Results for “deployment”

Guides securing and deploying the Dify platform in production, covering SSRF protection, code sandboxing, Docker/Kubernetes deployment, monitoring, and recovery.

Deploys web apps with backend APIs, databases, and file storage to a public URL via the AppDeploy HTTP API.

Provides a sandboxed execution environment for running code snippets, automating tasks, and deploying logic across multiple languages with resource capping and network isolation.

Deploys applications, static sites, and edge functions to Azion using the Azion CLI, with preflight checks for authentication and build configuration.

Manage Cloudflare Tunnels via API and TypeScript SDK, including creation, configuration, DNS routes, and token-based deployment.

Configure a QQ official bot and connect it to OpenClaw AI, covering creation, IP whitelisting, deployment, and troubleshooting.

Specialized skill for building production-ready serverless applications on AWS. Covers Lambda functions, API Gateway, DynamoDB, SQS/SNS event-driven patterns, SAM/CDK deployment, and cold start optimization.

Specialized skill for building production-ready serverless applications on AWS. Covers Lambda functions, API Gateway, DynamoDB, SQS/SNS event-driven patterns, SAM/CDK deployment, and cold start optimization.

Design, organize, and manage Helm charts for templating and packaging Kubernetes applications with reusable configurations. Use when creating Helm charts, packaging Kubernetes applications, or implementing templated deployments.

Expert knowledge for Azure Blueprints development including troubleshooting, architecture & design patterns, security, configuration, and integrations & coding patterns. Use when defining Azure Blueprints, mapping built-in compliance sets, automating via CLI/PowerShell/REST, or fixing assignment errors, and other Azure Blueprints related development tasks. Not for Azure Policy (use azure-policy), Azure Resource Manager (use azure-resource-manager), Azure Managed Applications (use azure-managed-applications), Azure Deployment Environments (use azure-deployment-environments).

Expert knowledge for Azure Data Share development including troubleshooting, decision making, security, configuration, and deployment. Use when estimating Data Share costs, managing invitations/RBAC, cross-region deployments, dataset mapping, or automation, and other Azure Data Share related development tasks. Not for Azure Data Box (use azure-data-box-family), Azure Import Export (use azure-import-export), Azure Open Datasets (use azure-open-datasets), Azure Data Explorer (use azure-data-explorer).

Build production-ready systems with stability patterns: circuit breakers, bulkheads, timeouts, and retry logic. Use when the user mentions "production outage", "circuit breaker", "timeout strategy", "deployment pipeline", "chaos engineering", "bulkhead pattern", "retry with backoff", or "health checks". Also trigger when designing resilient microservices, planning zero-downtime deployments, or investigating cascading failure scenarios. Covers capacity planning, health checks, and anti-fragility patterns. For data systems, see ddia-systems. For system architecture, see system-design.

Analyze engineering delivery throughput, hiring funnel health, team structure, and production discipline for startup VPEs and founders.

Check and manage Azure quotas and service limits across resource providers and regions for deployment planning and capacity validation.

Manage Azure API Center resources including APIs, versions, definitions, deployments, and metadata using the Python management SDK.

Manage Azure API Center resources including services, workspaces, APIs, versions, definitions, environments, and deployments using the .NET SDK.

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

Design, deploy, and operate production-ready software with stability patterns, capacity planning, and zero-downtime releases.

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

Adopt Bun as a JavaScript runtime, package manager, bundler, and test runner, including migration from Node and Vercel deployment.

Coordinates five specialized agents (planning, research, code, review, deploy) into a pipeline that ships features from spec to production with automated gates.

Track ML experiments, manage the model registry with versioning, deploy models, and reproduce experiments using MLflow's framework-agnostic platform.

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

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

Deploy static websites to IPFS with a single command using the PinMe CLI, auto-detecting the build directory and returning a preview URL.

Manages CDK for Terraform projects: synthesizes HCL, deploys stacks, inspects outputs, and analyzes diffs across TypeScript, Python, Go, Java, or C#.

Build and release pipeline for the Pump SDK — tsup TypeScript builds, Cargo release profiles, semantic release with commitizen, npm publishing, linting, Makefile targets, Vercel deployment, and MCP server distribution.

Add official Railway database services (Postgres, Redis, MySQL, MongoDB) to a project, check for existing databases, and connect them to other services.

Assess and manage Azure service quotas and limits to prevent deployment and scaling failures. Use this skill when users ask about quota errors, capacity planning, regional availability, or resource limits.

Generate production-grade Kubernetes manifests — Deployments with probes and security contexts, Services, Ingress with TLS, HPA, PDB, NetworkPolicy, ConfigMaps, Secrets — with optional Helm charts, Kustomize overlays, Istio mesh, and ArgoCD GitOps

Manages Agent Platform serving endpoints: create, list, describe, update, delete, and troubleshoot permission, quota, and resource busy errors.

Convert per-page styled HTML prototypes into Edge Delivery Services blocks and content pages, then deploy via DA.

Guides monitoring and observability setup for Qdrant vector search deployments, including Prometheus scraping, health checks, and metric-based debugging of production issues.

Automates security scanning for Infrastructure as Code templates using Checkov, tfsec, and KICS to detect misconfigurations before deployment.

Creates Dockerfiles, configures CI/CD pipelines, writes Kubernetes manifests, and generates Terraform/Pulumi infrastructure templates for deployment automation, GitOps, and incident response.

Turns model work into a production ML system with data contracts, reproducible training, quality gates, deployable artifacts, and monitoring.