GCP buckets are logical containers for your data. There is no limit to the number of buckets you can create; each bucket can hold any amount of data. Learn more.
GCP buckets form the foundation of how data is stored, secured, and scaled
in Google Cloud.
A GCP bucket is the core building block for object storage, defining how data is organized, accessed, and managed across cloud workloads.
GCP buckets support virtually unlimited scale, global uniqueness, and flexible configuration for storage class, location, and access control.
A google cloud storage bucket enables you to store unstructured data reliably while applying encryption, lifecycle policies, and governance controls.
Integrate monitoring and hybrid observability to optimize GCP bucket cost, performance, and resilience.
Google Cloud Platform (GCP) Storage uses buckets to store data. A GCP bucket is the primary resource for organizing and managing data in Cloud Storage. GCP buckets support virtually any data type including files, photos, videos, backups, or application assets.
Essentially, GCP buckets are logical containers for your data and when paired with container monitoring, they become a key part of managing modern cloud workloads. You can create as many buckets as you need, and each one can scale to hold an unlimited amount of data.
In this article, we’ll discuss what a GCP bucket is, why it matters, how to create and access one, and how to use it effectively in your cloud environment.
What is bucket storage in cloud computing?
In Google Cloud Platform, the Cloud Storage data model is built around buckets. A GCP bucket is a globally unique container that holds your data and provides a flat namespace for storing objects. These buckets help you to organize, store, and retrieve data using familiar tools like the Google Cloud Console, gsutil command-line tool, or client libraries similar to how you’d manage data in other cloud storage systems.
Why is a GCP bucket important?
You can create buckets in GCP Storage using the Buckets resource. All buckets share a single global namespace, which means each bucket name must be globally unique across all projects.
A GCP bucket is important because:
It acts as a container for objects – An object contained in GCP buckets has its own methods for interacting with it, such as reading, writing, or updating.
It enables fine-grained access control – A bucket contains bucket AccessControls, which allow fine-grained manipulation of the access controls for an existing bucket. This can be used to define who can read or modify data at both the bucket and object level.
It defines key storage settings – When you create a bucket, you also define its storage class, location, and other configuration options that apply to all objects stored within it. You can also enable features like autoclass, which automatically transitions objects between storage classes based on access patterns.
How do you create buckets in GCP?
When creating a GCP bucket, specify the name and access permissions. Buckets are created using the Buckets resource in Google Cloud Storage.
In the Google Cloud Console, navigate to the Cloud Storage Buckets page. Then, select “Create” to start the bucket creation process. When you’ve entered all your GCP bucket information, select “Continue.” Then, as you name your bucket, enter a name that meets the following requirements:
Bucket names must use only lowercase letters, numbers, hyphens (-), and dots (.).
Underscores and spaces are not allowed.
The name must begin and end with a letter or number.
Bucket names must be 3 to 63 characters long.
For domain-named buckets using dots, the name can be up to 222 characters, with up to 63 characters between consecutive dots.
You cannot use a string in IP address format (e.g., 192.168.0.1).
The bucket name cannot contain the “goog” prefix.
You cannot use a misspelling or derivative of “google,” such as “g00gle”.
The next step is to determine where your data will be stored. Select a Location type and a Location to indicate where you want to store the GCP bucket data. You’ll also select a default storage class for the data in your bucket. This storage class is assigned to all objects uploaded to your GCP bucket unless specified otherwise.
Based on your selected storage class and location, as well as your expected operations and data size—the Monthly cost estimate panel in the right pane will estimate the bucket’s monthly costs.
To control access to your GCP bucket objects:
Determine whether you’ll enforce public access prevention. If your project’s organization policy already enforces this, the Prevent Public Access toggle will be locked.
Select the Access control model for the bucket’s objects, either Uniform (recommended) or Fine-grained.
Before finalizing the bucket, select a data encryption method. You can use the default Google-managed encryption keys, or choose customer-managed or customer-supplied keys if your security requirements demand more control.
