Results for “dep”

Operate Firebase from the terminal with `firebase-tools`: install/auth the CLI, bootstrap `firebase.json` / `.firebaserc`, run the Emulator Suite, deploy Hosting / Functions / rules / App Hosting, manage preview channels, and handle Firebase admin tasks like auth import/export, Remote Config, App Distribution, and Extensions. Use when the job is Firebase platform/project operation through the CLI. Triggers on: firebase deploy, firebase init, firebase emulators, firebase hosting, firebase functions, firebase firestore, firebase database, firebase auth import, firebase remote config, firebase app distribution, firebase extensions, firebase apphosting, firebase dataconnect, firebase cli, firebase-tools, deploy firebase, firebase preview channel, firebase login, firebase use, firebase target apply. Route backend AI workflow orchestration to `genkit` and direct in-app SDK integration to `genkit` (`client-ai-logic` mode).

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

Deploys the vss-video-analytics-api REST service standalone with config, data-log bind, and optional Elasticsearch/Kafka connectivity.

Set up Cloudflare Turnstile end-to-end: create a widget, deploy a managed siteverify Worker, insert frontend snippets, and validate the integration.

Apply design, canon, and modules to every page in the inventory to produce a deployable static HTML site. Per-page, incremental, and idempotent.

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

Deploy DefectDojo as a centralized vulnerability management dashboard with scanner integrations, deduplication, metrics tracking, and Jira ticketing workflows.

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.

Consolidates 89 high-integrity SOPs for the Full department of the Galyarder Framework, covering adapter creation, execution protocols, and multi-agent hygiene.

Guides containerizing apps with Docker Compose, optimizing Dockerfiles, and deploying to Kubernetes, with a focus on turning these tasks into a paid service.

Evaluates a containerized framework for deploying distributed big data workloads, measuring execution time and cloud cost scaling from four to eight nodes.

You are an advanced Docker containerization expert with comprehensive, practical knowledge of container optimization, security hardening, multi-stage builds, orchestration patterns, and production deployment strategies based on current industry best practices.

Diagnose and configure compound-engineering environment. Checks CLI dependencies, plugin version, and repo-local config. Offers guided installation for missing tools. Use when troubleshooting missing tools, verifying setup, or before onboarding.

Expert knowledge for Azure Policy development including troubleshooting, best practices, decision making, security, configuration, integrations & coding patterns, and deployment. Use when authoring Machine Configuration packages, deploying via ARM/Bicep/Terraform, mapping CIS/NIST baselines, migrating from DSC, or querying compliance with Resource Graph, and other Azure Policy related development tasks. Not for Azure Blueprints (use azure-blueprints), Azure Role-based access control (use azure-rbac), Azure Resource Manager (use azure-resource-manager), Azure Security (use azure-security).

Generates CI/CD pipelines, Terraform modules, and Kubernetes deployment manifests with health-check gates and rollback support for AWS, GCP, and Azure.

Plan and execute zero-downtime migrations for databases, services, and infrastructure with automated compatibility validation and rollback strategy generation.

Export OpenTelemetry traces, metrics, and logs to Azure Monitor/Application Insights using the deprecated exporter or the recommended autoconfigure package.

Deploy the behavior-analytics service standalone with a chosen entrypoint, config source, and optional calibration, without the full warehouse stack.

Audits local code for production readiness, identifying risks in security, data integrity, payments, operations, and UX before shipping.

Runs a multi-phase verification pipeline for Laravel projects including environment checks, linting, static analysis, tests with coverage, security scans, and deployment readiness.

Improve cache efficiency, latency, and throughput for AMS deployments using the Adobe Dispatcher Apache HTTP Server module and related HTTPD configuration.

Reviews AWS infrastructure as code and deployed resources against the Well-Architected Framework, generating findings and GitHub issues for remediation.

Integrate gitleaks and trufflehog into CI/CD pipelines to detect leaked secrets before deployment.

Identifies security vulnerabilities, generates structured audit reports with severity ratings, and provides actionable remediation guidance for code, infrastructure, and cloud environments.

Provides expert guidance for using n8n-mcp MCP server tools to build, validate, and manage n8n workflows efficiently.

Interrogates a plan against real third-party documentation, extracting hard constraints and asking doc-cited questions before producing a constraints appendix.

Manage Uncloud clusters with the `uc` CLI: bootstrap machines, deploy Compose services, publish ports, configure Caddy ingress, scale, inspect logs, and manage volumes.

Skill for working with Firebase Hosting (Classic). Use this when you want to deploy static web apps, Single Page Apps (SPAs), or simple microservices. Do NOT use for Firebase App Hosting.

Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling.

Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling.

Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling.

Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling.

Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling.

Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling.

Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling.