Fanout

io.github.labstack由 GitHub 帳號 labstack 發布v2026.11.2-alpha更新於 Nov 7, 2026

Investigate OpenTelemetry traces, metrics, and logs, and manage personal dashboards.

已驗證Streamable HTTP可網頁執行安全與監控資料與分析

概覽

AI 產生的概覽

Fanout 是自架的觀測性伺服器,其 MCP 端點讓助理查詢 OpenTelemetry 的追蹤、日誌與指標,並管理個人儀表板。

可以做什麼
  • 查詢遙測資料:用與內建代理相同的型別化查詢工具調查追蹤、日誌與指標。
  • 不需 AI 供應商即可用 Explore 與 FanQL 查詢遙測。
  • 檢視涵蓋追蹤、日誌與指標的儀表板,以及錯誤率、延遲、吞吐量與日誌量的告警。
  • 設定 AI 供應商後,以自然語言提問並取得關於遙測的回答。
適用情境
當你已將 OpenTelemetry 資料送到自架的 Fanout 執行個體,並希望外部代理透過 MCP 調查事故、執行查詢與讀取儀表板,而不必在介面中逐項點選時使用。
執行需求
需要一個可透過 HTTPS 存取的執行中 Fanout 執行個體,並將 FANOUT_PUBLIC_URL 設為其穩定來源;MCP 用戶端連線至該來源的 /mcp 端點,透過 OAuth 註冊並在瀏覽器中授權作用域。Fanout 本身需要 FANOUT_AUTH_CODE_SECRET,啟用聊天還需 AI 供應商金鑰。
安裝前請注意
Fanout 處於預覽 alpha 階段,變更不提供移轉路徑;MCP 工具、儀表板與告警皆為預覽功能。你核准的 OAuth 作用域會讓用戶端存取遙測資料,請仔細核對。聊天會將遙測問題傳送給所設定的 Anthropic 或 OpenAI 供應商。擷取權杖只顯示一次,應以密鑰方式保存。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Fanout,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

Fanout

Observability your agents can operate. Send OpenTelemetry to one binary, then investigate with Fanout's built-in agent or connect your own over MCP.

[CI] [License: Apache 2.0] [Go Reference]

[A Fanout dashboard the built-in agent built from one request: store request rate, error rate, p95 latency and error logs, with request and error rates by service.]

Fanout keeps OpenTelemetry traces, logs, and metrics in one binary and one data directory, with no external storage services to operate. Fanout is pre-release and changes without migration paths; the browser client, built-in agent, MCP tools, dashboards, and alerts are preview capabilities (status). Start with the documentation or run it below.

  • OTLP ingest over gRPC and HTTP, with local Parquet storage and DuckDB analytics.
  • Explore and FanQL for querying telemetry without an AI provider.
  • An investigation agent that answers questions about your telemetry in plain language.
  • An MCP server for external agents using the same typed query tools.
  • Dashboards across traces, logs, and metrics, and alerts on service error rate, latency, throughput, and log volume.

Quick start

Docker

sh
docker run --name fanout --restart unless-stopped -p 7520:7520 \  -v fanout-data:/var/lib/fanout/data \  -e FANOUT_AUTH_CODE_SECRET=$(openssl rand -hex 32) \  labstack/fanout:latest

Open the one-time setup URL printed by the container and create the first administrator. Fanout displays the ingest token exactly once; save it with your collector secrets. For later sign-in without SMTP, mint a 15-minute, single-use link against the running container's control database:

sh
docker exec fanout fanout login-link [email protected]

The UI, API, MCP, and both OTLP transports share port 7520. See installation for image defaults and bind-mount ownership, and first boot for setup and SMTP login.

Native binary

Install a checksum-verified release for Linux or macOS, amd64 or arm64:

sh
curl -fsSL https://raw.githubusercontent.com/labstack/fanout/main/scripts/install.sh | shexport FANOUT_AUTH_CODE_SECRET=$(openssl rand -hex 32)fanout

Set FANOUT_VERSION to a release tag, such as v2026.11.0-alpha, to pin a release, and FANOUT_PREFIX to choose the installation directory. Native installs bind 127.0.0.1:7520; set FANOUT_ADDR=:7520 for remote access, then follow the same first-boot setup.

