Skill UI

Automates guidance for setting up and optimizing BigQuery scheduled queries within GCP, offering best practices, configuration templates, and validation for production-ready data workflows.

Automates BigQuery table creation by guiding GCP best practices, generating ready-to-deploy configurations, and validating resources whenever you trigger the BigQuery table creator skill.

Cloud Architect Blueprint provides guidance for designing resilient AWS, Azure, and GCP topologies, planning secure migrations, tightening zero-trust controls, optimizing costs, and orchestrating disaster recovery across multi-region deployments.

Automates guidance, code, and configuration for Google Cloud Function scenarios, helping engineers follow best practices for compute, storage, BigQuery, Vertex AI, and other GCP services.

Guides GCP cloud monitoring alert tasks by detailing steps, configs, production-ready code, and validation whenever alert-related requests arise for compute, storage, BigQuery, Vertex AI, or native services.

Automates Cloud Run service configuration within GCP, providing step-by-step guidance, best practices, ready-to-deploy configs, and validation for compute, storage, BigQuery, and Vertex AI workflows.

Guides GCP users through automating Cloud Scheduler job creation with best practices, ready-to-run code, and validation, ideal for implementing cron-driven workloads across compute, storage, BigQuery, Vertex AI, and Cloud Run.

Automated Cloud SQL setup guidance that activates within GCP Skills and delivers step-by-step configuration, production-ready code, and validation against best practices for compute, storage, BigQuery, Vertex AI, and other GCP services.

Automates guidance for setting up Cloud Tasks queues across GCP workloads, covering patterns, best practices, and vetted configs.

This skill provides expert guidance for modern, multi-cloud database administration. It covers comprehensive knowledge across AWS, Azure, and GCP platforms, spanning relational, NoSQL, and graph databases. Key areas include Infrastructure as Code (Terraform, Flyway), achieving high availability, disaster recovery, advanced performance optimization, and ensuring strict regulatory compliance (HIPAA, GDPR). It is essential for managing complex, highly reliable cloud data architectures.

This skill defines a senior engineer specializing in the entire software development lifecycle (SDLC). It covers building robust CI/CD pipelines (e.g., GitHub Actions), containerizing applications with Docker, and managing infrastructure using Infrastructure as Code (IaC) tools like Terraform or Pulumi. Key areas include Kubernetes deployment (GitOps), cloud platform configuration (AWS/GCP/Azure), release automation, and incident response planning.

Comprehensive guide for deploying Evernote integrations to robust production environments across major cloud platforms (AWS, GCP, Kubernetes). It covers advanced practices including multi-stage Docker builds, secure secrets management via Secret Manager, serverless function setup (Lambda), and configuring necessary health checks and CI/CD pipelines. Ideal for transitioning from testing to live deployment.