Overlap

Orchestration for Go

Orchestration tools that run on Go. The Catch for each, not a winner list.

6 tools · the Catch, not a ranking

BifrostApache-2.0 AI gateway — perf angle vs LiteLLM (Maxim)
Vs LiteLLM: same gateway job with a Go/perf positioning — not a model marketplace. Maxim upsell: enterprise/clustering/adaptive LB/OIDC provisioning and getmaxim.ai Bifrost enterprise pages are the commercial gravity; OSS gateway still runs locally. You still pay upstream model providers.
WeKnoraMIT self-host RAG/knowledge platform (Tencent)
Optional weknora.weixin.qq.com host is a separate product surface from the MIT self-host forever path — do not treat Tencent’s hosted WeChat-adjacent portal as the license or the ops model. LICENSE ships with THIRD_PARTY_NOTICES / licenses/ for bundled deps — MIT on the project, not a free pass on every vendored component. Vs LibreChat / AnythingLLM: WeKnora is knowledge/RAG+agent+wiki platform weight, not only a multi-provider chat UI.
Agent SubstrateHigh-density secure sandbox runtime for idle-heavy agent workloads
Vs AgentBox and Flue: Substrate is the dense sandbox/runtime control plane on Kubernetes, not a developer ADE and not a TypeScript harness framework. Ops cost is real — you need cluster competence. README notes it is not an officially supported Google product.
AX (Agent Executor)Apache-2.0 Go CLI and Kubernetes CRDs for running agent tasks
This is AX Agent Executor, not the live AX Check (Gauge) evaluation product — the names collide, so use the ax-agent-executor slug. Vs Agent Substrate: AX is the task/CLI/CRD experience on top of an agent runtime; vs OneCLI and Dexto: it is Kubernetes execution infrastructure, not a general desktop agent; vs Cua: it is not a browser/computer-use surface. Kubernetes and Agent Substrate operations are still your problem.
Docker AgentApache-2.0 YAML-defined agents with MCP toolsets — runs as `docker agent`
Agents are YAML config, not code in an SDK — great when your tools already ship as Docker images or MCP servers, limiting when you need custom control flow in Python/TypeScript. Local models need Docker Model Runner; otherwise bring your own provider API key and pay per token. Vs crewai (Python role/crew framework) and strands-agents (AWS model-driven SDK): Docker Agent is the declarative, container-native lane.
ScionApache-2.0 platform for running coding agents as teams
It needs a container runtime: Podman, Docker or Apple Container (Kubernetes or Cloud Run for hosted runs). There are no GitHub releases yet, only preview tags such as v0.3.0-preview.3, and the README warns that the project is evolving rapidly and APIs and configuration may change. It is from a Google Cloud repo but, in its own words, not an officially supported Google product. Every agent still runs on your own model keys and their token costs.