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Found 19 Skills
Start, query, and stop a network-specific TAO inference microservice ({network_arch}-inference-microservice) by delegating container execution to the appropriate platform skill. Handles container image resolution, job-payload JSON construction, and the service registry. Use when the user wants to run inference on a TAO model checkpoint using a microservice container, deploy a TAO inference endpoint, or stop a running inference container.
Manages Cloud Run services, jobs, and worker pools. Use when you need to deploy applications responding to HTTP requests (services), run event-triggered or scheduled tasks (jobs), or handle always-on pull-based background processing (worker pools).
Use when deploying Docker Compose applications to production including security hardening, resource management, health checks, logging, monitoring, and high-availability patterns.
Master Kubernetes with pods, deployments, services, ingress, ConfigMaps, secrets, and production cluster management.
Deploy containerised applications to Google Cloud Run from source using gcloud CLI. Use when the user asks to "deploy to GCP", "deploy to Cloud Run", "ship to Google Cloud", "gcloud run deploy", or needs to set up, redeploy, configure env vars/secrets, view logs, or troubleshoot a Cloud Run service.
Deploy containers on ECS and Fargate. Configure task definitions, services, and load balancing. Use when running containerized workloads on AWS.
Clone the latest NVIDIA Holoscan Sensor Bridge repo, ask which supported devkit is being used, configure the host per platform, build the correct demo container, run it, and verify HSB connectivity by pinging 192.168.0.2. Use for Holoscan Sensor Bridge setup, build, container launch, and first-connectivity bring-up.
Deploy applications on Railway platform. Use when deploying containerized apps, setting up databases, configuring private networking, or managing Railway projects. Triggers on Railway, railway.app, deploy container, Railway database.
Create Dockerfiles, docker-compose configurations, and container workflows for Python projects with UV. Use when containerizing applications, setting up development environments, or deploying with Docker.
Amazon Bedrock AgentCore deployment patterns for production AI agents. Covers starter toolkit, direct code deploy, container deploy, CI/CD pipelines, and infrastructure as code. Use when deploying agents to production, setting up CI/CD, or managing agent infrastructure.
Expert guidance for Docker Compose — writing production-grade compose.yml files for multi-container applications. Covers complete Compose file syntax (services, networks, volumes, secrets, configs, profiles, extends, include), service configuration (image/build, ports, environment, env_file, depends_on with health checks, deploy resources, restart policies), networking in Compose (default networks, custom networks, internal networks), volume management, environment variable strategies (.env vs environment vs env_file), override files for multi-environment, profiles for optional services, and migration to Kubernetes with kompose. Use when the user asks about docker compose, docker-compose.yml, compose file, multi-container, service orchestration, compose configuration, or needs to write/modify a compose file. 使用场景：docker compose、docker-compose.yml、compose 文件、多容器、服务编排、compose 配置、depends_on、profiles.
Deploy containerized applications on Google Cloud Run with automatic scaling, traffic management, and service mesh integration. Use for container-based serverless computing.