ConfigCat
Unleash
LaunchDarkly
Flagsmith
Split.io
Flagship.io
Switchover Feature Flag Management
Bullet Train
neptune.ai
Comet.ml
Algorithmia
Weights & Biases
Managed MLflow
Spell
MCenter
Iterative.ai
ConfigCat is a developer-centric feature flag service that helps you turn features on and off, change their configuration, and roll them out gradually to your users. It supports targeting users by attributes, percentage-based rollouts, and segmentation. Available for all major programming languages and frameworks. Can be licensed as a SaaS or self-hosted. GDPR and ISO 27001 compliant.
Track and version your notebooks Log all your notebooks directly from Jupyter or Jupyter Lab. All you need is to install a Jupyter extension.
Manage your experimentation process Neptune tracks your work with virtually no interference to the way you like to do it. Decide what is relevant to your project and start tracking: - Metrics - Hyperparameters - Data versions - Model files - Images - Source code
Integrate with your workflow easily Neptune is a lightweight extension to your current workflow. Works with all common technologies in data science domain and integrates with other tools. It will take you 5 minutes to get started.
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Only negative is I didn't see it integrated with Azure, does with Google, AWS and one more. Looks real nice, and pretty powerful and plenty useful features for a data science group
Based on our record, ConfigCat should be more popular than neptune.ai. It has been mentiond 54 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
ConfigCat - ConfigCat is a developer-centric feature flag service with unlimited team size, excellent support, and a reasonable price tag. Free plan up to 10 flags, two environments, 1 product, and 5 Million requests per month. - Source: dev.to / 3 months ago
ConfigCat allows you to manage your feature flags from an easy-to-use dashboard, including the ability to set targeting rules for releasing features to a specific segment of users. These rules can be based on country, email, and custom identifiers such as age, eye color, etc. - Source: dev.to / 5 months ago
I recently started helping my friend @jordan-t-romero with a NextJS and NodeJS project she is working on. This weekend we incorporated ConfigCat so that we can add feature flags to control what content is displayed in the different environments (local, staging, production, etc.). - Source: dev.to / 11 months ago
But how can you be sure you’re making the right changes? It’s impossible to read your clients’ minds, but A/B testing might just be the next best thing. In this article, I’ll guide you through conducting an A/B test on an Android (Kotlin) application using ConfigCat’s feature flag management system and Amplitude. - Source: dev.to / 11 months ago
If you're planning on cutting back or saving bandwidth utilization and optimizing for better performance on the client side then a caching solution like Redis can help. And, as we've seen from the code examples, Redis integrates quite easily with ConfigCat. With a caching solution in place, you can supercharge the way you do standard feature releases, canary deployments, and A/B testing. Besides Node.js, ConfigCat... - Source: dev.to / 11 months ago
Neptune.ai - Log, store, display, organize, compare, and query all your MLOps metadata. Free for individuals: 1 member, 100 GB of metadata storage, 200h of monitoring/month. - Source: dev.to / 3 months ago
Hi I am Jakub. I run marketing at a dev tool startup https://neptune.ai/ and I share learnings on dev tool marketing on my blog https://www.developermarkepear.com/. Whenever I'd start a new marketing project I found myself going over a list of 20+ companies I knew could have done something well to “copy-paste” their approach as a baseline (think Tailscale, DigitalOCean, Vercel, Algolia, CircleCi, Supabase,... - Source: Hacker News / 7 months ago
There are a lot of tools out there for experiment tracking (eg neptune.ai), but I'm really not sure whether that sort of thing is over the top for what I need to do. Source: 8 months ago
Welcome to another episode of The Developer-led Podcast, where we dive into the strategies modern companies use to build and grow their developer tools. In this exciting episode, we're joined by Jakub Czakon, the CMO at Neptune.ai, a startup that assists developers in efficiently managing their machine-learning model data. Jakub is renowned not only for his role at Neptune.ai but also for his developer marketing... - Source: dev.to / 9 months ago
Tbh I have done a pretty good search on this topic, I couldn't find any. I thought maybe community could help me find one, if people like you (who works at neptune.ai) have the same opinion then it is what it is :). Anyway thank you for the suggestions that you gave, probably gonna use that. Source: 10 months ago
Unleash - Open source Feature toggle/flag service. Helps developers decrease their time-to-market and to increase learning through experimentation.
Comet.ml - Comet lets you track code, experiments, and results on ML projects. It’s fast, simple, and free for open source projects.
LaunchDarkly - LaunchDarkly is a powerful development tool which allows software developers to roll out updates and new features.
Algorithmia - Algorithmia makes applications smarter, by building a community around algorithm development, where state of the art algorithms are always live and accessible to anyone.
Flagsmith - Flagsmith lets you manage feature flags and remote config across web, mobile and server side applications. Deliver true Continuous Integration. Get builds out faster. Control who has access to new features. We're Open Source.
Weights & Biases - Developer tools for deep learning research