Google Cloud Platform
Official@googlecloudplatform
Offers specialized infrastructure orchestration, Kubernetes resource management, and high-performance storage benchmarking for enterprise cloud environments.
Agent Skills by Google Cloud Platform
Showing 68 vetted skills indexed across 6 GitHub repositories.
genai-sdk
Guides Gemini API usage on Vertex AI with the Gen AI SDK across five languages.
quality-flywheel
Evaluate and improve GenAI models and agents using the Google GenAI Evaluation SDK.
vertex-ai
Routes Vertex AI tasks to deployment, inference, tuning, or Gen AI SDK sub-skills.
liveapi-service
Generates a LiveAPI websocket client service class in the user's chosen programming language.
update-terraform-fields
Guides updating Terraform-controller-managed KCC resources and patching the vendored Terraform Google Beta provider.
kcc-direct-base-types-implementer
Enforces baseline standards for KCC direct resource type definitions in Go.
solve-migration-diff-issues
Diagnoses and fixes takeover diffs when migrating KCC controllers from Terraform/DCL to Direct.
kcc-direct-controller-logic-brownfield
Implements Adapter reconciliation logic and E2E fixtures for direct controllers migrating from legacy.
update-client-library-version
Updates Google Cloud Go client libraries across Config Connector modules and validates fuzz tests.
reviewgen-legacy-feature
Reviews pull requests that add or modify features in legacy Terraform and DCL resources.
create-fuzzer
Implement round-trip KRM fuzzers for Config Connector direct controllers.
crd-mapper-fuzzer-existing-type
Generates direct KRM Go types for existing CRDs while preserving strict schema compatibility.
crd-mcp-server
Validates CRD schema changes for structural equivalence and backward compatibility against git references.
kcc-direct-controller-logic-greenfield-implementer
Implements direct controller reconciliation logic and E2E fixtures for KCC Greenfield resources against real GCP.
reviewgen-greenfield-controller
Reviews pull requests adding controllers for KCC Greenfield resources against defined criteria.
kcc-direct-mockgcp-implementer
Implements and aligns MockGCP services for direct KCC resources against real GCP logs.
test-terraform-fields
Validates Config Connector resource fields by recording golden HTTP logs against real GCP and MockGCP.
move-pr-forwards
Analyzes GitHub PR status, approver feedback, and failing CI logs to unblock pull requests.
kcc-direct-brownfield-types-implementer
Generates KRM types and CRD scaffolding for migrating existing Config Connector resources to direct controllers.
update-go-version
Updates Go and toolchain versions across modules, workspaces, Dockerfiles, and setup scripts.
add-export-support
Implements export support for Config Connector direct controllers via AdapterForURL.
update-tf-provider-for-resource
Backports and aligns KCC's vendored Terraform Google Beta provider code with upstream while preserving local patches.
reviewgen-brownfield-new-types
Reviews pull requests adding new KCC types for Brownfield GCP resources against defined criteria.
reviewgen-greenfield-new-types
Reviews pull requests adding new KCC types for Greenfield GCP resources against defined criteria.
Frequently Asked Questions About Google Cloud Platform
FAQPage SchemaWhat specific infrastructure tasks can be managed using these capabilities?▼
These capabilities enable automated GKE cluster provisioning, Spanner instance deployment, and GCSFuse performance benchmarking. Users can scaffold Kubernetes resource definitions, manage SSH multiplexing for compute instances, and validate storage bucket configurations across distributed environments.
Which technical personas are the primary users of these resources?▼
The primary users are Site Reliability Engineers, Cloud Infrastructure Architects, and Platform Engineers. These professionals utilize the manifest to manage Kubernetes-based resource controllers, perform system-level performance diagnostics, and maintain rigorous e2e testing standards for cloud-native applications.
What are the prerequisites for executing these infrastructure management tasks?▼
Execution requires an active Google Cloud project, configured authentication for the relevant service APIs, and a local environment capable of running Kubernetes-native manifests. Specific tasks like GCSFuse benchmarking also require pre-provisioned GCE or GKE compute resources with appropriate storage buffer configurations.