
Skill
doca-telemetry-exporter
program DOCA Telemetry Exporter on NVIDIA hardware
Description
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, creating sources, picking counter/gauge/event types, running capability queries before assuming limits, registering schemas before the first emit, 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", "emit returns AGAIN under bulk load", "consumer sees nothing but emit reports success", "NOT_FOUND on first submit", or "should I link the exporter or the telemetry service". Refuse and route elsewhere for the receiving DOCA Telemetry Service, plain stdout logging via doca_log, non-DOCA Prometheus scrape sinks, or real-time event subscription back into the app via doca-comch — those belong to other skills.
SKILL.md
DOCA Telemetry Exporter
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
TASKS.md if the user wants to do something (configure
/ build / modify / run / test / debug); open
CAPABILITIES.md when the question is what can
the exporter express on this install. If the user has not installed
DOCA yet, route to doca-setup 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
CAPABILITIES.md ## Capabilities and modes
before configuring anything.
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.md ## Capabilities and modesrole-split table + the path-selection bullet, both of which namedoca-telemetry-exporteras 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 single per-second
packets_processedcounter event from my DOCA Flow application". Answered by the schema-register-before-emit lifecycle inCAPABILITIES.md ## Capabilities and modesobject table + the workflow inTASKS.md ## configure+TASKS.md ## runstep 3 (single-event smoke before bulk). - "My event-emit call returns
DOCA_ERROR_AGAINunder load — should I retry?" — worked example: "my high-rate emit loop starts returningAGAINonce the downstream consumer falls behind — do I sleep-and-retry?". Answered by the hot-path drop-not-block invariant inCAPABILITIES.md ## Safety policy- the
AGAINrow inCAPABILITIES.md ## Error taxonomy: the app's correct response is to drop the event (or buffer bounded) — never block the data path on telemetry.
- the
- "My emit returns
DOCA_ERROR_NOT_FOUND— what did I forget?" — worked example: "doca_telemetry_exporter_source_reportreturnsNOT_FOUNDon the very first call". Answered by theNOT_FOUNDrow inCAPABILITIES.md ## Error taxonomy(schema for the event type was never registered against this source) + the lifecycle order inTASKS.md ## configure(register schemas BEFORE the first emit). - "My program emits, but the consumer sees nothing — where do I
start?" — worked example: "emit returns success, but the
collector log on the same host is empty". Answered by the
consumer-must-be-up-first rule in
CAPABILITIES.md ## Safety policypermission matrix + the smoke-before-bulk loop inTASKS.md ## test(one event end-to-end with consumer reception confirmed BEFORE any bulk emit). - "Is
doca_telemetry_exporter_*on my installed DOCA, and is the event type I want supported here?" — worked example: "is the gauge type on DOCA 3.3 against my install?". Answered by the version-compatibility overlay inCAPABILITIES.md ## Version compatibility, which cross-links the canonical detection chain indoca-version, plus the capability-query rule inCAPABILITIES.md ## Capabilities and modes.
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).
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 TASKS.md 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-register-before-emit lifecycle, the
capability-discovery rule, the same-user-as-the-app permission
rule, the hot-path drop-not-block invariant, 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_schemafor 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_sourceinstances to represent distinct logical sources of telemetry inside the application (e.g. one source per worker thread / per pipeline stage). - Picking the right
doca_telemetry_exporter_type(counter, gauge, event) for each field the application reports. - Reading the device + library capability surface for the
exporter via the
doca_telemetry_exporter_*_get_*query family before assuming a particular limit (max schema fields, max event size, …) is available on this install. - Debugging a
DOCA_ERROR_*returned from an exporter call (lifecycle vs. invalid value vs. transport-queue-full vs. permission vs. transport / driver) and the per-emit status reported back to the application. - Choosing between Telemetry Exporter and an adjacent option
(
doca_logwhen stdout / structured-log shipping is enough; a Prometheus client library when the user needs a non-DOCA-aware sink;doca-comchwhen 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-register-before-emit lifecycle, the permission policy, the hot-path drop-not-block invariant, and the capability + 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),
or non-exporter library questions. For those, use
doca-public-knowledge-map.
