'gcp' 검색 결과

Use when working with Gcp Idle Resources — detect unused and idle GCP resources that incur cost without providing value. Covers unattached Persistent Disks, unused external IPs, stopped VMs, idle Cloud NAT, idle load balancers, old snapshots, idle Cloud SQL instances, abandoned GKE node pools, unused VPC connectors, and orphaned Filestore instances. Includes estimated monthly waste per resource and anti-hallucination rules for safe detection.

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Expert en infrastructure GCP (GKE, Cloud Run, BigQuery, Pub/Sub, Firestore, Cloud Functions)

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Implementing and auditing GCP VPC firewall rules to enforce network segmentation, restrict ingress and egress traffic, apply hierarchical firewall policies across the organization, and monitor firewall rule effectiveness using VPC Flow Logs.

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Implement GCP Binary Authorization to enforce Dağıt:-time security controls that ensure only trusted, attested container images are Dağıtılmış to Google Kubernetes Engine and Cloud Run.

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Performing comprehensive security assessments of Google Cloud Platform environments using Forseti Security, Security Command Center, and gcloud CLI to audit IAM policies, firewall rules, storage permissions, and compliance against CIS GCP Foundations Benchmark.

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Implement GCP Organization Policy constraints to enforce security guardrails across the entire resource hierarchy, restricting risky configurations and ensuring compliance at organization, folder, and project levels.

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Responds to security incidents in cloud environments (AWS, Azure, GCP) by performing identity-based containment, cloud-native log analysis, resource isolation, and forensic evidence acquisition adapted for ephemeral cloud infrastructure. Activates for requests involving cloud incident response, AWS security incident, Azure compromise, GCP breach, cloud forensics, or cloud identity compromise.

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Responds to security incidents in cloud environments (AWS, Azure, GCP) by performing identity-based containment, cloud-native log analysis, resource isolation, and forensic evidence acquisition adapted for ephemeral cloud infrastructure. Activates for requests involving cloud incident response, AWS security incident, Azure compromise, GCP breach, cloud forensics, or cloud identity compromise.

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Create a Google Model Armor template for checking AI prompts and responses. Specify a Google Cloud project, location, and template ID, then use a preset or provide custom settings in JSON.

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• Creating a template with the jailbreak preset
• Defining template settings in JSON
• Preparing a template for prompt and response checks

Design and operate shared secret storage with HashiCorp Vault or cloud services. The skill guides access policies, automated credential rotation, temporary credentials, audit analysis, and secret delivery to applications and deployment pipelines.

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• Setting up Vault or a cloud secret store
• Automating database password and API key rotation
• Auditing access to secrets

Investigate Google Cloud network problems using traffic logs, performance metrics, and connection path tests. Identify blocked traffic, packet loss, and latency, summarize traffic volumes, or estimate VPC Flow Logs costs.

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• Investigate blocked traffic and packet loss
• Check latency and throughput trends
• Analyze Cloud NAT port exhaustion

Prepare and run Google Cloud CLI commands with syntax checks, explicit project and location settings, and focused output. Guides agents through change previews and authorization requirements for destructive operations and sensitive infrastructure changes.

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• Check command syntax and flags before execution
• List cloud resources with only the fields needed
• Review infrastructure changes before running commands

Find and manage agent skills in the Gemini Enterprise Agent Platform Skill Registry, a catalog of available capabilities. The skill supports searching, uploading, updating, deleting, inspecting revision histories, checking operation status, and creating local starter files.

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• Search for skills that provide a needed capability
• Upload or update skills in the registry
• Inspect skill details and revision histories

Build Cloud Monitoring requests from metric definitions and resource details. Generate JSON parameters, filters, and aggregation settings for retrieving time series data, then validate the request against the live API.

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• Build JSON requests to retrieve monitoring data
• Filter metrics for specific VMs or databases
• Set aggregation intervals and resource grouping

Plan and operate Google Cloud Platform infrastructure using services such as Cloud Run and GKE, Google's managed Kubernetes service. Get guidance on deployment, access permissions, networking, monitoring, and cost controls for the system's requirements.

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• Planning an API with Cloud Run and Cloud SQL
• Reviewing GKE access permissions
• Designing event processing with Pub/Sub

Investigate how credentials can be exposed in CI/CD, the systems that build and deploy software. Covers environment variables, logs, credential stores, cloud trust settings, and runner tokens, with methods to assess access scope and defensive controls.

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• Review secret exposure in build environments
• Search build logs and caches for leaked credentials
• Assess trust settings between pipelines and cloud services

Assess Kubernetes security from an existing pod or API access point. Covers permission checks, exposed node services, secrets, host access, and cloud metadata to explain how configuration weaknesses can expand access across a cluster.

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• Review service account permissions and RBAC settings
• Assess host access and secrets exposure from pods
• Trace access paths from a cluster to cloud infrastructure

Draft case reports, diagnostic reports, clinical trial reports, and patient records using document-specific structures and templates. The skill guides completeness checks, patient de-identification, and documentation aligned with named clinical reporting guidelines and regulatory frameworks.