Send telemetry

A standard OTLP/HTTP exporter can use the saved ingest token:

sh
export OTEL_EXPORTER_OTLP_PROTOCOL=http/protobufexport OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:7520export OTEL_EXPORTER_OTLP_HEADERS="authorization=Bearer%20$INGEST_TOKEN"

For a Collector on the same private container network, the forwarding side is:

yaml
exporters:  otlp_http/fanout:    endpoint: http://fanout:7520    headers:      Authorization: "Bearer ${env:INGEST_TOKEN}"
service:  pipelines:    traces:  { receivers: [otlp], exporters: [otlp_http/fanout] }    metrics: { receivers: [otlp], exporters: [otlp_http/fanout] }    logs:    { receivers: [otlp], exporters: [otlp_http/fanout] }

Use an existing otlp receiver, set INGEST_TOKEN, and replace fanout with the Collector's reachable private hostname. OTLP/gRPC uses localhost:7520 locally; see send telemetry for TLS and HTTP/2 setup.

Enable chat

Select FANOUT_AI_PROVIDER=anthropic and inject ANTHROPIC_API_KEY, or select FANOUT_AI_PROVIDER=openai and inject OPENAI_API_KEY, then restart Fanout; the selected provider requires its key at startup. With no provider, chat is disabled and the other features still work. See AI settings.

Connect an MCP client

Set FANOUT_PUBLIC_URL to your stable, externally reachable HTTPS origin, then point a remote MCP client at that origin's /mcp endpoint. The client discovers and registers through OAuth; you authorize its scopes in the browser. Fanout serves MCP 2026-07-28 and, through the initialize handshake, 2025-11-25 and 2025-06-18 over Streamable HTTP. See connect over MCP for setup and permissions.

How it compares

If you useWhere Fanout differs
Grafana with Loki, Tempo, and MimirThat stack keeps a service and a query language per signal, plus object storage underneath. Fanout keeps one process, one data directory, and one typed contract across all three signals, at the cost of the horizontal scale those components are built for.
SigNozBoth are OTLP-native and self-hosted. SigNoz composes a collector, ClickHouse, and query services; Fanout compiles ingest, authoritative Parquet storage, indexed trace reads, DuckDB analytics, alerting, and the browser client into one binary.
JaegerJaeger covers traces and expects a storage backend you run separately. Fanout ingests traces, logs, and metrics into the same store, with nothing else to deploy.
Prometheus with GrafanaPrometheus pulls metrics and is excellent at them. Fanout accepts pushed OTLP for all three signals and is built around investigating a specific incident rather than maintaining long-range metric series.
Datadog, Honeycomb, Grafana CloudThose are managed services: someone else runs the storage, the scaling, and the upgrades, and your telemetry leaves your network to get there. Fanout is a binary you run, on data that stays on your disk.
An OpenTelemetry Collector piped into ClickHouseThe same shape, assembled by hand: collector, database, dashboards, and the glue between them. Fanout is that assembly as one program, with an agent and an MCP server already wired to the same query contract.

Fanout is a single node. It has no clustering, no replication, and no object tier; a deployment that outgrows one machine's disk and CPU has outgrown Fanout.

Architecture

One process contains ingest, storage, query, alerts, the agent, MCP, and the React client. Browser and agent clients share a typed observability contract.

[Fanout runtime architecture: OTLP ingest and commit workers publish Parquet; the browser API, agent runtime, and MCP server share queries and dashboards, with DuckDB query state, SQLite control state, anomaly detection, and webhook alerts.]

Parquet holds telemetry, DuckDB query state is rebuildable, and SQLite holds transactional product state. See how storage works for durable ingest, indexed reads, and compaction while reads continue.

[Telemetry durability and query flow: authenticated OTLP rows pass through group admission, parallel commit workers, and durable publication into immutable Parquet batches; indexed trace reads, DuckDB SQL, retention, and compaction use those batches, while service and edge rollups populate rebuildable query state.]

Configuration

Configuration is environment-only: built-in defaults followed by nonempty process environment values, validated before data files or listeners open. Settings are read once at startup; every change requires a restart.

Environment variableDefaultPurpose
FANOUT_ADDR127.0.0.1:7520UI, API, MCP, and both OTLP transports
FANOUT_DATA_DIR./dataParquet, query state, and control SQLite
FANOUT_AUTH_MODElocalLogin link or SMTP, or oidc
FANOUT_AUTH_CODE_SECRET—Required in local mode, 32+ characters
FANOUT_AI_PROVIDER—Empty disables chat; anthropic or openai enables it
ANTHROPIC_API_KEY—Required for Anthropic chat
OPENAI_API_KEY—Required for OpenAI chat
FANOUT_RETENTION_DAYS30Telemetry retention window
FANOUT_MCP_ENABLEDtrueServe the MCP endpoint at /mcp

Every secret accepts <NAME>_FILE instead of its value; see the settings reference for validation and runtime secret delivery for deployment examples.

Advanced DuckDB sizing

Fanout sizes DuckDB automatically; measured workloads can override memory, connections, and threads as described in DuckDB sizing.

