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- Видео 183
- Просмотров 28 571
Kubernetes Bytes
Добавлен 5 авг 2021
Kubernetes Bytes is a podcast bringing you the latest from the world of cloud native data management. Hosts Ryan Wallner and Bhavin Shah come to you from Boston, Massachusetts with experienced backgrounds in cloud-native tech. They'll be sharing their thoughts on recent cloud native news and talking to industry experts about their experiences and challenges managing the wealth of data in today's cloud-native ecosystem.
Building scalable data platforms using Data on EKS
In this episode of the Kubernetes Bytes podcast, Bhavin sits down with Alex Lines and Vara Bonthu from AWS to talk about the Data on EKS project. The discussion dives into why AWS decided to build the Data on EKS project and provide patterns for EKS customers to use to deploy data platforms, machine learning and GenAI tools on EKS clusters. They talk about what's included and what's not included with each of these patterns and whats coming down the line.
#DataonEKS #DataOnKubernetes #kubernetes #KubernetesBytes
Check out our website at kubernetesbytes.com/
Cloud Native News:
- kubernetes.io/blog/2024/08/16/kubernetes-1-31-prevent-persistentvolume-leaks-when-deleting-out-of-order/
- kubernete...
#DataonEKS #DataOnKubernetes #kubernetes #KubernetesBytes
Check out our website at kubernetesbytes.com/
Cloud Native News:
- kubernetes.io/blog/2024/08/16/kubernetes-1-31-prevent-persistentvolume-leaks-when-deleting-out-of-order/
- kubernete...
Просмотров: 31
Видео
Deploy and fine-tune LLM models on Kubernetes using KAITO
Просмотров 25014 дней назад
Deploy and fine-tune LLM models on Kubernetes using KAITO
The business case for cloud-native and Kubernetes
Просмотров 38Месяц назад
The business case for cloud-native and Kubernetes
Building the AI Hyperscaler with Kubernetes
Просмотров 92Месяц назад
Building the AI Hyperscaler with Kubernetes
Shifting Minds: Exploring OpenShift's AI Landscape
Просмотров 782 месяца назад
Shifting Minds: Exploring OpenShift's AI Landscape
Training Machine Learning (ML) models on Kubernetes
Просмотров 1322 месяца назад
Training Machine Learning (ML) models on Kubernetes
The evolution of service mesh technologies
Просмотров 743 месяца назад
The evolution of service mesh technologies
How to Host and Access Local Models on Kubernetes | Model Catalog Solution
Просмотров 204 месяца назад
How to Host and Access Local Models on Kubernetes | Model Catalog Solution
Ops Ops Hooray! Navigating IDPs from an Ops perspective
Просмотров 2385 месяцев назад
Ops Ops Hooray! Navigating IDPs from an Ops perspective
IDPs Unveiled: Accelerating Deployment on Kubernetes
Просмотров 446 месяцев назад
IDPs Unveiled: Accelerating Deployment on Kubernetes
Running Kubernetes at the Edge using K3s
Просмотров 756 месяцев назад
Running Kubernetes at the Edge using K3s
Running multi-tenant Kubernetes clusters using vCluster
Просмотров 737 месяцев назад
Running multi-tenant Kubernetes clusters using vCluster
Byte-sized: Exploring the Basics of AI in Plain English
Просмотров 1378 месяцев назад
Byte-sized: Exploring the Basics of AI in Plain English
Kubecon North America 2023: Highlights, Themes and Key Takeaways
Просмотров 559 месяцев назад
Kubecon North America 2023: Highlights, Themes and Key Takeaways
Universal Control Planes for Kubernetes and Beyond
Просмотров 629 месяцев назад
Universal Control Planes for Kubernetes and Beyond
DevOpsDays Boston - Helping developers be more productive in a multi-cloud world
Просмотров 4010 месяцев назад
DevOpsDays Boston - Helping developers be more productive in a multi-cloud world
DevOpsDays Boston - Platform Engineering and Internal Developer Platforms
Просмотров 5610 месяцев назад
DevOpsDays Boston - Platform Engineering and Internal Developer Platforms
DevOpsDays Boston - Real value of community
Просмотров 4310 месяцев назад
