DevOps Podcast: AI/ML Workloads on K8s - The One Mistake Everyone Makes
Автор: Mutha Nagavamsi
Загружено: 2025-11-29
Просмотров: 363
How to manage ai/ml workloads on Kubernetes? 🤔
Nothing keeps me more interested than understanding this topic.
So i did this DevOps podcast with Zafeer and few other folks to understand few important things.
These are some of the high level topics discussed in this video.
What are important concepts that help understanding of AI workloads on Kubernetes?
How traditional apps running on k8s different from running AI/ML workloads?
Is there any setup changes one should do while setting K8s for AI workloads? What role GPU play in this entire thing?
What tools are you using to manage AI/ML models on K8s
What are top operations problems you face at work? How can everyone prepare for such scenarios?
Are there any special types of autoscaling strategies for AI workloads? I mean, unlike CPU / Memory based scaling? How busty traffic handled?
Advanced Questions
Is security a big gap because running AI on K8s is relatively new to everyone.
what skills one should aquire to manage ai workloads on k8s. any specific tools should one master? any specific saas on cloud is on demand? on prem is go ahead for future?
I hear a lot about KUDA. what is it, what does it do?
#kubernetes #ai #devops
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