What problem does it solve? Working with Google Cloud Storage involves many surfaces — the gcloud CLI, JSON and XML APIs, client libraries, Terraform, and MCP servers — each with its own commands, authentication patterns, and pitfalls. This Skill consolidates the correct, current way to perform any Cloud Storage operation so you avoid deprecated tools like gsutil and misconfigured buckets. ## Core Features & Use Cases - Bucket and Object Operations: Create, configure, list, upload, download, and delete buckets and objects using gcloud storage, the JSON API, or MCP tools. - Security and Data Protection: Configure IAM roles, uniform bucket-level access, public access prevention, signed URLs, encryption (CMEK/CSEK), versioning, soft delete, retention policies, and Bucket Lock. - Cost and Performance Optimization: Apply storage classes, lifecycle rules, Autoclass, Storage Transfer Service migrations, Rapid Buckets, Rapid Cache, and GCSFuse mounts for AI/ML workloads. - Use Case: Migrate terabytes of data from Amazon S3 into a GCS bucket, then mount that bucket on a GKE cluster with gcsfuse so a PyTorch training job can read the dataset with local-file semantics. ## Quick Start Ask the assistant to create a Cloud Storage bucket in a specific region and upload a local file to it.