DevOpsDays Boston - Real value of community
How Chick-fil-A adopts GitOps and K3s at the Edge
Просмотров 73511 месяцев назад
How Chick-fil-A adopts GitOps and K3s at the Edge
Nodeless Kubernetes - Optimizing costs with just in time compute
Просмотров 4611 месяцев назад
Nodeless Kubernetes - Optimizing costs with just in time compute
Solving Multicloud with Seamless Connectivity and AI - with Rob Croteau
Просмотров 7611 месяцев назад
Solving Multicloud with Seamless Connectivity and AI - with Rob Croteau
Generative AI: The New Frontier in Kubernetes Problem-Solving
Просмотров 238Год назад
Generative AI: The New Frontier in Kubernetes Problem-Solving
From Manual to Automatic: Revolutionizing Cloud Native Stack Deployment with Argonaut
Просмотров 40Год назад
From Manual to Automatic: Revolutionizing Cloud Native Stack Deployment with Argonaut
How frequently does one spins up a cluster ?
It depends on the organization. Usually, you will see people using long term clusters, for their test beds and for development. But, new clusters are spun up whenever CICD jobs are triggered for automated testing.
Why 21 sec, where is the full thing?
Find the link to the full episode here - ruclips.net/video/0UG3_gictCQ/видео.htmlsi=hwosQ8TVs0K2rc26
Thanks for mention JuiceFS, hope it's helpful. ❤
Thanks for listening!
Dan, I love the stuff you talk about. You use different terminology than me, but I see all the same trends as you do in the industry, and the need for multi-cloud, multi-cluster platforms. Great job! I might steal some of your terms :) but I often use the term "platform approach" for what you said about "K8s stop at the platform layer"
Thank you, Michael. Feel free to re-use any term!
First off, thanks so much on the session covering AI/ML/DeepLearning and touching on some of the specifics for LLMs . I did want to mention a few items that I have learned when using LLMs in my field as a Cloud Solutions Architect. When I use an LLM to summarise or focus on some text that i’m looking for a general, high level description of a subject (for example: uploading a group of manifest to validate configurations or possible explain the connection between CRDs and the Kubernetes resources), I use this pattern or prompt to confirm that the output is sufficiently valid and not inaccurate. Using the Fact check list pattern:(Definition:a pattern used to identify facts that are critically important to my question that is referring to an uploaded text file). It allows one to have the confidence that the result provided in the response is sufficient and by focusing on those key items, items that are highlighted and allow the requestor to confirm they are accurate. This pattern is one example of using the LLM as a tool to improve the results as intended.
thats an interesting example. Do you use OpenAI's GPT models or do you host something on your own locally?
@@kubernetesbytes I do use OpenAI's GPT model. Of course, I'm careful to scrub any manifest or other documents before uploading anything. I also turn off 'training' mode to further restrict the content that might be accessible to OpenAI. I also use the Advanced Data Analysis tool to generate slide decks from documentation or readme files as well.
"Promo SM" ❣️
Always fun listening to Viktor. Thanks for this episode 😊
Thank you for being a listener :)
Insightful session, thank you!
Thanks for the mention 👌
You guys do some awesome work! Would be great to have you on the pod as well!
@@kubernetesbytes sounds great - please reach out to Christian Hernandez on CNCF Slack :)
Hi guys, Love your podcast. I think your bitly link for your slack invite is bad.
Weird - how about this - bit.ly/k8sbytes
As an audio only person so far… I must say, Bhavin looks exactly like what I had imagined 😅 Ryan on the other hand, turned out to be much younger than I expected 😁😂
Game Changer
really enjoyed watching this 😄👍
Promo`SM 💯