neptune.ai
Algorithmia
Comet.ml
Weights & Biases
Managed MLflow
Spell
MCenter
5Analytics
Kubernetes
Rancher
Docker
Helm.sh
Google Kubernetes Engine
Docker Swarm
Docker Compose
Portainer
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.
neptune.ai KubernetesOnly 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, Kubernetes seems to be a lot more popular than neptune.ai. While we know about 299 links to Kubernetes, we've tracked only 23 mentions of neptune.ai. 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.
Experiment tracking tools like MLflow, Weights and Biases, and Neptune.ai provide a pipeline that automatically tracks meta-data and artifacts generated from each experiment you run. Although they have varying features and functionalities, experiment tracking tools provide a systematic structure that handles the iterative model development approach. - Source: dev.to / about 1 month 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 / 5 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 / 9 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: 10 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 / 11 months ago
Kubernetes has become the de facto standard for container orchestration, providing a powerful platform for deploying, scaling, and managing containerized applications. However, optimizing Kubernetes deployments can be challenging due to the complexity of the system and the wide array of configuration options available. In this article, we'll explore essential tips and tricks to help you optimize your Kubernetes... - Source: dev.to / about 1 month ago
Therefore, adopting Kubernetes is an obvious choice for us. Kubernetes is an open-source system designed specifically for automating deployment, scaling, and management of containerized applications. This guide will walk you through the basic setup of deploying your own Kubernetes cluster using k0s and Tailscale. - Source: dev.to / 5 days ago
This approach offers advantages, such as more flexible development and deployment (you can develop and deploy each microservice separately). It also offers scaling benefits, since services can be orchestrated to run in different geographies, and instances of running services can be added and removed dynamically based on usage (e.g. Using orchestration tools like Docker Swarm and Kubernetes). - Source: dev.to / 28 days ago
The open source projects Fastly uses and the foundations we partner with are vital to Fastly’s mission and success. Here's an unscientific list of projects and organizations supported by the Linux Foundation that we use and love include: The Linux Kernel, Kubernetes, containerd, eBPF, Falco, OpenAPI Initiative, ESLint, Express, Fastify, Lodash, Mocha, Node.js, Prometheus, Jenkins, OpenTelemetry, Envoy, etcd, Helm,... - Source: dev.to / 17 days ago
Kubernetes, also known as "K8s," is a container orchestration tool developed by Google. It is used to automate the deployment, scaling, and management of containerized applications. Docker and Kubernetes can be combined for better container management. - Source: dev.to / 16 days ago
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.
Rancher - Open Source Platform for Running a Private Container Service
Comet.ml - Comet lets you track code, experiments, and results on ML projects. It’s fast, simple, and free for open source projects.
Docker - Docker is an open platform that enables developers and system administrators to create distributed applications.
Weights & Biases - Developer tools for deep learning research
Helm.sh - The Kubernetes Package Manager
