인프라·DevOps 스킬

Plan and validate NVSHMEM and NVSHMEM4Py installations on individual machines, clusters, or containers. Checks system facts against version-specific documentation, selects a suitable installation method, and prepares commands and runtime validation steps for review.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Plan an NVSHMEM installation on a workstation
• Choose a Python installation method for NVSHMEM4Py
• Prepare a source build for a multi-node system

Choose an NVSHMEM transport, the communication path between compute nodes, from installed plugins, network evidence, and optional workload analysis. Receive a recommended configuration with minimal environment variables, compatibility evidence, alternatives, and clearly stated unknowns.

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• Choosing a transport compatible with a compute system
• Assessing communication needs in selected CUDA code
• Getting minimal transport selection settings

Recommends network-port assignments and environment settings for NVSHMEM using the compute node’s actual GPU and network topology. Helps select adapters, evaluate multiple-port options, and identify missing evidence before producing an exact configuration.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choosing network ports closest to each GPU
• Checking multi-NIC options for an NVSHMEM version
• Diagnosing unexpected port selection

Set up Auto Ontology with Helm or Docker Compose, or connect an agent to an existing deployment through MCP, an agent connection protocol. Guides database connections, readiness checks, and troubleshooting for startup and sign-in problems.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Installing Auto Ontology on Kubernetes
• Running the stack on one machine with Docker Compose
• Connecting an agent to an existing deployment

Set up NVIDIA infrastructure for synthetic data generation on MicroK8s or Azure AKS. Coordinate Kubernetes, inference services, and OSMO workflow execution, with prerequisite checks, deployment validation, capacity planning, and failure investigation before workloads are retried.

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• Set up a synthetic data generation environment on MicroK8s
• Deploy an Azure AKS environment with OSMO and inference services
• Check GPU quotas and capacity before scaling

Switch the vision-language model, which handles images and text, in VSS Alerts Blueprint. Configure alert generation, verification, and agent queries separately, choose an external endpoint or bundled vLLM deployment, and verify an actual inference response.

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• Switch all three VSS services to a different model endpoint
• Run standalone rtvi-vlm with an external model server
• Serve a model with vLLM inside the RTVI container

Helps an AI coding assistant answer NemoClaw installation, configuration, operation, and troubleshooting questions using official documentation. It finds relevant pages through MCP, a documentation connection, or Markdown files, then tailors guidance to the selected agent and environment.

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• Install NemoClaw for a selected agent
• Configure inference providers and models
• Investigate sandbox errors and logs

Configure observability in NeMo Relay 0.6 or 0.7 to inspect recorded activity. Choose raw events, execution histories, or traces that show how calls unfold, then verify the selected output before adding more destinations.

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• Inspecting raw events during local debugging
• Exporting execution histories in ATIF format
• Configuring OpenTelemetry trace output

Organize NeMo-RL experiments on Brev by placing large outputs and shared caches on /ephemeral, loading credentials without exposing them, checking disk capacity, and keeping concise reproduction records in the source checkout.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Prepare storage before a long training run
• Share model and dataset caches across experiments
• Run authenticated W&B or Hugging Face workflows

Prepare a Jetson BSP image, the board's system software, from local Jetson Linux and sample root filesystem archives. Apply GPU binaries for the selected target, verify existing images, and record image metadata in its profile.

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• Prepare a BSP image after selecting a Jetson target
• Extract matching Jetson Linux and root filesystem archives
• Check and reuse an existing Linux_for_Tegra directory

Switch the active Jetson target to an existing YAML profile before customization, building, or flashing. Review profile names and configuration summaries, choose a target, and update the pointer used by downstream skills without creating new profiles.

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• Switch the target before building
• Choose an existing profile before flashing
• Select a target when none is active

Inspect live Jetson memory usage, identify major consumers, and compare measurements before and after changes. It also supports checking whether approved cache clearing makes reclaimed memory visible in the device's reported free and available memory.

