🧩Embeddable kernel
A single core/ directory — zero npm dependencies, zero upward imports, enforced by a purity gate. Vendor it, implement ports, assemble with createAgent().
Relionaut brings 2026-generation SRE agent capabilities — autonomous incident investigation, tool governance, bring-your-own LLM, MCP tools, persistent memory — in a portable kernel you drop into your own production systems. No platform lock-in.
Cloud SRE agents ship impressive capabilities bound to their platform. Open-source investigators bind you to their stack. Relionaut splits the difference: a self-contained agent kernel with the capabilities, and every integration point behind a port you own.
A single core/ directory — zero npm dependencies, zero upward imports, enforced by a purity gate. Vendor it, implement ports, assemble with createAgent().
Every tool declares risk; a pure govern() choke point blocks write-risk tools in read-only mode — structurally, not by prompt. Unknown MCP tools default to write (fail-closed).
Investigations distill into lessons; the next incident starts with the relevant history injected into context.
Any Anthropic- or OpenAI-compatible endpoint, Ollama for air-gapped. Your telemetry via one interface. Your toolchain via MCP.
Every run ends in a persisted terminal outcome. Conclusions arrive via enforced submit_findings with verbatim evidence quotes. Nothing is dropped from the audit trail.
Prefer batteries included? docker compose up starts the full self-hosted loop: collect, alert, investigate, auto-recover, with a web console.
The ReAct investigation loop, governance, memory, and audit live in the kernel. Everything environment-specific sits behind five interfaces — that's the whole integration surface.
LlmProviderstreaming chat + tool calls; provider protocols never leak past this portTelemetrySourcelogs & metrics queries; sources describe themselves into the promptToolSourcestandard tools, whitelisted shell, or any MCP serverRunStorebatched, block-paired trajectory persistence with terminal outcomesMemoryStorelesson record & retrievalanthropic providerGLM / Claude-style endpointsPG telemetrybuilt-in collector: docker logs & stats, host metricsdocker toolsread-only whitelisted host forensicsPG run storeagent_messages with structured blocksalert enginerule evaluation → incidents → auto-investigate → auto-recoverFull stack: PostgreSQL, Redis, collector, alert engine, investigation agent, web console.
git clone https://github.com/Joshwong1908/relionaut.git cd relionaut echo 'GLM_API_KEY=your-key' >> .env docker compose up -d --build # open http://localhost:8082 — telemetry flows in 30s
Vendor the kernel directory, implement the ports you need, run an investigation.
import { createAgent, openaiProvider,
staticTools, telemetryTools,
inMemoryRunStore } from './agent-core/mod.ts';
const agent = createAgent({ llm: openaiProvider({ baseUrl: 'http://llm.internal:11434/v1', model: 'qwen3:32b' }), tools: [staticTools(...telemetryTools(myTelemetry))], store: inMemoryRunStore(), system: { / role, environment, output format / }, }); for await (const ev of agent.run({ runId, input })) { / SSE events / } ```
Open-source SRE agents cluster on an autonomy spectrum. Relionaut ships as a read-only investigator by default — the red line is structural — with the interface reserved for approved remediation as trust grows.
Deterministic analyzers, LLM explains findings.
Read-only investigator: ReAct loop, dynamic tool choice, read-only by design.
Interface reserved (advise mode).
Interface reserved (approve-write + Approval).