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Beyla

Organization
grafana
beyla

Auto-instrument an application's HTTP / gRPC / DB traffic with Grafana Beyla eBPF — no code changes, no SDK, no restart. Covers requirements (Linux 5.8+ with BTF, CAP_SYS_ADMIN, host PID), language matrix (Go / Java / Python / Ruby / Node / .NET / Rust / C++ / PHP), Docker + Helm + DaemonSet install, port- / process- / Kubernetes-metadata discovery, OTLP traces + Prometheus metrics export, routes decorator (cardinality control), trace sampling, and Grafana Cloud via Alloy. Use when adding observability to a service you can't recompile, instrumenting a closed-source binary, getting RED metrics + spans onto Tempo/Mimir without touching the app, or rolling Beyla as a cluster-wide DaemonSet — even when the user says "zero-code APM", "instrument legacy app", "trace this binary", "eBPF observability", or "no SDK" without naming Beyla.

Overview

Publishergrafana
Repositoryskills
Skill namebeyla
Stars
289
Forks
27
Bundled files
2
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by grafana on GitHub. Read the source before you install it.

Installation

Install the Beyla AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/grafana/skills/tree/main/skills/grafana-core/beyla
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/grafana/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/grafana-core/beyla .claude/skills/beyla
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Beyla in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Beyla on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Beyla is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Grafana Beyla

Docs: https://grafana.com/docs/beyla/latest/

Zero-code HTTP / gRPC / DB instrumentation via eBPF. Emits OTLP traces + Prometheus metrics.

Prerequisites

  • Linux kernel 5.8+ with BTF enabled (ls /sys/kernel/btf/vmlinux must exist)
  • Root or CAP_SYS_ADMIN (or privileged: true in Kubernetes + hostPID: true)
  • x86_64 or ARM64
  • An OTLP receiver (Tempo, Alloy, OTel Collector) reachable from Beyla

Common Workflows

1. Instrument a single binary with Docker

bash
# 1. Run Beyla against the app's port (the app must already be running, listening on 8080)
docker run --privileged --pid=host \
  -v /sys/kernel/debug:/sys/kernel/debug:ro \
  -e BEYLA_OPEN_PORT=8080 \
  -e BEYLA_PROMETHEUS_PORT=8999 \
  -e OTEL_EXPORTER_OTLP_ENDPOINT=http://otel-collector:4318 \
  -p 8999:8999 \
  grafana/beyla

# 2. Generate some traffic
curl http://localhost:8080/ ; curl http://localhost:8080/api/users/42

# 3. Verify Beyla emitted metrics — should list http_server_request_duration_seconds + counters
curl -s http://localhost:8999/metrics | grep -E '^http_(server|client)_request_duration'

# 4. Verify traces — in Grafana Explore on Tempo, search by service.name (default = process name)
#    Or: query Tempo's search API for spans with service.name="<app>"

2. Deploy as a cluster-wide DaemonSet

Full DaemonSet + RBAC YAML lives in references/kubernetes.md. After applying:

bash
# 1. Verify DaemonSet rollout
kubectl -n monitoring rollout status ds/beyla

# 2. Verify pods are Running, one per node
kubectl -n monitoring get pods -l app=beyla -o wide

# 3. Verify eBPF probes attached (no errors mentioning BTF or "permission denied")
kubectl -n monitoring logs ds/beyla --tail=50 | grep -Ei 'error|fail|btf' || echo "clean"

# 4. Verify telemetry is flowing — check the Tempo/Alloy receiver for spans from the cluster
#    Or scrape one pod directly:
kubectl -n monitoring port-forward ds/beyla 8999:8999 &
curl -s localhost:8999/metrics | head

3. Send to Grafana Cloud via Alloy

yaml
# beyla-config.yml
otel_traces_export:  { endpoint: http://alloy:4318 }
otel_metrics_export: { endpoint: http://alloy:4318 }
bash
# Verify Alloy is forwarding — check Alloy UI (localhost:12345) for the
# otelcol.receiver.otlp.beyla component showing received spans/metrics > 0.

Full Alloy + Beyla YAML: references/config.md.

Troubleshooting

  • failed to load BPF object → kernel < 5.8 or BTF missing; check /sys/kernel/btf/vmlinux
  • No spans in Tempo, but Prometheus metrics show → check OTEL_EXPORTER_OTLP_ENDPOINT, protocol (http vs grpc), and ports (4318 http / 4317 grpc)
  • HTTP route cardinality explosion → set routes.unmatched: heuristic and add patterns (see references/config.md)
  • Pod restarts with CrashLoopBackOff → likely missing hostPID: true or privileged: true / required capabilities

Resources

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Beyla AI skill do?

Auto-instrument an application's HTTP / gRPC / DB traffic with Grafana Beyla eBPF — no code changes, no SDK, no restart. Covers requirements (Linux 5.8+ with BTF, CAP_SYS_ADMIN, host PID), language matrix (Go / Java / Python / Ruby / Node / .NET / Rust / C++ / PHP), Docker + Helm + DaemonSet install, port- / process- / Kubernetes-metadata discovery, OTLP traces + Prometheus metrics export, routes decorator (cardinality control), trace sampling, and Grafana Cloud via Alloy. Use when adding observability to a service you can't recompile, instrumenting a closed-source binary, getting RED metri...

Why use Beyla on TypingMind?

Because you install it once and use it with any model. Beyla is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Beyla in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/grafana/skills/tree/main/skills/grafana-core/beyla. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Beyla?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Beyla?

As many as you like. As long as a model supports skills, you can use Beyla with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Beyla AI skill free?

Yes. It is published on GitHub by grafana under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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