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• Identify major memory consumers on a Jetson
• Check memory after stopping a model server
• Measure memory reclaimed by configuration changes

Configure Jetson CPU, GPU, and memory-controller clock frequencies before flashing an image. Edit firmware settings and the boot script to fix or limit frequencies, change frequency-control policies, and enable or disable automatic frequency scaling.

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• Preparing fixed CPU or GPU frequencies for performance tests
• Setting maximum or minimum device clock frequencies
• Enabling or disabling automatic memory-controller frequency scaling

Collect a short, read-only report from a running Jetson device, covering its model, L4T release, kernel, OS, power mode, and uptime. Use it to record the environment before performance, regression, or compatibility tests.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Record the device environment before performance tests
• Check the L4T release after flashing a Jetson
• Capture baseline information for compatibility tests

Prepare kernel device-tree overlays, files describing hardware settings, for PCIe controllers on Jetson Thor or Orin custom carrier boards. Set lane counts and link speeds from documented plans, and check consistency with existing ODMDATA configuration.

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• Preparing PCIe controller settings for a custom carrier board
• Updating kernel settings after UPHY lane reallocation
• Investigating a PCIe slot or M.2 device that is not detected

Reclaim application memory on Jetson deployments without displays or cameras. Guides changes to boot settings, kernel memory reservations, and the DMA transfer buffer, then checks compiled settings and memory usage on the running device.

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• Reclaiming memory on a Jetson without a display
• Removing camera memory reservations
• Shrinking and checking the DMA transfer buffer

Prepare a staged Jetson BSP image, the device software package, by copying customized files and built artifacts. Skip identical files and refresh startup files when kernels or modules change, without building or flashing the device.

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• Apply customized configuration files to a staged BSP image
• Copy built kernels and modules into the image
• Prepare an image for inspection before flashing

Reclaim memory on Jetson devices that do not need a local desktop or display. Build a plan from current memory audit data, preview reversible service changes, apply approved changes, and measure the actual memory savings afterward.

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• Estimate memory savings from headless operation
• Prepare a Jetson for use as an inference appliance
• Disable unneeded desktop and background services

Create a Jetson target-platform YAML profile by selecting a reference product and flash configuration, with optional details for a custom carrier board. The workflow also sets the active profile used by subsequent setup and customization skills.

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• Creating the first Jetson target-platform profile
• Recording a custom carrier board and its reference platform
• Adding a profile for another Jetson product

Customize Jetson and Tegra power modes in BSP files, the device's system software configuration. Adds, removes, or edits nvpmodel profiles, adjusts frequency limits, changes the boot default, and guides deployment of the updated configuration.

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• Add a power mode from a Power Estimator export
• Adjust frequency limits in an existing mode
• Change the default power mode at boot

Collects a read-only health snapshot of a Jetson device, covering its model, memory, GPU, temperatures, power mode, storage, services, and processes. Helps investigate slowdowns, overheating, and memory pressure using observed device data.

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• Identify the Jetson model and memory capacity
• Investigate slowdowns and overheating
• Find processes consuming RAM or GPU memory

Inspect a Jetson BSP folder on a Linux host before flashing. Get a concise report of the L4T release, available board configuration files, and whether the root filesystem appears populated, without modifying files.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking the L4T release before flashing
• Listing available board configuration files
• Checking whether the root filesystem appears populated

Start Jetson or IGX board software customization by selecting a setup mode, platform, release, and carrier-board intent in a questionnaire. It passes those choices to the appropriate setup skills and reports workspace readiness and remaining steps.

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• Start setup in a new Jetson workspace
• Continue setup using existing files and archives
• Check prerequisites in a prepared workspace

Manage nvfancontrol fan profiles for Jetson and Tegra boards. Add, remove, or edit temperature-based fan curves and boot defaults in board support files, while tracking changes and preserving configuration differences between related carrier boards.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• List fan profiles and boot defaults
• Add or remove a fan profile
• Adjust fan curves using measured platform data