Now the worker pool can be scaled via regular `kubectl scale` commands.
Use server-side-apply to apply changes.
Propagate the effective number of replicas from the status of the
managed deployment.
Fixes https://github.com/agent-substrate/substrate/issues/48
Adds golangci-lint v2.12.2 using the per-tool-module pattern under
hack/tools/golangci-lint/. The verifier at hack/verify/golangci-lint.sh
is auto-discovered by hack/verify-all.sh, so the existing CI verify
step picks it up with no workflow YAML change.
Ships .golangci.yaml with the standard linter set, a make lint
target, and a verify wrapper that pins GOOS=linux so ateom-gvisor's
netlink references typecheck on macOS the same way they do on CI.
Adjustments to keep the first run clean: two dead-code deletions
((*runsc).cmdList, MemoryPullCache.gcsClient), two SA9003 empty
branches replaced with slog.Error / t.Logf, one S1008 return-bool
simplification, and inline //nolint for one intentional best-effort
ReleaseLock plus four audit-tracked SA1019 deprecations.
Signed-off-by: Davanum Srinivas <davanum@gmail.com>
This commit was automatically generated by the tools/reorg tool.
```
go run ./tools/reorg
go generate ./...
bash benchmarking/locust/generate_protos.sh
```
This is the initial release of the Agent Substrate.
Agent substrate is a system built on top of Kubernetes which manages agent-like
workloads to achieve higher scale and efficiency than Kubernetes alone can
offer, with lower latency. It builds on top of Kubernetes features like
Pods and Pod autoscaling, but takes the Kubernetes control-plane out of the
critical path to achieve lower latency.
It can run on any Kubernetes cluster and does not inhibit “regular” use of
Kubernetes in any way. Kubernetes provides the infrastructure provisioning and
management for all types of workloads, while Agent Substrate provides
agent-specific scheduling and control.
At its core, Agent Substrate maps a larger set of “actors” (applications such
as agents) onto a smaller set of ready “workers” (Kubernetes Pods), 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 is currently in VERY 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.
Co-authored-by: Alex Bulankou <alexbu@google.com>
Co-authored-by: Benjamin Elder <bentheelder@google.com>
Co-authored-by: Bowei Du <bowei@google.com>
Co-authored-by: Dmitry Berkovich <dberkov@google.com>
Co-authored-by: Fabricio Voznika <fvoznika@google.com>
Co-authored-by: Francisco Cabrera <fclieutier@google.com>
Co-authored-by: Haven Xia <haoyuxia@google.com>
Co-authored-by: Julian Gutierrez Oschmann <juliangut@google.com>
Co-authored-by: Kevin Steuer <ksteuer@google.com>
Co-authored-by: Max Smythe <smythe@google.com>
Co-authored-by: Maya Wang <mymaya@google.com>
Co-authored-by: Michael Taufen <mtaufen@google.com>
Co-authored-by: Shruti Nair <shrutinair@google.com>
Co-authored-by: Taahir Ahmed <taahm@google.com>
Co-authored-by: Tim Hockin <thockin@google.com>
Co-authored-by: Zoe Zhao <zoezhao@google.com>
Tim Hockin