tests on feature flags and get the results, I am not sure what value feature-level analytics would add. Happy to hear your thoughts on this based on your early customers.

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4yr ago

Toggly

Maker

@puneet_kohli Thank you for the great questions! We collect metrics such as how many times a feature was checked and returned on vs off, how many individual requests that happened for, number of unique users, and how many times the feature was used (ex: an endpoint was hit which means the user actively gaining value from the feature vs just checked for being on) on a per-feature level. Then we record business metrics, which are whatever you want to send (ex: number of signups over time), and when you run an experiment, we increment the value of each business metric counter separately for the feature it's testing. This lets you run multiple experiments, and see statistically significant change in a metric based on interaction with that feature, using the data we collected for the metric during the same time, when the feature was off for other users. That said, we're actively building more, and we're using it ourselves, so expect to see the analytics part become quite interesting.

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4yr ago

Careerflow LinkedIn Optimization Tool

@alexandru11 Awesome, more power to you, and good luck! Following you to keep track of your journey :)

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4yr ago

Canua

Looks great! Congratulations! Our team use posthog to enable feature flags, not so happy about it in some aspects, what do you think toggly brings to the table that is superior? Thanks!

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4yr ago

Toggly

Maker

@luis_carlos_moyano_medina Thank you! Our goal going into this is making feature flags very fast to add to the codebase, and instantly see the feature when you turn it on or target it. We're not familiar with posthog, but we're just getting started and we hope to bring a lot of new ideas to the field

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4yr ago