인프라·DevOps 스킬

Start a CARLA simulator server from a downloaded release, packaged build, or source checkout. It selects the launch mode, supports headless or windowed operation, checks client connectivity, and guides clean shutdown.

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• Start a downloaded CARLA release
• Run traffic scenarios without a window
• Launch a server with native ROS 2 enabled

Start, inspect, and stop a CARLA UE 5.8 server. Choose an editor-based server, packaged build, or full editor; configure headless operation and ports; and enable native ROS 2 integration when the build supports it.

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• Start a UE 5.8 server for a CARLA client
• Configure camera image publishing through ROS 2
• Investigate missing maps or connection failures

Package a CARLA server built with UE 5.8 for distribution, choosing which maps to include. Inspect the resulting files for mismatched containers, missing road data, and exposure settings that can cause runtime failures.

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• Packaging a CARLA server with selected maps
• Investigating a black screen in a packaged server
• Checking road data and package consistency

Set up a CARLA driving evaluation environment for Leaderboard 1.0, 2.0, or 2.1. Match the simulator and scenario_runner versions, configure Python paths, and verify that the required components load correctly.

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• Setting up an environment to evaluate a driving agent
• Checking version differences behind inconsistent scores
• Recreating the Leaderboard 1.0 evaluation environment

Set up ScenarioRunner, CARLA’s scenario engine, with a branch matched to your simulator version. Install dependencies, configure Python search paths, and verify imports to address setup failures before running scenarios.

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• Install ScenarioRunner for a specific CARLA version
• Switch an existing setup to the UE5 branch
• Fix imports failing because the agents package is missing

Build distributable CARLA releases or asset packages containing selected maps and props. It prepares content for runtime use, checks output files, supports destination changes, and preserves native ROS 2 support when explicitly enabled.

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• Create a full CARLA release archive
• Export Town02 as an importable asset package
• Preserve native ROS 2 support in a packaged build

Package a CARLA Leaderboard agent into a Docker image for submission. It checks required directories and Python package files, supports ROS variants, and verifies that dependencies import and the agent loads inside the image.

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• Build a Docker image for Leaderboard submission
• Investigate missing egg files in make_docker.sh
• Package a ROS agent with its bridge

Downloads CARLA release packages, nightly builds, source code, or Docker images, then reports their locations and environment variables for follow-up setup. Supports extra maps and resumable downloads, helping prepare the files needed for subsequent installation or building.

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• Getting CARLA for the first time
• Downloading an older version to reproduce a bug
• Fetching additional maps

Deploy language model APIs and run batch generation with vLLM. Configure GPU memory use, quantization—lower precision model storage—and distribution across GPUs, then test response times and monitor how many requests the server handles.

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• Deploying an OpenAI-compatible language model API
• Generating responses for a large set of prompts
• Fitting a large model into limited GPU memory

Run machine learning workloads on Modal's cloud GPUs without managing servers. Guides Python configuration for training, inference, batch processing, and API deployment, including automatic scaling, persistent storage, scheduled jobs, and troubleshooting.

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• Running GPU inference without managing servers
• Deploying a model as an automatically scaling API
• Processing large batches in parallel

Guides setup and operation of Lambda Labs GPU instances for machine learning training and inference. Covers SSH access, persistent storage, API automation, and multi-GPU or multi-node training, including how to retain checkpoints and terminate idle instances.

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• Setting up a GPU instance for LLM fine-tuning
• Keeping datasets and checkpoints between sessions
• Automating instance launch and termination through the API

Configure machine learning training and batch jobs across multiple clouds with SkyPilot. The skill guides GPU selection, lower-cost cloud and region choices, and automatic recovery when discounted spot instances are interrupted.

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• Choose a lower-cost cloud for GPU training
• Run long training jobs with recovery after interruptions
• Configure distributed training across multiple machines

Run Python code and Shell commands in an isolated Cube Sandbox environment. The skill covers file access, host directory mounting, network restrictions, and pausing and resuming execution while preserving the sandbox's memory state.

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• Running untrusted code in an isolated environment
• Reading and writing sandbox files
• Restricting outbound network access

Prepare an Ant Design Mobile package release by checking the version, build, and package contents. After the user publishes to npm manually, verify the published package and create its Git tag and bilingual GitHub Release.

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• Prepare an Ant Design Mobile release
• Check files included in an npm package
• Draft release notes in Chinese and English

Build infrastructure as code with Terraform across AWS, Azure, and GCP. Create reusable modules, manage state records that track resources, configure environments and providers, and validate proposed changes before applying an explicitly approved plan.

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• Creating reusable Terraform modules
• Migrating state storage or importing existing resources
• Managing settings across development and production

Define reliability targets for production services and calculate error budgets, the allowed amount of failure. Create monitoring rules, incident response runbooks, capacity plans, and automation scripts, with failure experiments to check recovery behavior.

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• Define service reliability targets and error budget policies
• Design monitoring dashboards and actionable alerts
• Prepare incident response runbooks and postmortems

Create Dockerfiles, automated build and deployment pipelines, Kubernetes configurations, and infrastructure templates. The skill also prepares deployment checks, rollback procedures, and incident response runbooks to support application releases and production operations.

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• Setting up automated build and deployment pipelines
• Packaging applications with Docker
• Managing Kubernetes and cloud infrastructure as code

Investigate slow PostgreSQL and MySQL queries using execution plans, which show how the database runs a query. Develop index, SQL, and configuration changes, then compare measurements before and after each change to validate the results.

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• Investigating slow SQL queries
• Reviewing database index design
• Tuning memory and database configuration

Analyze and tune PostgreSQL databases using query execution plans, which show how queries run. This skill guides index design, JSONB searches, replication setup, maintenance, and monitoring, with checks to compare behavior before and after changes.

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• Investigate slow queries with EXPLAIN
• Design indexes for JSONB searches
• Configure replication and monitor lag

Design cloud architectures and migration plans for AWS, Azure, and GCP. Produce service diagrams, selection rationale, security designs, cost estimates, and recovery strategies, with deployment and rollback plans that account for availability and operational monitoring.

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• Design a cloud architecture and explain service choices
• Plan a cloud migration and cutover checks
• Review cloud spending and resource sizes

Set up application monitoring with structured logs, performance metrics, and traces that follow requests across services. Build dashboards and alerts, run load tests, investigate CPU and memory bottlenecks, and estimate future infrastructure capacity.

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• Set up application dashboards and alerts
• Investigate production issues using logs, metrics, and traces
• Run load tests before traffic increases

Create Kubernetes deployment files and Helm charts, reusable application packages. Configure permissions, network isolation, and persistent storage, then investigate pod failures and resource usage to adjust workloads and verify deployment health.

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• Create deployment YAML and Helm charts
• Configure access permissions and network isolation
• Set up persistent storage and sensitive configuration

Move an ongoing task to a new HumanLayer session on another machine. The skill saves and pushes changes, writes handoff notes, prepares the destination, transfers selected secret files, and checks that the remote session starts.

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• Move ongoing development to a sandbox
• Continue a task on a cloud VM
• Hand off work to a machine reachable through SSH

Update release base versions for supported packages, keep matching version fields in sync, and verify generated versions. The workflow covers committing and pushing the changes, with guidance for release steps after merging.

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• Prepare a package version update for release
• Synchronize version fields across related files
• Verify generated versions before pushing