In this episode, we talk with Abdel Sghiouar and Mofi Rahman, Developer Advocates at Google and (guest) hosts of the Kubernetes Podcast from Google. Together, we dive into one central question: can you truly run LLMs reliably and at scale on Kubernetes? It quickly becomes clear that LLM workloads behave nothing like traditional web applications: GPUs are scarce, expensive, and difficult to schedule.Models are massive — some reaching 700GB — making load times, storage throughput, and caching ...
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In this episode, we talk with Abdel Sghiouar and Mofi Rahman, Developer Advocates at Google and (guest) hosts of the Kubernetes Podcast from Google. Together, we dive into one central question: can you truly run LLMs reliably and at scale on Kubernetes? It quickly becomes clear that LLM workloads behave nothing like traditional web applications: GPUs are scarce, expensive, and difficult to schedule.Models are massive — some reaching 700GB — making load times, storage throughput, and caching ...
#114 Do We Even Need Logs Anymore? And What is vCluster?
De Nederlandse Kubernetes Podcast
41 minutes
1 month ago
#114 Do We Even Need Logs Anymore? And What is vCluster?
In this episode, we sit down with Nicolas Fränkel, Developer Advocate at Loft Labs, to talk about two things every Cloud Native engineer should know in 2025: 🪵 OpenTelemetry Tracing and 🌀 vCluster. Nicolas helps us unpack why tracing is often the missing pillar of observability — and whether it might one day make traditional logs obsolete. We dive into: How traces, spans and sampling actually work under the hood.Why post-sampling may save your storage bill.What happens when you combine traci...
De Nederlandse Kubernetes Podcast
In this episode, we talk with Abdel Sghiouar and Mofi Rahman, Developer Advocates at Google and (guest) hosts of the Kubernetes Podcast from Google. Together, we dive into one central question: can you truly run LLMs reliably and at scale on Kubernetes? It quickly becomes clear that LLM workloads behave nothing like traditional web applications: GPUs are scarce, expensive, and difficult to schedule.Models are massive — some reaching 700GB — making load times, storage throughput, and caching ...
