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Doca Telemetry Exporter

NVIDIAOfficialCreated by NVIDIA

  • Skill
  • Tool integration
  • Software development
  • Apache-2.0
  • Medium risk
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From the author

Use this skill when the user is doing hands-on DOCA Telemetry Exporter programming on a host where DOCA is installed — defining a doca_telemetry_exporter_schema and event types, creating sources, picking a publish surface (typed events / opaque events / the metrics counter-gauge-histogram API / OTLP logs / NetFlow), walking the schema-then-source lifecycle, or debugging DOCA_ERROR_* failures from the exporter API. Trigger even when the user does not explicitly mention "DOCA Telemetry Exporter" or "doca_telemetry_exporter_*" — typical implicit phrasings include "publishing counters from my DOCA app", "BAD_STATE when I report an event", "consumer/DTS sees nothing but my report succeeded", "how do I export NetFlow/IPFIX records", or "should I link the exporter or the telemetry service". Refuse and route elsewhere for the receiving DOCA Telemetry Service (DTS), plain stdout logging via doca_log, or real-time event subscription back into the app via doca-comch — those belong to other skills.
— the description by NVIDIA

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides technical guidance for developers using the DOCA Telemetry Exporter library to publish structured telemetry data—such as counters, gauges, and events—from a DOCA-enabled application to an external consumer. It covers the schema-to-source lifecycle, selection of publish surfaces (including Metrics API, OTLP, and NetFlow), and debugging common runtime errors. It is strictly focused on the publisher side and does not cover the receiving DOCA Telemetry Service or general DOCA installation.

What it does

  • Defines the schema-to-source lifecycle for telemetry emission.
  • Assists in selecting appropriate publish surfaces like Metrics, OTLP, or NetFlow.
  • Provides debugging strategies for DOCA_ERROR_* codes specific to the exporter.
  • Clarifies the distinction between the exporter library and the receiving telemetry service.
  • Guides users on verifying IPC transport liveness and exporter configuration.
  • Supports integration of the C ABI into custom application code or language bindings.

When to use it

  • When you need to emit structured telemetry from a DOCA application.
  • When you encounter errors like DOCA_ERROR_BAD_STATE during report calls.
  • When you are unsure whether to use the exporter library or the telemetry service.
  • When you need to implement specific publish surfaces like counters or opaque events.
  • When you need to verify if the exporter is correctly installed and connected to a transport.

Advantages

  • Provides a clear, structured workflow for the exporter lifecycle.
  • Helps avoid common pitfalls like incorrect initialization order.
  • Distinguishes clearly between publisher and consumer responsibilities.
  • Offers specific guidance on mapping application intent to publish surfaces.
  • Integrates with standard DOCA debugging and versioning practices.

Usage examples

“How do I emit a packets_processed event record from my DOCA Flow application?”
The agent will guide you through the schema definition, source creation, and the report call sequence required to emit structured events.
“My report call returns DOCA_ERROR_BAD_STATE on the first call, what is wrong?”
The agent will help you verify the lifecycle order, ensuring the source was properly started and the OTLP context is initialized before reporting.
“I want to publish per-interface packet counters and a bandwidth gauge, which API should I use?”
The agent will direct you to the Metrics API and provide the necessary steps to implement counter and gauge reporting.
“My report returns success, but the collector sees nothing. Where do I start?”
The agent will walk you through verifying the receiver status, checking IPC connectivity, and performing a file-write smoke test to isolate the issue.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/nvidia/doca-telemetry-exporter/download

  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip doca-telemetry-exporter.zip -d .agents/skills

Documentation by NVIDIA

DOCA Telemetry Exporter

Examples

  • "Publishing counters from my DOCA app." — this is in scope. Walk schema-then-source; do not configure DTS here.

  • "BAD_STATE when I report an event." — check the lifecycle order before changing the report call.

Instructions

Follow Loading order below. Open the tasks companion for configure / publish / debug. Open the capabilities companion for publish surfaces. Do not open every companion file.