You can also optionally configure data protection features, such as object versioning, retention policies, soft delete, or bucket lock. These are not required but may be useful for compliance or recovery purposes.
You can also automate bucket creation and configuration using terraform, which makes it easy to manage infrastructure as code.
Once your settings are complete, click “Create” to finish provisioning your GCP bucket.
How do you access buckets in GCP?
You can access a GCP bucket using the Google Cloud Console, the gsutil command-line tool, client libraries (e.g., Python, Java), or REST APIs. Buckets are part of a GCP project, and access to them is controlled through Identity and Access Management (IAM) permissions.
If a user or service account from a different project or organization needs access, the appropriate permissions (such as roles/storage.objectViewer or roles/storage.admin) must be granted explicitly on the bucket or project level.
Object data can also include custom metadata datasets, which helps with indexing, filtering, and programmatic access control.
How can you use Google Cloud Storage?
Google Cloud Storage is a highly durable and scalable object storage service used to store unstructured data. You can use it to:
Store and serve static assets such as images, videos, and documents
Back up files, databases, or virtual machine snapshots
Archive logs and compliance data for long-term retention
Host data lakes for analytics and machine learning workflows
Share data securely across projects, teams, or organizations
Cloud Storage is designed for high availability and redundancy, so your data is protected from loss or damage even in the event of hardware failures or regional outages. For high-performance workloads, adding a cache layer can accelerate access to frequently used data.
What objects can buckets contain?
Google Cloud Storage allows you to store virtually any type of file as an object such as documents, images, videos, backups, logs, and structured data formats like JSON, XML, or Protocol Buffers. There are no file type restrictions, and each object can be up to 5 TB in size. Buckets in GCP are designed for scalable, reliable object storage. Therefore they are suitable for a wide range of unstructured data workloads.
GCP buckets use a flat storage model, meaning objects aren’t stored in real folders. However, you can organize objects by using structured names with separators (such as logs/2024/event.json), which creates a folder‑like view in the console and tools. This naming approach helps manage large datasets by mimicking a hierarchical namespace, even though the underlying storage remains flat.
Final thoughts
Buckets in GCP are fundamental containers for storing data in the cloud. Every object you upload, whether it’s a file, backup, or log, is stored inside a bucket. While buckets may appear similar to folders in a file system, they use a flat object storage model and do not support traditional directory hierarchies.
Buckets can be deleted when empty, unless restricted by retention policies. Despite some structural differences from file systems, they remain essential for organizing data, managing access, and enforcing lifecycle and security controls in Google Cloud Storage.
FAQs
What’s the difference between a GCP bucket and a regular folder?
A GCP bucket isn’t exactly like a folder, it’s a high-level container for objects, not a file directory. While folders organize files within a computer, buckets are designed for scalability and remote access, often holding millions of files with different permissions and rules.
How should I choose a storage class when creating a bucket?
Your storage class depends on how frequently you need to access the data. Standard is for active data, Nearline and Coldline are for less frequent access, and Archive is for long-term storage. Choosing the right class impacts both cost and performance.
What happens if I delete all files in a bucket, can I delete the bucket itself?
Even with all files removed, some settings or access configurations might prevent deletion. Also, buckets with retention policies or active links may not be deletable right away. Double-check access control and lifecycle rules before trying to remove the bucket.
Can I make my GCP bucket completely private?
Yes. You can enforce public access prevention and set fine-grained or uniform access control to allow only authorized users or service accounts to access the contents.
What types of files can I store in a GCP bucket?
Object storage in GCP is format-agnostic, you can store photos, videos, documents, backups, logs, and structured data like JSON or XML. There’s no restriction on file type, only object size limits (5 TB per object).
How does data encryption work in GCP buckets?
By default, all data is encrypted at rest using Google-managed keys. You can also choose customer-managed or customer-supplied encryption keys during bucket setup if your security requirements need more control.
