Results for “dep”

Deploy, inspect, log-tail, snapshot, and troubleshoot AEM Rapid Development Environments using the Adobe I/O CLI plugin.

Runs a Trailmark summary analysis on a codebase to auto-detect languages, count entry points, and list dependencies.

Plans and coordinates the deployment of a model to Amazon SageMaker AI, selecting the appropriate pathway (real-time, serverless, async, batch, or Bedrock CMI) based on model type, traffic, latency, and cost constraints.

Run pre-deployment validation checks for Azure readiness, including configuration, infrastructure (Bicep or Terraform), RBAC role assignments, and managed identity permissions.

Deploy the AutoMagicCalib microservice and web UI from pre-built NGC release images using Docker Compose.

Validates Bicep deployments to Azure before execution, including syntax checks, what-if analysis, and permission verification.

Discovers, validates, or creates a SageMaker execution role before deploying or training, preventing IAM-related deployment failures.

Build, deploy, and modify GitHub Copilot SDK apps on Azure with scaffolding, model configuration, and deployment orchestration.

Build AI applications using the Azure AI Projects SDK for TypeScript, managing agents, connections, deployments, datasets, indexes, and evaluations.

Diagnose failed or unhealthy Dynamo deployments by collecting a read-only debug bundle, classifying failures, and providing step-by-step remediation guidance.

Generates comprehensive GitHub project plans with Epic > Feature > Story/Enabler > Test hierarchy, dependencies, priorities, and automated issue tracking.

Set up and initialize AWS CDK applications in Python, including prerequisites, project creation, dependency management, and deployment.

Deploys Python web apps (Flask, Django, FastAPI) to Azure App Service Linux with automatic resource creation and framework detection.

Guides through interactive deployment of Azure OpenAI models with full control over version, SKU, capacity, content filtering, and advanced options.

Manage Azure AI Foundry projects with .NET SDK: create and run agents, manage connections, datasets, deployments, evaluations, and indexes.

Develop, deploy, and manage Cloudflare Workers and associated services (KV, R2, D1, Queues, etc.) using the Wrangler CLI with up-to-date commands and configuration.

Generates Mermaid diagrams from code graphs, including call graphs, class hierarchies, module dependency maps, and data flow visualizations.

Trains, evaluates, exports, and runs inference on FoundationStereo models for stereo depth estimation and 3D reconstruction from stereo image pairs.

Deploy and configure Generic VNIC Attachment (GVA) for OCI Kubernetes Engine (OKE), including node pool creation with secondary VNIC profiles and workload mapping.

Create, deploy, and debug machine learning applications on Hugging Face Spaces using Gradio, Docker, or Static SDKs, with support for ZeroGPU and dedicated hardware.

Fine-tune models on Azure AI Foundry using SFT, DPO, or RFT, covering dataset preparation, training job submission, deployment, and evaluation.

Deploy and verify Multus-based pod multihoming on OKE clusters with existing GVA secondary VNIC node pools, including discovery, manifest generation, and connectivity validation.

Generate comprehensive rollout plans with preflight checks, step-by-step deployment, verification signals, rollback procedures, and communication plans for infrastructure and application changes.

Audits project dependencies for supply chain risks including single maintainers, unmaintained packages, low popularity, high-risk features, past CVEs, and missing security contacts.

Deploy Expo apps to production with EAS — build and submit to the iOS App Store, Google Play Store, and TestFlight, configure eas.json build and submit profiles, manage app versions and build numbers, publish App Store metadata and ASO, and deploy web bundles and API routes via EAS Hosting.

Selects, configures, deploys, verifies, debugs, or tears down a VSS profile (base, search, lvs, warehouse, edge) for NVIDIA's video search and summarization stack.

Deploy serverless browser automation as cloud functions using Browserbase. Run browser automation on a schedule, create webhook endpoints, or run automation in the cloud instead of locally.

Ensure .NET/C# code meets project-specific best practices for structure, design patterns, dependency injection, async/await, testing, configuration, and security.

Trains, evaluates, exports, and runs inference for FastFoundationStereo (FFS) stereo depth estimation models, a distilled variant of FoundationStereo with lower latency.

Create, configure, and deploy Azure Static Web Apps using the SWA CLI, including local development, runtime configuration, and CI/CD setup.

Selects the correct SageMaker serving container image URI for HuggingFace model deployments, prioritizing HuggingFace-curated Deep Learning Containers over generic alternatives.

Build, scaffold, and deploy Power Automate cloud flows programmatically via the FlowStudio MCP server, including constructing flow definitions, wiring connections, deploying, and testing.

Deploy a standalone RT-VLM dense-captioning microservice and exercise its REST API endpoints for file upload, caption generation, streaming, chat completions, and Kafka integration.

Deploy, debug, and operate the RTVI-CV 2D detection/tracking microservice and call its REST API for stream management, health checks, and metrics.

Deploy and operate the RTVI-CV-3D microservice for multi-camera 3D detection and tracking, supporting sample datasets, custom videos, and RTSP streams.

Wire CommunityToolkit.Mvvm ViewModels into Microsoft.Extensions.DependencyInjection with constructor injection, service lifetimes, IMessenger registration, and testing seams for WPF, WinUI 3, MAUI, Uno, and Avalonia apps.