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.
Running an in-bundle DOCA service as a container on a BlueField (Argus, DMS, Firefly, or UROM service): kubelet standalone watching a static-pod manifests directory, YAML pod-spec drop, kubelet status / ENTRYPOINT logs / per-service liveness. Trigger on "how do I run my built service on the BlueField?", "where do I drop the pod-spec YAML?", "pod stuck in Pending / ImagePullBackOff / CrashLoopBackOff", "container Running but service isn't ready", "pod restart-loops after edit", or "DMS and Firefly together", even without naming container deployment. A DOCA-linked binary launched directly on the host or Arm belongs to doca-bare-metal-deployment. Covers smoke-before-bulk and the layered error taxonomy (pod-spec, scheduling, image pull, runtime, mount, network, version, host). Refuse and route elsewhere for per-service config schemas, DOCA install, library-API questions, external NVIDIA services (BlueMan, HBN, SNAP, Virtio-net), or full Kubernetes-cluster ops.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Follow Loading order below. Open the tasks companion for configure / run / debug. Open the capabilities companion for the kubelet-standalone contract. Do not open every companion file.
Where to start: This skill is for operating the cross-cutting DOCA container-deployment runtime — the shared pattern every DOCA service on the BlueField uses to come up (kubelet standalone agent on the BlueField Arm watching a static-pod manifests directory; the operator drops a YAML pod spec into that directory; kubelet schedules the pod and runs the container).
If the developer has NOT yet decided container vs. bare-metal
("I just got a BlueField, what now?", "my code is built, how do I
run it?", "how do I deploy this?"), route them BACK to
doca-setup first.
That is the front-door routing decision. The wrong failure mode is
to silently push every developer onto the container path because the
agent loaded this skill first. ## recognize detects the system
shape, asks the minimum residual question, and lands the developer on
either this skill (when the workload is a packaged DOCA service to
drop on a BlueField) or the bare-metal-path sibling
doca-bare-metal-deployment
(when the workload is a DOCA-linked application binary the developer
launches directly).
If the developer is already on the container path, open
the tasks companion and start at
## configure. If the question is what shape
of runtime is this and what does the deployment contract look like,
start at the capabilities companion. For per-service
overlays, follow the per-service skill under skills/services/ that
layers on top of this one — the supported overlays are Argus, DMS,
Firefly, and UROM service. Flow-Inspector and OS-Inspector are
policy-excluded from this public bundle; route them through
doca-public-knowledge-map
instead of applying this runtime overlay. Externally-productized
NVIDIA services (BlueMan, HBN, SNAP, Virtio-net, DOCA Telemetry
Service as productized, …) are also out of scope and route through
that map. If DOCA is
not installed on the BlueField target yet, route to
doca-setup first.
This skill serves external operators and platform teams who deploy
DOCA service containers on BlueField — i.e., people who have a
BlueField with DOCA installed on the Arm side, a container runtime
plus the kubelet standalone agent already present per the BlueField
OS image, and the host-OS permissions the public DOCA Container
Deployment Guide names for the chosen service. The skill is the
shared deployment runtime; each per-service skill in the bundle
(see the list in ## Related skills) supplies
the service-specific config schema, paired-workload contract, and
"healthy" definition.
It is not for NVIDIA developers contributing to the BlueField
container runtime or to kubelet itself, and it is not a generic
Kubernetes tutorial. Kubelet runs on the BlueField in standalone
mode here — no full Kubernetes control plane, no kubectl against
a cluster API server — and the substantive answer to most
container-deployment questions on the BlueField is the public DOCA
Container Deployment Guide. This skill teaches the agent which
guide to quote, in what order to walk it, and how to map a symptom
to a layer; it does NOT re-invent kubelet flags, pod-spec field
names, or static-pod path strings. The shared deployment runtime
described here is the cross-cutting layer; the per-service skill
(doca-argus, doca-dms, doca-firefly,
doca-urom-svc) supplies the per-service
config schema, paired-workload contract, and "healthy" definition.
Load this skill when the user is doing hands-on container deployment of any DOCA service on a BlueField target, or asking a cross-service deployment question that is not specific to one service's config schema. Concretely:
Running;
ENTRYPOINT logs are clean; service answers a trivial liveness
probe) BEFORE the BlueField is put under workload.Do not load this skill for per-service config schema questions
(those belong to the matching per-service skill); for installing
DOCA itself or preparing the BlueField env (use
doca-setup); for library-API
questions (use the matching libs/<library> skill); or for general
Kubernetes-cluster operations (this skill covers kubelet standalone
mode on the BlueField, not a full Kubernetes control plane).
This is a thin loader. Substantive material lives in two companion files:
configure, build, modify, run, test, debug,
plus a Deferred task verbs block routing per-service config
questions, host-firmware-slot work, paired-workload work, and
full-Kubernetes-cluster work out to their owning skills.The skill assumes a BlueField target where DOCA is already installed
on the Arm side, the BlueField OS image ships kubelet standalone +
the container runtime per the public DOCA Container Deployment
Guide, and the operator has the host-OS permissions that guide
names. It does not cover installing DOCA — that path goes through
doca-setup — and it does not
re-document the per-service config schema, which is the canonical
concern of each DOCA service's public guide reached through
doca-public-knowledge-map.
doca-public-knowledge-map
— public Container Deployment Guide, per-service guides, and
NGC. Quote documented paths and tags from there; do not invent
them.doca-setup — env and install on the
BlueField target, including the recognize front door that
chooses this skill vs bare-metal.doca-bare-metal-deployment
— the sibling binary-launch path.doca-debug — cross-cutting debug
ladder this runtime's pod / image / ENTRYPOINT layers sit on.doca-version — four-way match and
container-tag overlay.doca-structured-tools-contract
— prefer structured status when present.doca-argus,
doca-dms,
doca-firefly,
doca-urom-svc.doca-programming-guide
— program-side discipline when a service surfaces a library
error.아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
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.