Official NVIDIA-authored guidance for NVIDIA cuDF GPU DataFrames, pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV/Parquet I/O, nullable semantics, and multi-GPU DataFrame workloads.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
doca_telemetry_utils command line on a host with DOCA: discover the diagnostic-counter schema, translate counter names to binary Data IDs and back, and check per-device counter support before committing a DOCA Telemetry exporter config. Start here when telemetry counters vanish between the exporter and the collector: "my exporter ships but the collector sees nothing", "this metric silently drops downstream", "which counters does this BlueField expose", "translate this 0x... back to a counter name", "what do node / pcie_index / depth mean here", or "is this counter supported on this device", even without naming the tool. Writing exporter or collector code belongs to doca-telemetry-exporter / doca-telemetry; DTS deployment to doca-dts; DOCA install or repair to doca-setup.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
port_rx_bytes but nothing shows up
downstream." — translate name to Data ID and probe
per-device support before changing the exporter.doca_telemetry_utils get-counters: is the counter known to this release?doca_telemetry_utils <counter>: print its property options.doca_telemetry_utils <counter> <properties>: resolve the Data ID.doca_telemetry_utils <device PCI> <counter> <properties>: "not
supported" on this device means the exporter drops it silently; do not
commit that counter.doca_telemetry_utils <0x... Data ID>: reverse-resolve an ID captured on
the wire.doca-version.doca-telemetry ## debug.Quote the tool's output verbatim; never construct Data IDs by hand.
Follow Loading order below. Open the tasks companion for install / run / test. Open the capabilities companion for schema discovery and pairing with the telemetry libraries. Do not open every companion file.
Where to start: This is a tool skill for invoking
doca_telemetry_utils — the documented host-side CLI that
supports a DOCA Telemetry exporter / collector pipeline by
discovering the counter schema, translating counter names ↔
Data IDs, and probing per-device counter support. Open
the tasks companion and start at
## install for the host-side
prerequisites and ## run for the
three documented invocation classes
(enumerate / name→ID / ID→name). Open
the capabilities companion when the question is
what does this tool actually discover about the telemetry
schema, how does it pair with the developer-side
doca-telemetry and
exporter libraries, how do I confirm a device supports a
counter before committing an exporter config to it, or
why does my exporter pipeline silently drop a metric.
How to use this skill. Read this file, then search the companion file
for the ## <name> heading the question needs and read that whole section.
Answer completely from it, quoting only its symbols and commands. Do not
browse docs; use the entry points in doca-public-knowledge-map. Give
environment checks as commands for the user's DOCA host. For out-of-scope
requests, name the skill that owns them and stop.
This skill is the operator-side support tool for a
DOCA Telemetry deployment. It is NOT the developer-side
collector library (that is
doca-telemetry),
NOT the developer-side publisher library (that is
doca-telemetry-exporter — see
doca-telemetry ## Related skills),
and NOT a DOCA Telemetry Service (DTS) deployment guide
(route to doca-dts).
Three separate surfaces; conflating them is the most
common telemetry first-touch error.
The CLASSES of doca_telemetry_utils questions this skill
is built to answer, each with one worked example. The
class is the load-bearing piece; the worked example is one
instance.
port_rx_bytes but
nothing shows up downstream — what did I get wrong?" —
worked example: "my exporter config has a counter name
string and my collector sees no events with that
name". Answered by the name ↔ Data ID translation
step in
the capabilities companion
doca_telemetry_utils get-counters lists every
counter name the diagnostic-data surface knows about;
pair with a per-device probe to confirm support).Data ID: 0x1160000600030201 — translate it
back so I can correlate against the public guide".
Answered by the reverse-resolve invocation class in
the capabilities companion
pcie_link_write_stalled_time_* — what
do node / pcie_index / depth mean and what
values does the device accept?". Answered by the
property-dimension table in
the capabilities companion
<name> invocation without arguments which
prints the documented property options + units +
unit-specific axes.port_rx_bytes with node=1 is
exposed on the BlueField at PCIe address X before I
write the exporter config". Answered by the
per-device-support probe (<device PCI> <name> [properties]) in
the capabilities companion
doca_telemetry_utils on my install, and is it
paired with the matching doca-telemetry library
version?" — worked example: "is the diagnostic-
data counter set my exporter targets on this DOCA
version?". Answered by the version-overlay in
the capabilities companion,
which redirects to the canonical
doca-version chain
and adds the tool ↔ doca-telemetry library
schema-version match rule.Load this skill when the user is — or the agent needs
to — invoke doca_telemetry_utils on a real host with
DOCA installed, alongside an exporter / collector
pipeline that needs schema discovery, per-device
support validation, or Data ID translation.
Concretely:
get-counters).Do not load this skill for general DOCA orientation,
collector / exporter library programming, DTS
deployment, or DOCA install. For those, route to
doca-public-knowledge-map,
doca-telemetry,
or doca-setup.
