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gatling.io might be a bit more popular than Flagsmith. We know about 19 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.
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 / 16 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
Gatling: An open-source load and performance testing tool primarily designed for web applications, Gatling utilizes a simple domain-specific language (DSL) for creating and maintaining test scripts. It supports HTTP/2 and allows recording and generation of scenarios directly from a browser. The tool also provides detailed performance reports that are easy to analyze. - Source: dev.to / about 2 months ago
Performance and load testing are essential parts of GraphQL API testing. It ensures APIs can handle expected traffic volumes and respond within acceptable timeframes. You can use tools like Apache JMeter or Gatling to generate realistic loads and evaluate the API's performance under different scenarios. Techniques like batched queries and caching can help mitigate this issue. - Source: dev.to / 10 months ago
New to the .NET community and trying to learn! I have used tools such as Apache JMeter (Java), gatling.io (Java) and Locust (Python) that are decent full featured web perf frameworks. Typically these integrate well with your code, and can be run as part of your unit/integration tests and produce offline reports. Source: about 1 year ago
Gatling , this is what we tested concurrency with. Setting up might take a while depending on your exp. But the tool is solid. Source: about 1 year ago
I used SpringBoot 3.0.2, GraalVM 22 (JVM mode), a MacOS 2,6 GHz 6-Core Intel Core i7, running 1000 users for 5 minutes. The idea was to test how memory consumption and CPU usage evolve. Below, I compared the footprint of these three solutions. I collected the total count of requests, throughput, memory consumption, and CPU usage using VisualVM and Gatling. - Source: dev.to / over 1 year ago
ConfigCat - ConfigCat is a developer-centric feature flag service with unlimited team size, awesome support, and a reasonable price tag.
locust - An open source load testing tool written in Python.
LaunchDarkly - LaunchDarkly is a powerful development tool which allows software developers to roll out updates and new features.
Apache JMeter - Apache JMeter™.
Unleash - Open source Feature toggle/flag service. Helps developers decrease their time-to-market and to increase learning through experimentation.
Loader.io - Loader.io is a simple cloud-based load testing service