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Found 136 Skills
Operate the Google Cloud gcloud CLI safely and effectively. Authenticates users, reads cloud resource state freely for debugging and exploration, and creates, updates, or deletes resources only after explicit user confirmation. Use when working with gcloud, Google Cloud CLI, GCP resources, cloud debugging, reading logs, managing Compute Engine, Cloud Run, Cloud Functions, GKE, IAM, networking, Cloud Storage, Cloud SQL, Pub/Sub, or when the user mentions any gcloud command, Google Cloud project, or needs to authenticate with GCP.
Develops and executes Spark code on Dataproc Clusters and Serverless. Reads and writes data using BigLake Iceberg catalogs, BigQuery and Spanner. Debugs execution failures. Use when: - Writing Spark ETL pipelines on GCP. - Training or running inference with ML models with spark on GCP. - Managing Spark clusters, jobs, batches, and interactive sessions. Don't use when: - Writing generic Python scripts that don't use Spark. - Performing simple SQL queries that can be done directly in BigQuery.
Provides guidance for writing, packaging and executing Apache Beam pipelines on GCP using Cloud Dataflow. Use when: - Creating an Apache Beam Dataflow pipeline. - Creating a Google Flex Template.
Analyzes GCP costs and provides optimization recommendations including committed use discounts, rightsizing, and unused resources. Use when optimizing GCP spending or analyzing GCP costs.
Grafana Cloud private network connectivity — AWS PrivateLink, Azure Private Link, and GCP Private Service Connect. Send telemetry (metrics, logs, traces, profiles) to Grafana Cloud without traversing the public internet. Eliminates cloud egress costs, meets compliance requirements (PCI-DSS, HIPAA). Use when setting up secure private telemetry ingestion from AWS/Azure/GCP, reducing egress costs, or meeting data residency/compliance requirements.
Deploy and manage Google Kubernetes Engine clusters. Configure node pools, networking, and workload identity. Use when running Kubernetes on GCP.
Deploy telecine services to GCP Cloud Run via Pulumi, publish elements packages to npm, publish skills docs, rollback, scale resources, manage secrets, and debug failed deployments.
Migrate workloads from Google Cloud Platform to AWS — including AI and agentic workloads regardless of cloud provider. Triggers on: migrate from GCP, GCP to AWS, move off Google Cloud, migrate Terraform to AWS, migrate Cloud SQL to RDS, migrate GKE to EKS, migrate Cloud Run to Fargate, Google Cloud migration, migrate from OpenAI to Bedrock, move off OpenAI, switch from ChatGPT API to AWS, migrate from Gemini to Bedrock, migrate LangChain to Bedrock, migrate LangGraph to AWS, migrate agentic workloads to AWS, move AI workloads to AWS, migrate my AI app to AWS. Runs a 6-phase process: discover GCP resources from Terraform files, app code, or billing exports, clarify migration requirements, design AWS architecture, estimate costs, generate migration artifacts, and collect optional feedback. Clarify must finish before Design, Estimate, or Generate. Includes AI provider migration guidance (for example, OpenAI to Amazon Bedrock) by selecting closest-fit Bedrock model families for required modality, latency/quality targets, context windows, and cost constraints. Model mapping is compatibility-guided, not 1:1 parity; validate prompts, tool-calling behavior, and eval metrics before cutover. Do not use for: Azure or on-premises migrations to AWS, AWS-to-GCP reverse migration, general AWS architecture advice without migration intent, GCP-to-GCP refactoring, or multi-cloud deployments that do not involve migrating off GCP.
Processes GCP infrastructure design and deployment workflows within Application Design Center (ADC). Use when: - Designing GCP infrastructure with Terraform. - Validating local HCL. - Performing best-practice plan scans. - Importing templates to Application Design Center (ADC). - Deploying templates. - Troubleshooting deployment failures. Boundaries: - Only use for GCP-specific cloud infrastructure. - Only use for Terraform coding within the ADC context.
Processes GCP infrastructure design and deployment workflows. Use when: - Designing GCP infrastructure with Terraform. - Validating local HCL. - Performing best-practice plan scans. - Importing templates to Application Design Center (ADC). - Deploying templates. - Troubleshooting deployment failures. Don't use for non-GCP cloud providers, or general Terraform coding outside the ADC context.
Manage Compute Engine instances and instance templates. Configure managed instance groups and preemptible VMs. Use when deploying compute resources on GCP.
Provision Cloud SQL and Spanner databases. Configure high availability, backups, and security. Use when deploying managed databases on GCP.