Agent execution runtime engineered to run millions of sandboxes

NOTE: This is not an officially supported Google product. This project is not eligible for the Google Open Source Software Vulnerability Rewards Program.

Agent Substrate is a secure-by-default agent execution runtime engineered to run millions of sandboxes with 10x higher density than standard container runtimes. Purpose-built for the era of autonomous agents, Substrate delivers sub-500ms resume operations at over 500 suspend/resume activations per second with native zero-trust kernel and network isolation. It supports multiple sandbox technologies including microVMs and gVisor, enabling consistent lifecycle operations for all sandbox types.

At its core, Agent Substrate maps a larger set of “actors” (applications such as agents) onto a smaller set of ready “workers”, relying on the fact that agent-like applications tend to be idle most of the time to achieve heavy multiplexing. It provides functionality to manage an actor’s lifecycle (e.g. create/destroy, suspend/resume), to assign actors to workers in real time, and to route incoming traffic to them.

Agent Substrate is intended to be a low-opinion system. The workloads it manages don't have to be literal AI agents, but those are the best example of the kind of applications it is designed for. It is not an SDK for building agents, but rather a system for running them at scale.

Agent Substrate leverages Kubernetes for the infrastructure provisioning and worker lifecycle management (Kubernetes Pods). It builds on top of Kubernetes features like Pods and Pod autoscaling, while Agent Substrate provides agent-specific scheduling and control to achieve lower latency. Using Kubernetes as the underlying system enables consistent infrastructure management across all workloads types that are required for end to end agentic deployments and allows holistic infrastructure optimizations for RL scenarios that span agentic, inference and training cycles.

Watch the Agent Substrate cluster multiplex ~250 stateful actors across just 8 physical pods.

This demo highlights the core developer experience and "Agentic Infrastructure" capabilities of Substrate:

1. Actor Teleport: High-performance suspend and resume of actors onto any available worker in the pool with sub-second activation.
2. State Persistence: Persistent working memory (volatile RAM) and filesystem state preserved perfectly across hibernation cycles via full-state snapshots.
3. Agent Multiplexing: Demonstrates 30x+ oversubscription by "juggling" a large registry of stateful actors onto a small pool of shared physical pods.

To reproduce this demo in your own cluster, please refer to the detailed walkthrough in the Counter Demo.

For more videos and walkthroughs, visit our YouTube channel: agent-substrate.

Agent Substrate is designed to be framework and agent harness agnostic. Because it manages standard OCI containers at the kernel level (via gVisor), it can host agents built on any stack.

• Agent Development Kit (ADK): Support for ADK agents with session state preservation across invocations as actor state. Ideal for all types of agents and stateful tool or subagent calls.

• LangChain: Ideal execution environment for LangChain agents and tool calls.

• Claude Code, CodeX, and Antigravity: Support for high-density, stateful coding environments that preserve system state and filesystem state across sessions.

• Model Context Protocol (MCP): Support for deploying secure, sandboxed MCP servers as Substrate Actors to provide durable tools for any model.

• Agent Executor: A distributed agent runtime that demonstrates building a secure, hyper-scalable agent harness on Agent Substrate (see theannouncement blog andintegration guide ).

• kagent: A CNCF Sandbox project and Kubernetes-native framework for building, deploying, and managing AI agents that uses Agent Substrate to run sandboxed, stateful agent workloads (see theannouncement blog ).

Agent Substrate is currently in early development. It is not ready for production use, and the APIs are almost guaranteed to change. We are not making any guarantees about backward compatibility at this stage, and everything in this project may be changed.

Currently we aim to support the latest stable release of Kubernetes, and the previous minor release.

For announcements, technical discussions, and community support, please join the ate-dev Google Group.

We host a weekly community meeting every Thursday from 10:00am - 11:00am PST.

• Video call link: https://meet.google.com/uhq-cxvn-dhy
• Or dial: (US) +1 253-289-6971 PIN: 787 664 574 59#
• More phone numbers: https://tel.meet/uhq-cxvn-dhy?pin=9044088223662
• Meeting notes for the weekly sync meeting
• Recordings and transcripts of all community meetings

We also have channels in the CNCF slack; request an invite here if you don't have access.

• #substrate-users to discuss using substrate.
• #substrate-dev to discuss developing substrate.

Please see CONTRIBUTING.md for guidelines on contributing to the project. We welcome contributions of all kinds, but the project is VERY young. Our immediate focus is on building out the core system and demos, so we may not be able to review or merge contributions that don't align with those goals in the near term.

To quickly set up the complete environment:

Make sure you have Go ,kubectl , and docker installed and configured on your dev machine. We will automatically manage other dependencies via Go, includingkind . 2. Run the following steps:

hack/create-kind-cluster.sh

hack/install-ate-kind.sh --deploy-ate-system

hack/install-ate-kind.sh --deploy-demo-counter

go install ./cmd/kubectl-ate

kubectl ate create actor my-counter-1 -a ate-demo-counter --template counter

kubectl port-forward -n ate-system svc/atenet-router 8000:80

1. In a separate terminal , send an HTTP request to increment the counter:

curl -X POST \
   -H "ate-target-actor: ate-demo-counter/my-counter-1" \
   -i http://localhost:8000/

Worker capacity is versioned: the dataplane (the atelet DaemonSet and the worker pods) schedules only on nodes that carry the ate.dev/substrate-version label, and the install stamps it on every node that exists when it runs. A node added later hosts no workers until you label it with the installed version (kubectl label node <node> ate.dev/substrate-version=<build version>). kubectl get ds -n ate-system -l app=atelet -L ate.dev/substrate-version prints the installed version, off the atelet DaemonSet the install created.

