agent-substrate/substratePublic

Agent Substrate: the core system

AI summary: A high-density runtime control plane for orchestrating and multiplexing large-scale AI agent deployments.

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GoApache-2.0Created May 13, 2026Last push todayLatest release v0.0.0+122 stars this week+241 this month

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since May 17, 2026
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1.8K stars as of Sep 10, 2026, tracked back to May 17, 2026. Historical curve reconstructed from public GitHub event archives, calibrated to the current total.

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    +122 stars this week

  • Very active

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  • Permissive license

    Apache-2.0

  • Continuous integration

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What substrate does

Agent Substrate provides a performant, Kubernetes-native runtime environment explicitly designed to manage large-scale deployments of stateful AI agents. Because AI agents are often idle while waiting for LLM responses or human input, Substrate multiplexes hundreds of 'actors' onto a much smaller pool of physical workers. It manages the full lifecycle of these sandboxes, utilizing advanced snapshotting to instantly suspend and resume actors with sub-second latency while perfectly preserving volatile memory and filesystem state. By deeply integrating with technologies like gVisor, it ensures secure, framework-agnostic execution for any agent harness.

Agent Substrate is for platform engineers, DevOps teams, and AI researchers building highly scalable, multi-agent systems. It requires expertise in Kubernetes administration and distributed system architecture.

  • High-density multiplexing: Efficiently oversubscribes hardware by juggling stateful actors across a limited pool of physical pods.
  • Sub-second teleportation: Rapidly suspends and resumes actors on any available worker, preserving RAM and filesystem state perfectly.
  • Framework agnostic execution: Manages standard OCI containers at the kernel level, supporting LangChain, Claude Code, and custom ADKs.
  • State preservation: Utilizes full-state snapshots to maintain working memory across hibernation cycles without data loss.
  • Kubernetes integration: Leverages standard Kubernetes infrastructure and Custom Resource Definitions (CRDs) for dynamic routing and scaling.

Where teams use it

Scalable agent hosting

Platform teams deploy the substrate to run thousands of concurrent AI agents efficiently on a highly constrained hardware footprint.

Stateful terminal environments

Developers use it to host Claude Code agents that maintain terminal state, directory context, and memory across multiple sessions.

Secure tool sandboxing

Engineers deploy Model Context Protocol (MCP) servers as substrate actors to provide durable, safely isolated tools for external LLMs.

Cost-optimized execution

Startups drastically reduce cloud infrastructure costs by aggressively multiplexing idle agent workloads instead of provisioning dedicated instances.

Getting started: hack/create-kind-cluster.sh && hack/install-ate-kind.sh --deploy-ate-system

README

main branch

Agent Substrate

License

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

What is Agent Substrate?

Agent Substrate delivers a performant, high density runtime environment for large scale agent deployments. The agent substrate control plane provides full lifecycle management for agent sandboxes, delivering sub-second agent resume/suspend operations, and allows heavy multiplexing of agents onto the same computer infrastructure. 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.

Demo

Agent Substrate Demo

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. Instant 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 Swarm 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.

Framework Agnostic & Compatibility

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): Native support for ADK-compatible actor identity and persistent working memory.
  • LangChain: Ideal execution environment for long-running, stateful LangChain agents and sandboxed tool-calling.
  • Claude Code & CodeX: Support for high-density, stateful coding environments that preserve terminal and filesystem state across sessions.
  • Model Context Protocol (MCP): Deploy secure, sandboxed MCP servers as Substrate Actors to provide durable tools for any LLM.

Ecosystem & Examples

Status and compatibility

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.

Supported Kubernetes Releases

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

Community

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.

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

Developing

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.

Quickstart (Development)

To quickly set up the complete environment:

  1. Make sure you have Go, kubectl, and docker installed and configured on your dev machine. We will automatically manage other dependencies via Go, including kind.

  2. Run the following steps:

# create cluster and local registry (IPv4; IP_FAMILY=dual|ipv6 overrides)
hack/create-kind-cluster.sh

# install ate, PostgreSQL, rustfs
hack/install-ate-kind.sh --deploy-ate-system

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

# install kubectl-ate
go install ./cmd/kubectl-ate

# create a counter actor in the demo's atespace (--template-ref names the
# actor template, resolved in the actor's atespace)
kubectl ate create actor my-counter-1 -a ate-demo-counter --template-ref counter

# port-forward the network router to bind to local port `8000`
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 "Host: my-counter-1.ate-demo-counter.actors.resources.substrate.ate.dev" -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.