This is a thin loader. Substantive material lives in two companion files:
doca_telemetry_utils
discovers + how it pairs with the developer-side
surfaces: the three documented invocation classes
(enumerate / name→ID / ID→name), the property-
dimension model (counters carry property axes such
as node, pcie_index, depth, plus per-unit
axes), the optional per-device capability probe
(<device PCI> <name> runs the resolved counter
against the device), the operator-side support
role (this is NOT the developer-side library; it
exists to make exporter / collector setups
honest), the version overlay (tool ↔
doca-telemetry library schema version pairing),
the layered error taxonomy (install / parse /
unknown-counter / unknown-data-id / property-out-
of-range / device-not-supported / version /
cross-cutting), the observability surface
(stdout-only), and the safety policy (the tool is
read-only; mistakes appear downstream as silent
metric drops, not crashes).install (host-side DOCA +
telemetry component prerequisites), configure
(axis decisions: which invocation class, which
device, which counter), build (route to install
— the binary is shipped), modify (refuse — do
not patch the binary; modify the invocation and
the exporter / collector config that consumes the
resolved Data IDs), run (the three documented
invocations), test (round-trip a chosen
counter through name → Data ID → per-device
probe → exporter config → collector receipt),
debug (walk the error taxonomy), use (the
hand-off into the developer-side doca-telemetry
collector / exporter pipeline), plus a Deferred task verbs block.The skill assumes a host where DOCA is already
installed with the telemetry component, a BlueField
the operator is targeting is visible to DOCA, and the
exporter / collector pipeline that consumes the
resolved Data IDs is either being authored or has
already been authored against the matching
doca-telemetry
library version.
This skill is agent guidance, not a samples or scripts bundle. To keep the boundary clean, it deliberately does not contain — and pull requests should not add:
doca_telemetry_utils get-counters on the
installed binary is the authoritative source.doca-public-knowledge-map.
This skill resolves the counter names + IDs a
DTS pipeline consumes; it does not configure DTS.samples/ or reference/ subtree. This is
a thin loader for a shipped CLI; substantive
material lives on the public page, in --help,
and in doca-telemetry.install, configure, build,
modify, run, test, debug, use — see
the tasks companion.doca-telemetry
— the developer-side collector library whose
schema this tool helps the operator discover. Pair
them in every exporter-pipeline triage session.
The collector library skill teaches the
collector-vs-exporter rule, the schema-must-match
contract with the publisher, and the consumer-
queue-full back-pressure rule; this tool's role
is to make the schema half of that contract
inspectable from the operator side. Conflating
the library and the tool is the most common
telemetry first-touch error.doca-public-knowledge-map
— routing to the public DOCA Telemetry guide and
the DOCA Telemetry Service (DTS) page on
docs.nvidia.com, plus the on-disk install
layout for the tool.doca-version —
canonical DOCA version-handling rules. The
## Version compatibility section in
the capabilities companion is a concise
overlay that redirects here for the body and
adds the tool ↔ doca-telemetry library
schema-version pairing rule.doca-setup — env
preparation, install verification, and the I
have no install yet path with the public NGC
DOCA container. This skill assumes its
preconditions are satisfied (DOCA installed
with the telemetry component, BlueField visible
to DOCA).doca-debug — the
cross-cutting debug ladder. Telemetry-utils
feeds the cross-cutting ladder by surfacing the
counter schema + per-device support truth at the
runtime layer; exporter-pipeline regressions
often resolve at the schema layer before
touching the collector / network path.doca-structured-tools-contract
— the bundle's detect → prefer → fall back →
report contract for structured helper tools. The
command appendix in the tasks companion
honors this contract.doca-programming-guide
— general DOCA programming patterns shared by
every library / tool surface, including the
cross-library DOCA_ERROR_* taxonomy this
tool's host-side error layer overlays on top of
when downstream collector / exporter code
surfaces a related error.아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
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Official NVIDIA-authored guidance for NVIDIA cuDF GPU DataFrames, pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV/Parquet I/O, nullable semantics, and multi-GPU DataFrame workloads.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Customize NVIDIA Nemotron Voice Agent's Generic Pipecat example for healthcare appointment, five-field patient intake, or custom tool-calling workflows without a separate backend.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Calibrate a new dataset from live RTSP camera streams via the AutoMagicCalib REST API. Use when the user provides RTSP URLs or asks to calibrate live cameras; VIOS records clips, AMC ingests them, then runs calibration.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Run end-to-end calibration on the shipped sample dataset (sdg_08_2_sample_data_010926.zip) against a running AMC microservice. Use when user says 'test sample dataset', 'run sample calibration', 'verify AMC install', or 'launch and test'.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Calibrates pre-recorded `cam_*.mp4` datasets through the AutoMagicCalib REST API. Use for user-supplied local MP4s; route live RTSP streams to `amc-run-rtsp-calibration`.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Launch AutoMagicCalib microservice and web UI from NGC release images via Docker Compose. Use when user says 'deploy auto calibration', 'launch auto calibration', 'launch AMC', 'start MS+UI', or 'set up auto-magic-calib'. Requires NGC API key.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.