Where to start: This skill assumes DOCA is already installed and the user is doing hands-on telemetry-exporter work — emitting structured application telemetry (counters / events) from a DOCA-using program to an external consumer. Open the tasks companion if the user wants to do something (configure / build / modify + rebuild / run / test / debug); open the capabilities companion when the question is what can the exporter express on this install. If the user has not installed DOCA yet, route to doca-setup/SKILL.md first. If the user is confused about whether they want this library or the DOCA Telemetry Service (the receiver) — read the exporter-vs-service rule in the capabilities companion before configuring anything.

This library is NOT a DOCA Core context. There is no doca_ctx_start() for the exporter and no per-doca_devinfo capability-query family (its doca_caps dump is a stub). The lifecycle is schema_init → configure exporters → register type(s) → schema_start → source_create → source_start → report → flush → destroy.

Example questions this skill answers well

The CLASSES of telemetry-exporter questions this skill is built to answer, each with one worked example. The agent should treat the class as the load-bearing piece — the worked example is a single instance.

  • "Which library do I want — the exporter or the telemetry service?" — worked example: "I want my DOCA Flow program to publish a per-second packets-processed counter to a downstream collector — which DOCA artifact do I link?". Answered by the exporter-vs-service rule in

    Capabilities and modes

    role-split table + the path-selection bullet, both of which name doca-telemetry-exporter as the publisher the application links and route the receiving / consuming side away from this skill.

  • "How do I emit my first structured event from a DOCA program?" — worked example: "emit a packets_processed event record from my DOCA Flow application". Answered by the schema → source lifecycle in

    Capabilities and modes

    object table + the workflow in

    configure +

    run step 3 (file-write smoke before

    bulk), starting from the telemetry_export/ sample.

  • "Which publish surface do I want — typed events, metrics, OTLP logs, or NetFlow?" — worked example: "I want labeled per-interface packet counters and a bandwidth gauge". Answered by the publish-surface table in

    Capabilities and modes

    (that intent maps to the Metrics API — _metrics_add_counter / _add_gauge — and the telemetry_export_metrics/ sample), plus the sample map in ## modify.

  • "My report call returns DOCA_ERROR_BAD_STATE — what did I get wrong?" — worked example: "doca_telemetry_exporter_source_report returns BAD_STATE on the first call". Answered by the BAD_STATE row in

    Error taxonomy

    (the source was never started, or an OTLP context is missing on write/flush) + the lifecycle order in

    configure. Note there is NO

    DOCA_ERROR_AGAIN and NO DOCA_ERROR_NOT_FOUND on this API.

  • "My program reports, but the DTS / collector sees nothing — where do I start?" — worked example: "my report returns success, but the DTS log is empty". Answered by the receiver-up-first staging in

    Safety policy

    • the file-write smoke and check_ipc_status steps in

    test (prove the publish half with

    file write, then confirm IPC is CONNECTED and the receiver is up).

  • "How do I confirm the exporter is installed and my transport is live?" — worked example: "is the exporter on my DOCA 3.x install, and is IPC to DTS actually connected?". Answered by the version-compatibility overlay in

    Version compatibility

    (cross-linking the detection chain in doca-version/SKILL.md) plus the honest introspection rule in

    Capabilities and modes

    (doca_telemetry_exporter_check_ipc_status, not a device cap-query).

Audience

This skill serves external developers building applications that emit structured telemetry through DOCA Telemetry Exporter — i.e., users whose application code calls doca_telemetry_exporter_* (directly in C/C++, or through FFI/bindings from another language) to publish counters, gauges, and events from their DOCA-using program to an external telemetry consumer. It is not for NVIDIA developers contributing to DOCA Telemetry Exporter itself, and it is not for users building the receiving / aggregating telemetry service (the DOCA Telemetry Service is a separate DOCA service with its own public guide, reached via doca-public-knowledge-map/SKILL.md).

Language scope. DOCA Telemetry Exporter ships as a C library with pkg-config module name doca-telemetry-exporter. The shipped samples are written in C. C and C++ consumers are the canonical case; the worked examples in the tasks companion assume that path. Other-language consumers (Rust, Go, Python, …) consume the same *.so through FFI or language-specific bindings; the skill's contribution in that case is to keep the exporter-vs-service distinction, the schema → source lifecycle, the transport-not-caps discovery rule, the same-user-as-the-app permission rule, the buffered flush-based delivery model, and the error-taxonomy guidance language-neutral, and to route the agent to the public C ABI as the authoritative surface that any wrapper will eventually call.