Create and configure your environment file:

cp hack/ate-dev-env.sh.example .ate-dev-env.sh

source .ate-dev-env.sh

Enable application-default credentials for gcloud:

gcloud auth application-default login --project=${PROJECT_ID}

Provision the required GCP resources (GKE cluster, GCS, and IAM bindings):

go run ./tools/setup-gcp bootstrap

On a fresh project this step also creates the atelet Workload Identity IAM grants that snapshots depend on — see what create iam actually grants to audit them or apply them manually. If you bring your own cluster instead, note the required Kubernetes beta APIs can only be enabledat cluster creation — see theCreate Cluster warning . 4. Deploy the Agent Substrate system to your cluster:

./hack/install-ate.sh --deploy-ate-system

Nodes that GKE adds later (autoscaling, auto-repair, node upgrades) are born with the node pool's labels, so the pool needs ate.dev/substrate-version too; seeNode version labels . 5. You can then deploy the sample applications. See demos/counter/README.md ordemos/sandbox/README.md for detailed walkthroughs.

./hack/install-ate.sh --deploy-demo-counter

You can run individual setup steps to create GCP resources as needed. See go run ./tools/setup-gcp --help for available options. For example:

go run ./tools/setup-gcp create cluster
go run ./tools/setup-gcp create bucket

To run the PostgreSQL store backend on Cloud SQL — with IAM database authentication and no passwords — see tools/setup-gcp/cloud-sql.md.

Similarly, you can deploy or cleanup specific Agent Substrate components using the installation script. See ./hack/install-ate.sh --help for all options.

./hack/install-ate.sh --deploy-ate-apiserver

./hack/install-ate.sh --delete-all

If you need to delete the resources created by the setup script, you can use the provided script hack/teardown.sh. This script will delete resources in the reverse order of creation and handles partial failures gracefully.

./hack/teardown.sh --all

Or run individual teardown steps as needed (see ./hack/teardown.sh for available options).

If you need to delete the local kind cluster and its registry (if it was created by hack/create-kind-cluster.sh):

./hack/delete-kind-cluster.sh

We provide several sample applications demonstrating Agent Substrate's capabilities:

1. Counter Demo : A stateful Go HTTP server demonstrating state preservation across suspends/resumes, and on-demand actor resumption and routing via the Substrate router.
2. Sandbox Demo (Antigravity) : A secure, sandboxed execution environment (running Alpine Linux) that allows arbitrary shell execution while preserving filesystem state across sessions.
3. Claude Code Multiplex : Demonstrates oversubscribing physical hardware by multiplexing multiple Claude Code agents onto a limited pool of workers.
4. Multi-Template : TwoActorTemplate s running different binaries share oneWorkerPool , even though the templates live in different atespaces.
5. Request Parking : An oversubscribed pool where the router holds inbound requests until a worker frees up, instead of returning503 .
6. Autoscaled WorkerPool : Scales aWorkerPool on its assigned-worker count with an HPA fed by prometheus-adapter.

• Architecture : How the control plane, node supervisor, and networking stack fit together.

• API Configuration Guide : Detailed reference for configuring WorkerPools, ActorTemplates, Secrets, and Volumes.

• Full CLI Documentation : Installation and usage forkubectl-ate .

• Glossary : Core terms (Actor, Atespace, ActorTemplate, WorkerPool, Worker, ate-api-server, atenet, atelet, ateom) and how they relate.

• Integration Repositories : Where integrations live, how their repositories are named, and how fixes flow back to core.

• Observability Guide : Guide to actor logging, metrics, and distributed tracing.

• Authentication Guide : Configure trusted JWT providers and human credentials.

• Enabling man-in-the-middle (MITM) interception for Actor Egress policy : Egress policies such as header injection depend on MITM interception of Actor traffic. This guide explains how an Actor should be configured to enable interception.

• Request Parking : How the router parks requests through transient worker-pool saturation.

• Rolling Upgrade Runbook : Upgrade a running substrate node by node without losing actor state.

• Threat Model : Trust boundaries, assumptions, and known risks.

• Roadmap : Current limitations and what is planned next.

• Benchmarking Guide : Locust-based load tests, monitoring stack, and the orchestrated benchmark harness.

• cmd/ateapi : The core control plane API server exposing gRPC endpoints to manage actor and worker lifecycles.

• cmd/atelet : A node-level DaemonSet that supervises physical worker pods, coordinates snapshotting, and manages state transfers.

• cmd/atecontroller : A Kubernetes controller that reconciles WorkerPool custom resources.

• cmd/atenet : A combined networking controller providing Envoy routing and proxy sidecars.

• cmd/ateom-gvisor : An interior-pod helper running inside sandboxed worker pods to executerunsc checkpoint and restore commands.

• cmd/ateom-microvm : The micro-VM peer ofateom-gvisor , running actors as cloud-hypervisor VMs.

• cmd/podcertcontroller : A "polyfill" that provides Pod Certificate signers that will eventually ship in upstream Kubernetes (with different names).

• cmd/kubectl-ate : A CLI tool for managing Agent Substrate resources. See itsREADME .

• cmd/benchmarking : Synthetic workloads used by the load tests, includingglutton , which consumes RAM, disk, and file descriptors on demand.

• tools/setup-gcp : A provisioning utility to set up the necessary GCP infrastructure resources (GKE, GCS, IAM).

• demos/ : Sample applications demonstrating Agent Substrate capabilities.

source & further reading

github.com — original article UsageBar – Claude Code and Codex rate limits in the macOS menu bar JevEmon: Typed Decisions over GBA RAM to Walk Pokémon FireRed Show HN: Jev-CLI – CLI wrapper for JEV typesafe AI model