Flagsmith
ConfigCat
LaunchDarkly
Unleash
Split.io
Flagship.io
Postman
Visual Studio Code
Algorithmia
neptune.ai
Managed MLflow
MCenter
5Analytics
Datatron
Iterative.ai
Numericcal
Flagsmith| Categories |
|
|---|---|
| Website | flagsmith.com |
| Pricing URL | Official Flagsmith Pricing |
| Details $ | freemium |
| Release Date | 2018-06-13 |
Algorithmia| Categories |
|
|---|---|
| Website | algorithmia.com |
| Pricing URL | - |
| Details $ | |
| Release Date | - |
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Based on our record, Flagsmith should be more popular than Algorithmia. It has been mentiond 13 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.
Considering all these points, the team at Flagsmith has developed a feature flag management platform Flagsmith and made it open source. The core functionality is open and you can check out the GitHub repository here. I have utilized and authored several blogs discussing their excellent offerings and strategies. - Source: dev.to / 4 days ago
Flagsmith - Release features with confidence; manage feature flags across web, mobile, and server side applications. Use our hosted API, deploy to your own private cloud, or run on-premise. - Source: dev.to / over 1 year ago
Flagsmith is written in Django and is open source as well: https://flagsmith.com. Source: almost 2 years ago
Before we dive in, one important call-out: We provide our feature management product to customers in three ways depending on how they want to have it managed: Fully Managed SaaS API, Fully Managed Private Cloud SaaS API and Self-Hosted. The infrastructure costs that we are sharing is for our customers that leverage our Fully Managed SaaS API offering (try it free: https://flagsmith.com/) which represents a portion... - Source: dev.to / almost 2 years ago
On March 15th, Sebastian Rindom, the CEO & Co-founder of Medusa, did an interview with Flagsmith where he talked about how Medusa started, why create a headless commerce solution, why make it open-source, and more. - Source: dev.to / about 2 years ago
To push a model into production, there are additional concerns which the tools in the versioning, deployment and release space aim to solve. This includes obtaining adequate infrastructure to run the model reliably and facilitating easy model release or rollback. Solutions in the MLOps space includes Kubeflow, Pachyderm and Algorithmia. - Source: dev.to / over 2 years ago
And for enterprises that want to do the same with ML you can use algorithmia.com. Source: over 2 years ago
Algorithmia advertises themselves as an MLops platform for data scientists, and they provide an easy way to host models on a scalable REST API. Source: over 2 years ago
Seems similar to https://algorithmia.com. Source: over 2 years ago
Algorithmia.com — Host algorithms for free. Includes free monthly allowance for running algorithms. Now with CLI support. - Source: dev.to / over 2 years ago
ConfigCat - ConfigCat is a developer-centric feature flag service with unlimited team size, awesome support, and a reasonable price tag.
neptune.ai - Neptune brings organization and collaboration to data science projects. All the experiement-related objects are backed-up and organized ready to be analyzed and shared with others. Works with all common technologies and integrates with other tools.
LaunchDarkly - LaunchDarkly is a powerful development tool which allows software developers to roll out updates and new features.
Managed MLflow - Managed MLflow is built on top of MLflow, an open source platform developed by Databricks to help manage the complete Machine Learning lifecycle with enterprise reliability, security, and scale.
Unleash - Open source Feature toggle/flag service. Helps developers decrease their time-to-market and to increase learning through experimentation.
MCenter - Machine Learning Operationalization