GKE Quickstart (Development)

  1. Create and configure your environment file:

    cp hack/ate-dev-env.sh.example .ate-dev-env.sh
    
    # Edit .ate-dev-env.sh to match your project and preferences, then source it:
    source .ate-dev-env.sh
  2. Enable application-default credentials for gcloud:

    gcloud auth application-default login --project=${PROJECT_ID}
  3. 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 enabled at cluster creation — see the Create 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; see Node version labels.

  5. You can then deploy the sample applications. See demos/counter/README.md or demos/sandbox/README.md for detailed walkthroughs.

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

Custom Setup and Deployment

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

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

# Re-deploy only ate-apiserver of the ATE system
./hack/install-ate.sh --deploy-ate-apiserver

# Delete everything (core system and all demos)
./hack/install-ate.sh --delete-all

Tearing down resources (GCP)

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).

Tearing down local kind resources

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

Demos

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 dynamic CRD routing.
  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: Two ActorTemplates running different binaries share one WorkerPool, across three namespaces.
  5. Request Parking: An oversubscribed pool where the router holds inbound requests until a worker frees up, instead of returning 503.
  6. Autoscaled WorkerPool: Scales a WorkerPool on its assigned-worker count with an HPA fed by prometheus-adapter.

Documentation & Guides

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

Tour

Commands

  • 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 and ActorTemplate custom resources.
  • cmd/atenet: A combined networking controller providing DNS, Envoy routing, and proxy sidecars.
  • cmd/ateom-gvisor: An interior-pod helper running inside sandboxed worker pods to execute runsc checkpoint and restore commands.
  • cmd/ateom-microvm: The micro-VM peer of ateom-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 its README.
  • cmd/benchmarking: Synthetic workloads used by the load tests, including glutton, 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.
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  1. v0.0.0 - initial commitv0.0.0May 19, 2026

    This is the initial commit.

