You're designing the control plane for your AI infrastructure, and you need a component that can orchestrate containerized applications across a cluster of nodes — handling scheduling, scaling, networking, and lifecycle management. Which tool is purpose-built for this?
Select an answer to reveal the explanation.
Short Explanation and Infographic
Kubernetes is the container orchestration platform. NCCL is for GPU-to-GPU communication, Triton is an inference server, DCGM is for monitoring. Only Kubernetes handles the full orchestration lifecycle.
Full explanation below image
Full Explanation
Kubernetes has become the standard container orchestration platform for AI workloads. It provides: scheduling (placing containers on nodes), resource management (memory, CPU, GPU), networking (service discovery, load balancing), storage orchestration (persistent volumes), lifecycle management (rolling updates, health checks), and scaling (horizontal pod autoscaling). When you containerize an AI workload, Kubernetes takes it from there. NCCL (NVIDIA Collective Communications Library) is a GPU communication library for fast all-reduce operations in distributed training — it's not an orchestrator. Triton Inference Server is a specific inference serving platform by NVIDIA — it runs inside containers that Kubernetes orchestrates. DCGM is for GPU monitoring and health, not orchestration. The question tests whether you know the architectural roles of different components in an AI infrastructure stack.