This is a multi-series blog on GPUs, how they intersect with Kubernetes and containers. In this blog, we will discuss how CPUs and GPUs are architecturally similar and different. We will also review when it is ideal to use a CPU vs a GPU.
This is part of a blog series on AI/Machine Learning. In the previous blog, we discussed Jupyter Notebooks, how they are different and the challenges organizations run into at scale with it. In this blog, we will look at organizations can use JupyterHub to take to provide access to Jupyter notebooks as a centralized service for their data scientists.
Jupyter Notebook is open-source software created and maintained by the Jupyter community. A Jupyter notebook allows for the creation and sharing of documents with code and rich text elements. It works with over 40 programming languages including Python, R, and Ruby making it versatile and flexible for data scientists. In this introductory blog to Jupyter notebooks, we will look at "why it exists" and "what it looks like".
We frequently get asked by users that are currently on AWS whether they should be using Amazon ECS or EKS to deploy and operate their containerized applications. Since this is such a common question and the answers are somewhat nuanced, we wanted to share our thoughts and recommendations for the benefit of all users.
It is a well understood fact on Kubernetes that there is a significant amount of "wastage" of expensive cloud/infrastructure because of over provisioned applications. In this blog, we will look at how app developers and platform teams can save their organizations millions of dollars by right sizing their applications using a free, open-source tool called resize that we recently developed for our customers.
Important
Note that this is just one tool in a comprehensive Cost Control solution that Rafay provides our customers. Please contact us if you are interested in this.
A few days back, as part of our early March 2024 release, we opened up Rafay's Generative AI based Copilot to our customers. For the folks that are active readers of our product blogs, you will recognize that this is the result of a GenAI focused Hackathon we ran in late 2023. You can read more about our learnings from the Hackathon in 2023.
Just like Batman works way better with Robin as his copilot, we are seeing our customers benefiting immensely by using the Rafay Copilot that is integrated right in the console. In this blog, we will use a few examples to showcase the value of the Rafay copilot.
At KubeCon 2023, I had the opportunity to sit down and have a discussion with Amy Tobey from Equinix. We thought it would be a lot of fun to record a completely unscripted conversation for folks that may not be that familiar with Rafay. This full conversation (approx. 20 minutes) is available now on Equinix's YouTube channel.
The Rafay team was at AWS re:Invent 2023 in Las Vegas from 27-30th Nov, 2023. In this blog, we summarize some of our announcements at AWS re:Invent 2023, describe some of the cutting edge demos we showcased to the attendees at the event and also highlight some of our observations.
We constantly hear from our customers about wanting their developers to experiment with Generative AI. No organization wants to be left behind and they are all trying to find ways to empower their developers and application teams to be able to experiment with use cases powered especially by Generative AI.
According to recent Gartner research, >80% of enterprises will have used Generative AI APIs or Deployed Generative AI-Enabled Applications by 2026.
We have been listening to our customers and are happy to announce Rafay's Templates for AI & Generative AI. Platform teams can now provide their developers with a self service experience for Gen AI infrastructure enabling developers to experiment with new and innovative Generative AI use cases.
Our recent release update adds support for a number of new features and enhancements. This blog is focused on support for Upstream Kubernetes on nodes based on Red Hat Enterprise Linux (RHEL) v9.2 and Red Hat Enterprise Linux (RHEL) v9.1. Both new cluster provisioning and in-place upgrades of Kubernetes clusters are supported for lifecycle management.
