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Otel Profiles

Organization
ollygarden
otel-profiles

OpenTelemetry profiles signal and the eBPF profiler (otelcol-ebpf-profiler, `profiling` receiver). Use when setting up continuous profiling with OpenTelemetry, deploying the eBPF profiler on Linux hosts, Docker, or Kubernetes (DaemonSet, kind, k3d), building a profiles pipeline, sending OTLP profiles to Pyroscope, Grafana Cloud Profiles, or another backend, getting flame graphs from OTel, enabling off-CPU profiling, or debugging profiler errors about tracefs, PID namespaces, missing pods, or the service.profilesSupport feature gate. Not for SDK tracing or metrics setup.

Overview

Publisherollygarden
Repositoryopentelemetry-agent-skills
Skill nameotel-profiles
Stars
119
Forks
13
Bundled files
6
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.

  • 6 bundled files

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

  • Open source

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

Installation

Install the Otel Profiles 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/ollygarden/opentelemetry-agent-skills/tree/main/skills/otel-profiles
  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/ollygarden/opentelemetry-agent-skills.git /tmp/opentelemetry-agent-skills
mkdir -p .claude/skills
cp -r /tmp/opentelemetry-agent-skills/skills/otel-profiles .claude/skills/otel-profiles
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Otel Profiles 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 Otel Profiles 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 Otel Profiles 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.

OpenTelemetry Profiles

The main OpenTelemetry producer is the eBPF profiler, shipped as the profiling receiver in the otelcol-ebpf-profiler Collector distribution. It profiles every process on a Linux host with no application changes.

Maturity: the signal entered public Alpha in March 2026, the OTLP profiles proto (v1development) is Development, the profiling receiver is Development, and the Collector gate service.profilesSupport is alpha. Expect breaking changes; pin the profiler, Collector, and backend versions together.

Collector-side component facts (OTLP receiver/exporter profile support, the fixed /v1development/profiles HTTP path, k8s_attributes, memory_limiter, filter profile_conditions) live in the otel-collector skill's component pages; OTTL profile/profilesample contexts live in otel-ottl.

otelcol-ebpf-profiler 0.163.2 bundles only: receivers profiling, nop; processors memory_limiter, k8s_attributes, resource_detection, resource, transform (plus batch, which does not support profiles); exporters otlp_grpc, otlp_http, debug, file, nop; extensions health_check, pprof, opamp, offcpu. For anything else (filter, the basicauth extension, vendor exporters), relay to a regular Collector or build a distribution (otel-collector-builder skill).

Version matrix (Verified 2026-10-25)

ArtifactVersionWhat it means
otel/opentelemetry-collector-ebpf-profiler0.163.0, 0.163.1, 0.163.2 (newest release at verification, 2026-10-21)Pins ebpf-profiler v0.0.202640: pid_namespace_translation_mode (#1801); bundles the offcpu extension. Components unchanged from 0.163.0.
Same image, 0.162.0last release before the changePins ebpf-profiler v0.0.202636: boolean pid_namespace_translation; does not bundle offcpu.

Evidence: Docker Hub tags, the v0.163.0, v0.163.1, and v0.163.2 distribution manifests; the v0.163.2 changelog.

Read references/receiver.md when setting keys beyond samples_per_second, enabling off-CPU or OBI correlation, or pinning a release not in this table (keys follow the pinned ebpf-profiler, not the Collector version).

Workflow

  1. Pick the image and pin. Use the latest release unless a needed key or component is missing from it (see the matrix). Alternative: an OCB build (otel-collector-builder skill) based on the distribution manifest.
  2. Pick the environment.
  3. Wire the pipeline. profiles pipeline: profiling receiver, memory_limiter first, enrichment processors, then otlp_grpc or otlp_http. Start the Collector with --feature-gates=+service.profilesSupport. Run validate --config=<file> --feature-gates=+service.profilesSupport with the target image; it catches wrong keys for the pinned version.
  4. Export and verify. Add debug (verbosity: basic) first: each reporter_interval it logs "resource profiles": N, "sample records": M; no lines or zero counts mean the receiver is not producing (see troubleshooting). verbosity: detailed shows resource attributes. Then add the backend: references/backends.md for endpoints, auth, and per-backend label behavior.
  5. Troubleshoot by exact error string: references/troubleshooting.md.

Run on a host

The profiler needs root or CAP_SYS_ADMIN/CAP_BPF/CAP_PERFMON, the host PID namespace, and a mounted tracefs. A container gets a fresh /sys without tracefs even when privileged, so bind-mount it:

bash
docker run -d --name otel-ebpf-profiler --privileged --pid=host \
  -v /sys/kernel/tracing:/sys/kernel/tracing \
  -v "$PWD/config.yaml:/etc/otelcol/config.yaml:ro" \
  otel/opentelemetry-collector-ebpf-profiler:0.163.2 \
  --config=/etc/otelcol/config.yaml --feature-gates=+service.profilesSupport
yaml
receivers:
  profiling:
    samples_per_second: 20      # default
processors:
  memory_limiter:
    check_interval: 1s
    limit_mib: 800
    spike_limit_mib: 200
exporters:
  debug:
    verbosity: basic
  otlp_grpc:
    endpoint: profiles-backend:4317   # backend-specific, see references/backends.md
    tls:
      insecure: true
service:
  pipelines:
    profiles:
      receivers: [profiling]
      processors: [memory_limiter]
      exporters: [otlp_grpc, debug]

The image is built FROM scratch: no shell, so debug from logs, not exec. Expected startup lines: eBPF tracer loaded, Attached sched monitor, Everything is ready.

Known limitations

  • The receiver profiles every process; it has no process, container, or namespace selection, and upstream declined to add one (#358). To keep a subset, filter on enrichment attributes with filter profile_conditions; see "Keep only some workloads" in references/kubernetes.md. Sampling cost on the node stays the same; only exported volume drops.
  • Linux amd64/arm64, kernel 5.10+ (checked at config validation; no_kernel_version_check bypasses it). Backends may lag the proto; check which OTLP profiles version they accept.
  • Trace-to-profile correlation is partial: OTLP profiles can link samples to trace_id/span_id, but the profiler fills them only from a context producer (OBI via obi_process_ctx; the thread-context OTEP is accepted, but the receiver's thread_context support in v0.0.202640 is a stub). Go pprof labels are read as custom labels.

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 Otel Profiles AI skill do?

OpenTelemetry profiles signal and the eBPF profiler (otelcol-ebpf-profiler, `profiling` receiver). Use when setting up continuous profiling with OpenTelemetry, deploying the eBPF profiler on Linux hosts, Docker, or Kubernetes (DaemonSet, kind, k3d), building a profiles pipeline, sending OTLP profiles to Pyroscope, Grafana Cloud Profiles, or another backend, getting flame graphs from OTel, enabling off-CPU profiling, or debugging profiler errors about tracefs, PID namespaces, missing pods, or the service.profilesSupport feature gate. Not for SDK tracing or metrics setup.

Why use Otel Profiles on TypingMind?

Because you install it once and use it with any model. Otel Profiles 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 Otel Profiles in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ollygarden/opentelemetry-agent-skills/tree/main/skills/otel-profiles. 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 Otel Profiles?

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 Otel Profiles?

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

Is the Otel Profiles AI skill free?

Yes. It is published on GitHub by ollygarden 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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