When to load this skill

Load this skill when the user is doing hands-on DOCA Telemetry Exporter work, in any language. Concretely:

  • Defining a doca_telemetry_exporter_schema for the events the application will emit (field names + field types), and registering it with the exporter BEFORE any event is published.

  • Creating one or more doca_telemetry_exporter_source instances to represent distinct logical sources of telemetry inside the application (e.g. one source per worker thread / per pipeline stage).

  • Picking the right publish surface — typed structured events (_source_report), opaque events (_source_opaque_report), the Metrics API (counter / gauge / histogram), OTLP logs, or the NetFlow sibling API — for what the application reports.

  • Confirming the exporter's install + transport reality (there is NO doca_devinfo cap-query family and NO doca_caps data for this library): doca_telemetry_exporter_check_ipc_status for IPC liveness, _source_get_opaque_report_max_data_size for the opaque payload bound, and the _schema_get_* config getters.

  • Debugging a DOCA_ERROR_* returned from an exporter call (BAD_STATE lifecycle-order vs. INVALID_VALUE type/label mismatch vs. NO_MEMORY vs. INITIALIZATION vs. UNKNOWN backend) and the per-call status returned to the application.

  • Choosing between Telemetry Exporter and an adjacent option (doca_log when stdout / structured-log shipping is enough; a Prometheus client library when the user needs a non-DOCA-aware sink; doca-comch/SKILL.md when the user needs a real-time event subscription back INTO the app — the exporter is publish-only / one-way).

  • Designing or extending non-C bindings (Rust, Go, Python, …) that wrap the exporter C ABI — for the exporter-vs-service distinction, the schema → source lifecycle, the permission policy, the buffered flush-based delivery model, and the transport-introspection + error rules the wrapper must honor.

Do not load this skill for general DOCA orientation, install of DOCA itself, the receiving telemetry service (the DOCA Telemetry Service has its own public guide reachable through doca-public-knowledge-map/SKILL.md), or non-exporter library questions. For those, use doca-public-knowledge-map/SKILL.md.

What this skill provides

This is a thin loader. The body keeps only the orientation needed to pick the right next file. The substantive exporter-specific material lives in two companion files:

  • the capabilities companion — what the exporter can express on this install: the exporter-vs-service role-split rule, the object family (doca_telemetry_exporter_schema → _type/_field → _source with the schema → source lifecycle), the four publish surfaces (typed events / opaque events / Metrics API / OTLP logs) plus the NetFlow sibling API, the transport-not-caps introspection rule (check_ipc_status, _get_opaque_report_max_data_size, _schema_get_* — NO doca_caps data, NO device cap-query), the exporter error taxonomy (mapped onto the cross-library DOCA_ERROR_* set, with the note that there is NO AGAIN and NO NOT_FOUND on this surface), the observability surface (per-call status + IPC status + file-write inspection + the receiver side as the end-to-end signal), the safety policy that gates the same-user-as-the-app permission and the receiver-up-first staging, and the path-selection rule against doca_log and doca-comch.

  • the tasks companion — step-by-step workflows for the six in-scope exporter verbs: configure, build, modify (followed by a rebuild), run, test, debug. Plus a Deferred task verbs block that points out-of-scope questions at the right next skill.

The skill assumes a host where DOCA is already installed at the standard location, the application runs as a user that can write to the telemetry transport the exporter is configured for, and a receiving telemetry consumer is reachable and started before the exporter. It does not cover installing DOCA — that path goes through doca-setup/SKILL.md — and it does not cover configuring / operating the receiving telemetry service, which is a separate DOCA service with its own public guide.

What this skill deliberately does not ship

This skill is agent guidance, not a samples or templates bundle. To keep the boundary clean, it deliberately does not contain — and pull requests should not add:

  • Pre-written DOCA Telemetry Exporter application source code, in any language. The verified exporter source code is the shipped C samples at /opt/mellanox/doca/samples/doca_telemetry_exporter/. The agent's job is to route the user to those files and prescribe a minimum-diff modification on them via the universal modify-a-sample workflow in doca-programming-guide/SKILL.md, layered with the exporter-specific overrides in

    modify.

