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Amazon Bedrock might be a bit more popular than Flagsmith. We know about 17 links to it since March 2021 and only 13 links to Flagsmith. 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.
Amazon Bedrock - fully managed service for using foundation models from Amazon and third parties. - Source: dev.to / 16 days ago
You can now customize foundation models (FMs) with your own data in Amazon Bedrock to build applications that are specific to your domain, organization, and use case. With custom models, you can create unique user experiences that reflect your company’s style, voice, and services. - Source: dev.to / about 1 month ago
The second service is what’s going to make our application come alive and give it the AI functionality we need and that service is AWS Bedrock which is their new generative AI service launched in 2023. AWS Bedrock offers multiple models that you can choose from depending on the task you’d like to carry out but for us, we’re going to be making use of Meta’s Llama V2 model, more specifically meta.llama2-70b-chat-v1. - Source: dev.to / about 2 months ago
Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon. Each model is accessible through a common API which implements a broad set of features to help build generative AI applications with security, privacy, and responsible AI in mind. - Source: dev.to / 2 months ago
For those keeping track, Amazon Bedrock became generally available in September of 2023. My team had access to a preview, so when the AWS Comprehend entity analysis did not lend itself well to my use case; and I didn't feel like training a model, I started to get familiar with Bedrock. The following post is a follow-on to the Community article above and fleshes out a few details that will help those newer to... - Source: dev.to / 3 months ago
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 / 2 months 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 / about 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
Claude AI - An AI assistant from Anthropic
LaunchDarkly - LaunchDarkly is a powerful development tool which allows software developers to roll out updates and new features.
Streamlit - Turn python scripts into beautiful ML tools
ConfigCat - ConfigCat is a developer-centric feature flag service with unlimited team size, awesome support, and a reasonable price tag.
Amazon Titan - Amazon Titan foundation models are pretrained on large datasets, making them powerful, general-purpose models.
Unleash - Open source Feature toggle/flag service. Helps developers decrease their time-to-market and to increase learning through experimentation.