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:
CAPABILITIES.md— what the exporter can express on this install: the exporter-vs-service role-split rule, the object family (doca_telemetry_exporter_schema→_source→_typewith the schema-register-before-emit lifecycle), the capability-query surface (doca_telemetry_exporter_*_get_*), the exporter error taxonomy (mapped onto the cross-libraryDOCA_ERROR_*set, with theAGAIN-means-drop-not-block rule called out explicitly), the observability surface (per-emit status + capability snapshot at configure time + the consumer side as the end-to-end signal), the safety policy that gates the same-user-as-the-app permission and the consumer-must-be-up-first staging, and the path-selection rule againstdoca_log, Prometheus, anddoca-comch.TASKS.md— step-by-step workflows for the six in-scope exporter verbs:configure,build,modify,run,test,debug. Plus aDeferred task verbsblock 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 — 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 indoca-programming-guide, layered with the exporter-specific overrides inTASKS.md ## 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. 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, wherepkg-config --modversion doca-telemetry-exporteris the source of truth. - A
samples/,bindings/, orreference/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
- Read this
SKILL.mdfirst to confirm the user's question is in scope. - For the exporter-vs-service rule, the object family, the
schema-register-before-emit lifecycle, the capability-query
surface, the error taxonomy (including the
AGAIN-means-drop rule), observability, the safety policy, and the path-selection rule againstdoca_log/ Prometheus / comch, see CAPABILITIES.md. - For step-by-step workflows — configure, build, modify, run, test, debug — see TASKS.md.
Both companion files cross-link to each other,
doca-version for the canonical
version-handling rules, and
doca-public-knowledge-map
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— 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 ishttps://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— 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— canonical DOCA version-handling rules. This skill's## Version compatibilitycross-links the four-way match rule + detection chain and adds the exporter-specific overlay rules.doca-structured-tools-contract— the bundle's structured-tools precedence rule (detect / prefer / fall back / report). The Command appendix in TASKS.md honors this contract.doca-programming-guide— general DOCA programming patterns shared by every library: the canonicalpkg-config+ meson build pattern, the universal modify-a-shipped-sample first-app workflow, the universal lifecycle, the cross-libraryDOCA_ERROR_*taxonomy, and the program-side debug order. This skill layers exporter specifics on top.doca-comch— 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— the cross-cutting debug ladder (install / version / build / link / runtime / program / driver). Exporter-specific debug (consumer not up, schema-not-registered, transport queue full, hot-path block) overlays on top of that ladder.
More skills from the skills repository
View all 305 skillsaccelerated-computing-cudf
accelerate data processing with cuDF
Jul 14Data AnalysisData EngineeringNVIDIAPerformanceaiq-deploy
deploy and manage NVIDIA AI-Q infrastructure
Jul 14DeploymentInfrastructureNVIDIAaiq-research
conduct deep research with AI-Q
Jul 14AgentsNVIDIAResearchamc-run-sample-calibration
run AMC sample dataset calibration
Jul 17Data AnalysisNVIDIATestingamc-run-video-calibration
calibrate video datasets with AutoMagicCalib
Jul 17AutomationImagingNVIDIAVideoamc-setup-calibration-stack
deploy AutoMagicCalib microservice with Docker
Jul 17DeploymentDockerNVIDIAOperations
More from NVIDIA
View publishernemoclaw-user-guide
retrieve NemoClaw documentation and configuration
NemoClaw
Jul 20DocumentationMCPSearchmcore-build-and-dependency
manage Megatron-LM development environments
Megatron-LM
Jul 14ContainersDeploymentPythonmcore-bump-base-image
update NVIDIA PyTorch base images
Megatron-LM
Jul 14CI/CDDeploymentmcore-cicd
manage CI/CD pipelines for Megatron-LM
Megatron-LM
Jul 14CI/CDDeploymentGitHubmcore-create-issue
investigate CI failures and create issues
Megatron-LM
Jul 14DebuggingGitHubTriagemcore-linting-and-formatting
lint and format Megatron-LM code
Megatron-LM
Jul 14Best PracticesCode Analysis