  • A telemetry consumer / collector / receiving service. The DOCA Telemetry Service is a separate DOCA service with its own public guide; routing to it goes through doca-public-knowledge-map/SKILL.md. This skill is about the publisher side only.

  • Standalone build manifests (meson.build, CMakeLists.txt, Cargo.toml, …) parked inside the skill. The agent constructs the build manifest in the user's project directory against the user's installed DOCA, where pkg-config --modversion doca-telemetry-exporter is the source of truth.

  • A samples/, bindings/, or reference/ subtree of any kind. A mock or incomplete artifact in this skill's tree, even one labeled "reference", is misleading: users will read it as buildable.

Loading order

  1. Read this skill first to confirm the user's question is in scope.

  2. For the exporter-vs-service rule, the object family, the schema → source lifecycle, the four publish surfaces + NetFlow, the transport-not-caps introspection rule, the error taxonomy (note: no AGAIN, no NOT_FOUND), observability, the safety policy, and the path-selection rule against doca_log / comch, see the capabilities companion.

  3. For step-by-step workflows — configure, build, modify, rebuild, run, test, debug — see the tasks companion.

Both companion files cross-link to each other, doca-version/SKILL.md for the canonical version-handling rules, and doca-public-knowledge-map/SKILL.md whenever the right answer is "look it up in the public docs or the installed package layout" rather than "exporter-specific guidance".

Related skills

  • doca-public-knowledge-map/SKILL.md — the routing table for every public DOCA documentation source and the on-disk layout of an installed DOCA package. The exporter's public guide URL is https://docs.nvidia.com/doca/sdk/DOCA-Telemetry-Exporter/index.html; the on-disk samples live under /opt/mellanox/doca/samples/doca_telemetry_exporter/. The DOCA Telemetry Service (the receiver, out of scope here) is a separate guide reachable through that same routing table.

  • doca-setup/SKILL.md — env preparation, install verification, transport-side reachability checks, and the I have no install yet path with the public NGC DOCA container. This skill assumes its preconditions are satisfied (in particular, the application user can write to the telemetry transport).

  • doca-version/SKILL.md — canonical DOCA version-handling rules. This skill's ## Version compatibility cross-links the four-way match rule + detection chain and adds the exporter-specific overlay rules.

  • doca-structured-tools-contract/SKILL.md — the bundle's structured-tools precedence rule (detect / prefer / fall back / report). The Command appendix in the tasks companion honors this contract.

  • doca-programming-guide/SKILL.md — general DOCA programming patterns shared by every library: the canonical pkg-config + meson build pattern, the universal modify-a-shipped-sample first-app workflow, the universal lifecycle, the cross-library DOCA_ERROR_* taxonomy, and the program-side debug order. This skill layers exporter specifics on top.

  • doca-comch/SKILL.md — the right primitive when the user needs a real-time event subscription back INTO the application (host ↔ DPU control-plane messaging). The exporter is publish-only / one-way; this skill's path-selection rule routes there when subscription is the actual requirement.

  • doca-debug/SKILL.md — the cross-cutting debug ladder (install / version / build / link / runtime / program / driver). Exporter-specific debug (receiver not up, lifecycle-order BAD_STATE, type/label INVALID_VALUE, opaque-path-not-enabled) overlays on top of that ladder.

Files

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Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

The author says: Requires DOCA SDK installed at /opt/mellanox/doca on Linux (Ubuntu 22.04/24.04 or RHEL/SLES) with a BlueField DPU or ConnectX NIC attached. Reads the user's local install via `pkg-config doca-telemetry-exporter` and inspects /opt/mellanox/doca/{lib,include,samples,applications}. The validation steps require a live DOCA install.

Security

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Attribution and licence

Created by
NVIDIA
Publisher
NVIDIA (Official)
Source
NVIDIA/skills · skills/doca-telemetry-exporter · commit fce3cca
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE-APACHE)
  • ATTRIBUTION.md (written by AutoGineer)
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