BETA

Kubeflow as a Service

Our fully managed development environment allows you to leverage the scale of Civo compute for machine learning and AI projects.

  • Incredibly low entry point, pricing starting from $250 a month
  • Powerful CPU fully managed, auto-scaling Machine Learning Development Environment
  • Integrated into all your existing Civo services
  • No Kubernetes or Machine Learning expertise necessary!

Build, launch, and scale your projects in just a few clicks

Civo KFaaS significantly lowers the effort required to run high performance machine learning workloads, we do all the heavy lifting so you can focus on your ML project.

Integration

Easily integrated with other tools and platforms, such as Jupyter notebooks, RStudio, and Visual Studio Code, providing a seamless workflow.

High-performance computing

Access to high-performance computing resources, including CPU & GPU (coming soon) accelerated instances, for efficient data processing and model training.

Scalability

With a low barrier of entry starting at just $250, our solution adapts to your demands, accommodating both compact and expansive projects seamlessly.

Easy deployment

Deploy and launch your machine learning models effortlessly using our intuitive user interface, all in under 10 minutes!

Cost-effective

By leveraging the power of the cloud, Civo KFaaS provides a cost-effective solution for machine learning without the need for expensive hardware.

Cloud-based

Access your Civo KFaaS project from any location with internet connectivity, eliminating the need for hardware maintenance.

KFaaS Pricing

Our fully managed development environment allows you to leverage the scale of Civo compute for machine learning and AI projects.

KubeFlow as a Service pricing

KubeFlow as a Service pricing
Size RAM CPU Storage Data Transfer Price
Small
3 x Small nodes
48 GB 12 cores 180GB NVMe FREE
$250per month
Medium
3 x Medium nodes
96 GB 24 cores 240GB NVMe FREE
$500per month
Large
3 x Large nodes
192 GB 48 cores 360GB NVMe FREE
$1,000per month
Extra Large
3 x Extra Large nodes
384 GB 96 cores 540GB NVMe FREE
$2,000per month

Choose your favorite cloud IDE, we'll do the rest

Let us handle the setup and maintenance, so you can focus on what matters most: your analysis.

JupyterLab

For easy collaboration and sharing of notebooks.

Visual Studio Code

For syntax highlighting, debugging, and code refactoring.

RStudio

For data analysis and statistical computing.

BYOD

Bring your own development environment.


Frequently Asked Questions


What is the current product life cycle stage for Civo KFaaS?

The CPU is in a publicly available beta at this stage, to have access, create a Civo account, or access your Civo dashboard. GPU compute is currently in a closed invite-only beta.


How does Civo KFaaS differ from other machine learning services?

Civo KFaaS sets itself apart with one-click access to CPU and GPU (coming soon) backed machine learning and AI tooling, native support for Jupyter and Visual Studio Code, and acceleration by Civo infrastructure for optimal performance. In addition, its Kubeflow foundation, easy integration with tools like Jupyter, RStudio, Visual Studio Code, TensorFlow, and PyTorch, and focus on providing a cost-effective and user-friendly solution make it an ideal choice for both data scientists and engineers.


How easy is it to use Civo KFaaS for my projects?

Civo KFaaS is designed to be easy to use, with a user-friendly interface, one-click access to powerful CPU and GPU (coming soon) backed machine learning and AI tooling, and seamless integration with popular tools and frameworks.


What types of machine learning algorithms does Civo KFaaS support?

Civo KFaaS supports a wide array of machine learning algorithms, encompassing supervised and unsupervised learning, deep learning, reinforcement learning, and Large Language Models (LLMs). This versatility is achieved through our integration with various ML frameworks.


Can I use Civo KFaaS to scale my existing machine learning projects?

Yes, Civo KFaaS allows you to scale your existing machine learning projects and take advantage of CPU and the powerful GPU backed infrastructure provided by Civo (GPU coming soon).


How can I access my notebooks on Civo KFaaS?

Civo KFaaS offers native support for JupyterLab, Visual Studio Code, and RStudio, ensuring effortless access and editing of your notebooks. Additionally, you have the flexibility to bring your own containers, tailoring the environment to your specific needs.


Does Civo KFaaS come with any pre-trained models?

Civo KFaaS does not come with pre-trained models, but it provides access to a wide range of machine learning and AI tooling, allowing users to train their own models using their preferred ML frameworks.


GPU vs. CPU in machine learning

When it comes to machine learning, the choice between GPUs and CPUs often comes down to the specific needs of a task. GPUs, known for their parallel processing capabilities and a large number of cores, are highly effective for complex computations and handling vast amounts of data, making them ideal for training deep learning models. On the other hand, CPUs, which have fewer but more powerful cores, offer better performance for simpler, sequential tasks and tend to be more cost-efficient for inference. In the end, the decision to use GPUs or CPUs for machine learning will depend on the task at hand, the scale of the workload, and the desired balance between performance and cost.