Ekin Karabulut

Ekin Karabulut is a data scientist and developer advocate previously at Run:ai, now at NVIDIA, exploring the efficient usage of large models in different production scenarios. Previously she worked on privacy implications of federated learning, focused on distributed training techniques and got fascinated by inefficiencies in GPU usage in research and industry settings. She established the AI Infrastructure Club and is based in Munich, Germany.
Avatar photo

Posts by Ekin Karabulut

Data Center / Cloud

Agent Substrate: Advancing Kubernetes for Agents at Scale

AI agents spend most of their time idle, waiting on a human prompt, a tool result or a model response. Kubernetes wasn’t built for that. Running one Pod per... 12 MIN READ
Data Center / Cloud

Start and Restore GPU Workloads in Seconds with NVIDIA Snapshot

NVIDIA Snapshot, a new open-source component of the NVIDIA DSX AI Factory Platform, makes initialized GPU workloads reusable across inference... 8 MIN READ
Data Center / Cloud

Memory-Enforced GPU Sharing in Kubernetes with NVIDIA CUDA 13.4

Many AI workloads need only a fraction of a GPU. Giving each one an entire device can leave capacity idle; sharing GPUs lets platform teams serve more workloads... 7 MIN READ
Data Center / Cloud

NVIDIA Run:ai Is Now Open Source as Part of NVIDIA DSX AI Factory Platform

NVIDIA is making the full NVIDIA Run:ai platform available as open source software, giving customers, developers, and ecosystem partners access to... 13 MIN READ
Data Center / Cloud

How to Run Isolated Tenant Kubernetes Clusters on Shared GPU Infrastructure

Running a dedicated Kubernetes cluster per team often results in more isolation than an organization requires. While one cluster can be successfully shared... 10 MIN READ
Data Center / Cloud

Deploying Disaggregated LLM Inference Workloads on Kubernetes

As large language model (LLM) inference workloads grow in complexity, a single monolithic serving process starts to hit its limits. Prefill and decode stages... 14 MIN READ