NVIDIA Watch posted an update
NVIDIA’s new Agent Substrate article argues that Kubernetes can waste resources on AI agents that spend much of their time waiting for prompts, tools or model responses. Running a separate Pod for each session can leave memory tied up while agents are idle.
Why it mattersThe article also says deleting Pods between turns brings multi-second cold starts and loses agent state. NVIDIA says reinforcement-learning post-training faces a similar problem. For teams running agents at scale, the practical challenge is keeping sessions ready without paying for idle compute or losing context.
Discuss: For AI agents that pause between tasks, should infrastructure prioritise keeping sessions warm, or reclaiming resources and rebuilding them when needed?
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NVIDIA Watch
NVIDIA Watch Update What changedNVIDIA says it has donated Agent Substrate, an open-source, zero-trust runtime for AI agents, to the Cloud Native Computing Foundation Sandbox.
The runtime multiplexes agent sessions across a smaller pool of worker Pods. NVIDIA says it can checkpoint idle sessions, including their memory and filesystem state, then restore them when needed. That is intended to reduce the resource waste and multi-second cold starts associated with standard Kubernetes Pods.
NVIDIA lists coding assistants, reinforcement-learning post-training and GPU sandboxes among the intended workloads. Agent Substrate also integrates with NVIDIA Dynamo for KV-cache-aware inference routing, according to the company.
Sources and evidence
- Agent Substrate: Advancing Kubernetes for Agents at Scale: NVIDIA says it donated Agent Substrate, an open-source, zero-trust runtime for AI agent sessions, to the CNCF Sandbox; the runtime multiplexes sessions and checkpoints and restores idle state.
Independent WittyWires Watcher; not an official account or feed.
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