Kubernetes + GPUs: The Backbone for AI-Enabling Workloads
Welcome to this edition of the Cloud-Native Innovators newsletter, Feb Triumph. Cloud-Native Innovators monthly Linkedin is back ! Being a true innovator means more than gaining knowledge and keeping up with the technology trends. It's about harnessing that knowledge, applying it in our daily work, and ultimately driving meaningful results to our organizations. What we can consistently do is to empowering ourselves to make a positive impact !
As AI continues to generate excitement in 2024, Kubernetes stands as the backbone for some major AI players such as OpenAI. That's why, in this issue, let's explore the interesting trilogy surrounding Kubernetes and GPUs for AI-enabling workloads on large-scale GPU-accelerated computing together.
Kubernetes in 2024
In 2024, Kubernetes continues to witness widespread adoption, serving as the backbone for organizations seeking to streamline the deployment, management, and scaling of containerized applications. This surge in adoption prompts DevOps, platform engineering, and development teams to prioritize the reliability, security, and cost efficiency of their workloads according to the Kubernetes Benchmark Report 2024 based on their analysis data from over 330,000 workloads.
Kubernetes isn't just a platform but an entire ecosystem. Since CNCF started in 2015, it's been home to lots of important projects, like Kubernetes, Prometheus, Envoy, and others. Right now, CNCF hosts 173 projects, with over 220,000 people from 190 countries helping out. This shows how big and diverse the Kubernetes community is, and how it's not just a tool, but a big part of a growing network of technology.
Kubernetes isn’t just a platform for running application workloads. It’s now an integral part of handling auxiliary tasks. This includes managing security controls, service meshes, messaging systems, observability, and CI/CD tools. The versatility of Kubernetes extends beyond the primary function of application hosting.
If you're eager to learn Kubernetes in 2024, this guide is designed to assist you in adopting the right strategies and easily getting it started within minutes. Remember, Rome wasn't built in a day!
Kubernetes + GPUs = ?
Currently, 48% of organizations use Kubernetes for AI/ML workloads, and the demand for such workloads also drives usage patterns on Kubernetes more and more significantly.
You see unlike CPUs, GPUs require specialized handling due to their parallel processing capabilities for things like to train and infer complex deep-learning models, scientific simulations, and graphics rendering.
And Kubernetes is designed to scale the infrastructure by pooling the compute resources from all the nodes of the cluster.
So, The synergy between Kubernetes and GPUs offers unparalleled scalability for handling AI workloads and the combination of Kubernetes and GPUs delivers unmatched scale for AI workloads.
NVIDIA Leads the Charge in Accelerated Computing
On May 30, 2023, NVIDIA became a member of the?trillion-dollar?club with an $1.02 trillion market value, and in less than a year, NVIDIA's net worth doubled and reached an incredible 2 trillion dollars in Feb 2024.
Did you know there’s a secret weapon behind NVIDIA’s success in powering the AI boom? NVIDIA’s AI chips play a pivotal role in training Large Language Models (LLMs) for advanced generative AI applications, empowering sophisticated chatbots such as ChatGPT and Gemini Advanced (formerly Google Bard).
NVIDIA is skillfully utilizing containers and Kubernetes, which are crucial for modern workloads because they’re easy to move around and can grow as needed. So, in this blog post, let’s discuss how NVIDIA is using cloud-native technologies to strengthen their GPU infrastructure with Kubernetes to empower the unprecident Gen AI growth.
An interesting fact is that Kubernetes lacks native support for GPU scheduling and management, it is done by using device plugins.
领英推荐
NVIDIA is making waves in the cloud-native world by seamlessly integrating its GPU and DPU hardware accelerators with Kubernetes, ensuring that GPUs are accessible to cloud-native developers:
Check out the following blog post to get a glimpse of this endeavor :
People are going to use more and more AI. Acceleration is going to be the path forward for computing. These fundamental trends, I completely believe in them. — Jensen Huang — CEO & Co-founder of NVIDIA
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Embrace the Pathless Path
Exactly 11 months ago, I started this newsletter after destiny led me down a path I hadn't experienced before. Many may see uncertainty as undesirable, but to me, uncertainty also means infinite possibilities.
In the past 11 months, I've explored many different things based on a blueprint I'd only dreamed about before. I've enjoyed many moments re-reading a book called "The Pathless Path" by Paul Millard. It delves into embracing uncertainty in work and life through insightful stories and practical advice.
Practically, it's not easy to find fulfillment beyond the conventional path. The unconventional path is often seen as risky but also sometimes incredibly exciting. I believe that's how each of us forges our own unique narrative.
I haven't forgotten that I promised a book review, it will be coming soon on my Medium publication. Feel free to follow me if you're interested in my take on it. If you're interested in
this book, you can check out the Audible audiobook here or take a look at Amazon.
“The pathless path is an alternative to the default path. It is an embrace of uncertainty and discomfort. It’s a call to adventure in a world that tells us to conform. For me, it’s also a gentle reminder to laugh when things feel out of control and trusting that an uncertain future is not a problem to be solved.” ― Paul Millerd, The Author of The Pathless Path: Imagining a New Story For Work and Life
What's Next ?
We have been fine-tuning the Cloud-Native Innovators newsletter to ensure it is tailored for tech professionals to help them stay updated on the latest trends in cloud-native, serverless, and generative AI technologies but also from a technies point of view. As we've been optimizing the production pipeline for the CloudMelon Vis blog and Medium publication to ensure timely updates. For those who enjoy video content, check out our CloudMelon Vis YouTube channel. If you'd like to stay connected and receive all our updates, we have build a weekly edition for Cloud-Native Innovator newsletter which you can subscribe to it here. Also, don't forget to forward or follow our monthly updates on LinkedIn if you haven't already!
Thanks, community, for your continued support! And let’s keep educating ourselves, I will see you in the next one!
Best wishes from Paris
M.
Senior System Reliability Engineer / Platform Engineer
8 个月Taban C. Kubernetes + GPU + AI
Recruiter
8 个月[email protected]
Client-Focused Problem Solver | Transforming Business Complexity into Clear, Efficient Solutions
8 个月AI/ML workloads on K8s sharing the costly compute like GPU/TPU using container technology will be a game changer. Plus you will get all the benefits of orchestration that K8s bring to the table.
? Empowered @Microsoft & CNCF Ambassador & Founder @CVisiona & Published Author
9 个月This issue is a continuation of a previous issue about NVIDIA H100, but this time with a focus diving into the connection between Kubernetes and GPUs, as well as NViDIA's endeavors to make sure cloud-native developers leverage GPU infrastructure for AI/ML workloads in their organizations. ?? https://www.dhirubhai.net/pulse/innovating-cloud-native-ai-m%25C3%25A9lony-qin/?trackingId=OfO4wyFoRYmGVsrbvVDH%2Fg%3D%3D