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When work happens

weekday and hour
SunMonTueWedThuFriSat036912151821Sun 0:00 — 0 commitsSun 1:00 — 0 commitsSun 2:00 — 0 commitsSun 3:00 — 1 commitsSun 4:00 — 0 commitsSun 5:00 — 1 commitsSun 6:00 — 0 commitsSun 7:00 — 0 commitsSun 8:00 — 0 commitsSun 9:00 — 0 commitsSun 10:00 — 0 commitsSun 11:00 — 1 commitsSun 12:00 — 0 commitsSun 13:00 — 1 commitsSun 14:00 — 0 commitsSun 15:00 — 0 commitsSun 16:00 — 1 commitsSun 17:00 — 0 commitsSun 18:00 — 1 commitsSun 19:00 — 0 commitsSun 20:00 — 0 commitsSun 21:00 — 3 commitsSun 22:00 — 2 commitsSun 23:00 — 3 commitsMon 0:00 — 0 commitsMon 1:00 — 1 commitsMon 2:00 — 0 commitsMon 3:00 — 2 commitsMon 4:00 — 0 commitsMon 5:00 — 1 commitsMon 6:00 — 0 commitsMon 7:00 — 1 commitsMon 8:00 — 4 commitsMon 9:00 — 7 commitsMon 10:00 — 12 commitsMon 11:00 — 8 commitsMon 12:00 — 3 commitsMon 13:00 — 20 commitsMon 14:00 — 11 commitsMon 15:00 — 12 commitsMon 16:00 — 9 commitsMon 17:00 — 14 commitsMon 18:00 — 7 commitsMon 19:00 — 8 commitsMon 20:00 — 4 commitsMon 21:00 — 2 commitsMon 22:00 — 5 commitsMon 23:00 — 2 commitsTue 0:00 — 2 commitsTue 1:00 — 1 commitsTue 2:00 — 1 commitsTue 3:00 — 0 commitsTue 4:00 — 0 commitsTue 5:00 — 6 commitsTue 6:00 — 1 commitsTue 7:00 — 6 commitsTue 8:00 — 2 commitsTue 9:00 — 6 commitsTue 10:00 — 11 commitsTue 11:00 — 8 commitsTue 12:00 — 7 commitsTue 13:00 — 3 commitsTue 14:00 — 7 commitsTue 15:00 — 4 commitsTue 16:00 — 11 commitsTue 17:00 — 15 commitsTue 18:00 — 7 commitsTue 19:00 — 11 commitsTue 20:00 — 7 commitsTue 21:00 — 6 commitsTue 22:00 — 6 commitsTue 23:00 — 3 commitsWed 0:00 — 1 commitsWed 1:00 — 2 commitsWed 2:00 — 2 commitsWed 3:00 — 0 commitsWed 4:00 — 0 commitsWed 5:00 — 1 commitsWed 6:00 — 0 commitsWed 7:00 — 1 commitsWed 8:00 — 2 commitsWed 9:00 — 9 commitsWed 10:00 — 13 commitsWed 11:00 — 8 commitsWed 12:00 — 3 commitsWed 13:00 — 8 commitsWed 14:00 — 9 commitsWed 15:00 — 10 commitsWed 16:00 — 18 commitsWed 17:00 — 7 commitsWed 18:00 — 11 commitsWed 19:00 — 8 commitsWed 20:00 — 11 commitsWed 21:00 — 10 commitsWed 22:00 — 5 commitsWed 23:00 — 3 commitsThu 0:00 — 2 commitsThu 1:00 — 1 commitsThu 2:00 — 0 commitsThu 3:00 — 2 commitsThu 4:00 — 0 commitsThu 5:00 — 4 commitsThu 6:00 — 1 commitsThu 7:00 — 0 commitsThu 8:00 — 2 commitsThu 9:00 — 5 commitsThu 10:00 — 6 commitsThu 11:00 — 8 commitsThu 12:00 — 6 commitsThu 13:00 — 14 commitsThu 14:00 — 8 commitsThu 15:00 — 11 commitsThu 16:00 — 11 commitsThu 17:00 — 9 commitsThu 18:00 — 11 commitsThu 19:00 — 12 commitsThu 20:00 — 7 commitsThu 21:00 — 8 commitsThu 22:00 — 3 commitsThu 23:00 — 5 commitsFri 0:00 — 4 commitsFri 1:00 — 3 commitsFri 2:00 — 0 commitsFri 3:00 — 0 commitsFri 4:00 — 1 commitsFri 5:00 — 0 commitsFri 6:00 — 1 commitsFri 7:00 — 2 commitsFri 8:00 — 2 commitsFri 9:00 — 4 commitsFri 10:00 — 6 commitsFri 11:00 — 10 commitsFri 12:00 — 12 commitsFri 13:00 — 14 commitsFri 14:00 — 13 commitsFri 15:00 — 7 commitsFri 16:00 — 16 commitsFri 17:00 — 13 commitsFri 18:00 — 7 commitsFri 19:00 — 15 commitsFri 20:00 — 3 commitsFri 21:00 — 11 commitsFri 22:00 — 0 commitsFri 23:00 — 2 commitsSat 0:00 — 1 commitsSat 1:00 — 2 commitsSat 2:00 — 1 commitsSat 3:00 — 1 commitsSat 4:00 — 1 commitsSat 5:00 — 2 commitsSat 6:00 — 2 commitsSat 7:00 — 0 commitsSat 8:00 — 1 commitsSat 9:00 — 4 commitsSat 10:00 — 1 commitsSat 11:00 — 1 commitsSat 12:00 — 5 commitsSat 13:00 — 8 commitsSat 14:00 — 6 commitsSat 15:00 — 2 commitsSat 16:00 — 3 commitsSat 17:00 — 0 commitsSat 18:00 — 0 commitsSat 19:00 — 2 commitsSat 20:00 — 2 commitsSat 21:00 — 0 commitsSat 22:00 — 0 commitsSat 23:00 — 1 commits
Commit volume by weekday and hour (UTC). Larger dots mean more commits.
DateListRankStars gained
Aug 22, 2026daily#5+22
Aug 21, 2026daily#5+22
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