For TLS, health checks, backups, upgrades, retention, and recovery, see the operator runbook.

Performance

Fanout v2026.11.0-alpha accepted 507,311 mixed OpenTelemetry items/s over 306.8 seconds on a Hetzner Cloud ccx33 (8 dedicated vCPUs, 32 GB RAM), with telemetrygen on a separate ccx33. The ingest run on 6 November 2026 passed every quality gate. See the performance methodology. Fanout Bench reproduces the measurement on your hardware.

Build from source

  • Go 1.27.3 and a C/C++ toolchain on native Linux or macOS, amd64 or arm64. Build with just build or bash scripts/with-duckdb.sh go build ./cmd/fanout; the wrapper supplies DuckDB's pinned headers, static libraries, and CGO flags. The first build needs network access to download the checksum-verified engine.
  • Bun — compiles the browser assets
  • Node.js 24.19.0 — runs development helpers and builds the documentation site
  • just — task runner
  • A 32-character authentication code secret
sh
git clone https://github.com/labstack/fanout.gitcd fanoutjust install   # browser dependencies and git hooksjust build     # browser assets, then the binary

Run it with the minimum configuration:

sh
export FANOUT_AUTH_CODE_SECRET=$(openssl rand -hex 32) # must be 32+ characters
./bin/fanout

Open http://localhost:7520 and follow first-boot setup. SMTP and chat are optional; without SMTP, run ./bin/fanout login-link [email protected] with the same configuration and data directory.

Development

Run just to list recipes, just check for the full gate, just test for Go tests, and just ui to rebuild embedded browser assets. See CONTRIBUTING.md for environment setup, generated assets, hooks, and project layout.

Releases

Versions are CalVer — vYYYY.M.N[-alpha|-beta|-rc], numbered from 0 within each month across all maturity suffixes. Fanout is alpha (for example, v2026.11.0-alpha); GA has no suffix. Container tags omit the leading v, and every release moves latest. Tagged releases publish identical manifests to Docker Hub (labstack/fanout) and GHCR (ghcr.io/labstack/fanout); GHCR is canonical and also carries development images.

Image tagPoints at
labstack/fanout:latestthe newest release, mirrored on Docker Hub
labstack/fanout:2026.11.0-alphathat exact release, mirrored on Docker Hub
ghcr.io/labstack/fanout:latestthe newest release
ghcr.io/labstack/fanout:2026.11.0-alphathat exact release
ghcr.io/labstack/fanout:mainthe tip of main
ghcr.io/labstack/fanout:sha-<commit>one specific commit

See docs/release.md for platforms, checksums, provenance, and verification.

Contributing

Issues and pull requests are welcome; follow CONTRIBUTING.md and run just check and just test-race before opening a pull request. Report security issues through SECURITY.md.

Scope

This repository builds Fanout without another repository; LabStack's deployment configuration, uptime monitoring, and public demo instance are not included. The documentation site in site/ is included, with settings pages generated from the same internal/config type the loader binds and checked by just check.

License

Apache-2.0 © LabStack LLC. See NOTICE and THIRD_PARTY_NOTICES for attribution, and TRADEMARK for use of the Fanout name and logo.

來源:README.md,提交 0b65468

工具

0
SourceWeft 尚未讀取此伺服器的工具。

版本歷史

23
  1. v2026.11.2-alpha最新Nov 7, 2026
  2. v2026.11.0-alphaNov 5, 2026
  3. v2026.10.24-alphaOct 30, 2026
  4. v2026.10.23-alphaOct 26, 2026
  5. v2026.10.22-alphaOct 22, 2026
  6. v2026.10.20-alphaOct 20, 2026
  7. v2026.10.19-alphaOct 19, 2026
  8. v2026.10.18-alphaOct 19, 2026
  9. v2026.10.16-alphaOct 19, 2026
  10. v2026.10.15-alphaOct 18, 2026
  11. v2026.10.13-alphaOct 18, 2026
  12. v2026.10.12-alphaOct 17, 2026
  13. v2026.10.11-alphaOct 17, 2026
  14. v2026.10.9-alphaOct 16, 2026
  15. v2026.10.7-alphaOct 16, 2026
  16. v2026.10.5-alphaOct 15, 2026
  17. v2026.10.4-alphaOct 15, 2026
  18. v2026.10.3-alphaOct 15, 2026
  19. v2026.10.1-alphaOct 15, 2026
  20. v2026.10.0Oct 11, 2026
  21. v2026.9.8Sep 22, 2026
  22. v2026.9.7Sep 21, 2026
  23. v2026.9.6Sep 16, 2026

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