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• Drafting case reports for journal submission
• Organizing radiology, pathology, and laboratory reports
• Preparing clinical trial and serious adverse event reports

Migrate workloads from Microsoft Azure to AWS. Triggers on: migrate from Azure, Azure to AWS, move off Azure, migrate AKS to EKS, migrate App Service or Azure VMs to AWS compute, migrate Azure SQL or Azure Database to RDS, migrate Cosmos DB to DynamoDB, migrate Azure OpenAI to Bedrock, move Azure AI or agentic workloads to AWS, estimate AWS costs for my Azure infrastructure, what-if workshop. Runs a 6-phase process: discover Azure resources from Terraform, the live `az` CLI, app code, and billing exports, then clarify, design, estimate costs, optionally reprice scenarios, generate artifacts, and collect feedback. Clarify gates Design, Estimate, and Generate; Generate is opt-in at the post-Estimate decision gate. Bicep/ARM discovery is not yet implemented; a Bicep/ARM-only workspace halts. Do not use for: GCP migrations (see gcp-to-aws), Heroku migrations (see heroku-to-aws), general AWS architecture advice (see architect-for-startups), AWS-to-Azure reverse migration, or Azure-to-Azure refactoring.

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Use when the user wants to migrate code that calls OpenAI, Gemini/Google AI, or the Anthropic API to Amazon Bedrock — a pure model/SDK rewrite. End-to-end: assesses the codebase, rewrites SDK calls, evaluates output quality against Bedrock, and delivers a ready-to-merge git branch. Also has an access-only mode for checking or enabling Bedrock model access for specific models (e.g. 'request access to Claude on Bedrock', 'which models do I turn on') with no code migration — it checks each model and walks the right access step, then stops. Not for agent runtime selection or agent migration planning (use agent-advisor), nor standalone cost estimates or infra-only migration. The full migration REQUIRES gcp-to-aws OR azure-to-aws installed alongside this skill (gcp-to-aws preferred when both are present); access-only mode needs neither.

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AWS-curated copy-paste prompts for AI coding agents (MVP scaffolding, RAG chatbot with Claude on Bedrock, security baseline evaluation, cost anomaly detection, GPU quota requests, EKS deployment, Well-Architected review, etc.) plus downloadable installable agents (Multi-Account Transition Advisor, Bill Shock Preventer, Service Quota Agent, Bedrock Model Availability Agent, AWS DB Advisor). Use when the user asks for a prompt to do X on AWS, wants an installable agent for multi-account / cost monitoring / quota management / Bedrock model availability / database selection, or asks how to use AWS prompts. For migration intent (GCP to AWS, Azure to AWS, OpenAI/Gemini to Bedrock), route to the migration skills in this plugin (`gcp-to-aws`, `azure-to-aws`, `heroku-to-aws`, `llm-to-bedrock`). Do not use for: factual AWS Activate / programs / credits questions, learn articles, sample architectures, or for prompts that are not in the bundled `references/prompt-library/` tree.

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Migrate workloads from Heroku to AWS. Triggers on: migrate from Heroku, Heroku to AWS, move off Heroku, migrate Heroku Postgres to RDS, migrate Heroku Redis to ElastiCache, migrate Heroku Kafka to MSK, migrate dynos to Elastic Beanstalk, migrate dynos to Fargate, migrate Heroku Private Space, Heroku to ECS, leave Heroku, what-if workshop, compare migration scenarios, workshop mode. Runs a 6-phase process: discover Heroku resources live via the authenticated Heroku CLI (read-only, consent-gated) and/or from Terraform, Procfile/app.json, and billing exports, then clarify, design, estimate costs, generate artifacts, and collect feedback. Clarify must finish before Design, Estimate, or Generate. An optional post-Estimate what-if workshop reprices region/HA/compute/Graviton scenarios. Do not use for: GCP migrations (see gcp-to-aws), Azure migrations (see azure-to-aws), AWS-to-Heroku reverse migration, general AWS architecture advice without migration intent, or Heroku-to-Heroku refactoring.

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Startup-tailored AWS architecture advice for non-agent workloads, adjusted to the company's stage (pre-revenue through Series B+), team size, runway, and credits. Not for AI agents: deploying an AI agent on AWS, picking its runtime, or any agentic architecture is agent-advisor. Use when a founder wants guidance or a recommendation rather than code changes: which services to choose, how to plan or review an architecture, how to stretch credits and control cost, or how to prepare architecture for a fundraise or technical diligence. For an interactive discovery flow that scaffolds and writes the architecture into the codebase, use start-building-for-startups. Do not use for: writing or scaffolding code, factual AWS Activate / programs / credits lookups (see knowledge-base-for-startups), a single copy-paste prompt (see prompt-library-for-startups), or migration intent such as GCP-to-AWS, Azure-to-AWS, or Heroku-to-AWS (see the migration skills: `gcp-to-aws`, `azure-to-aws`, `heroku-to-aws`, `llm-to-bedrock`).

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Interactive discovery + implementation workflow that gathers requirements through picker-based questions (intent, scope, constraints, preferences), scans the codebase for what it can already infer, then writes an AWS architectural scaffold and implementation directly into the project. Use when the user wants to build a new app, scaffold a project, or expand/refactor an existing one on AWS — anything that calls for a structured discovery flow followed by code changes, not a one-off lookup. Do not use for: factual lookups about AWS Activate / programs / credits, requests for a single copy-paste prompt, non-AWS architectural work, architecture advice/recommendations without code changes (see architect-for-startups), a new idea centered on an AI agent — runtime selection, agentic architecture, or an agent POC (see agent-advisor), or migrating an existing GCP/Azure/Heroku workload or an LLM SDK rewrite (see gcp-to-aws / azure-to-aws / heroku-to-aws / llm-to-bedrock).

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