Object storage is a method for storing large amounts of unstructured data (think images, videos, documents, backups, application assets, and datasets) as individual units called ‘objects’.
Unlike traditional file storage, which organizes files into folders and directories, or block storage, which divides data into fixed-size blocks, object storage keeps each piece of data as a self-contained object with its own data, metadata, and unique identifier.
This architecture makes object storage particularly well-suited for cloud applications and workloads that need to store and retrieve very large amounts of data efficiently.
What is the object storage architecture?
Object storage is a storage architecture designed to manage data as objects rather than files or blocks.
An object typically consists of three things:
The data itself, such as an image, video, document, software package, or dataset
Metadata describing the object
A unique key or identifier applications use to locate and retrieve it
Objects are generally placed inside logical containers commonly called buckets. Instead of navigating a traditional file system hierarchy, applications interact with the storage service through an API.
Object storage is particularly useful for unstructured data: information that doesn't naturally fit into rows and columns in a traditional relational database. Examples include media libraries, user uploads, log files, AI datasets, backups, and static application assets.
How does object storage work?
At a high level, object storage separates the application from the physical details of where and how its data is stored.
The process typically works like this:
An application creates an object. The application sends data to the object storage service through an API.
The object is assigned a key. That key uniquely identifies the object within its bucket or namespace. (Think of this like giving a file a label or name).
The storage platform stores the data and metadata. The system handles the underlying infrastructure required to retain the object.
The application requests the object when needed. Instead of looking for a file at a traditional filesystem path, the application makes an API request using the bucket and object key.
The storage service returns the object. That object can then be processed by an application, delivered through a CDN, downloaded by a user, or used by another service.
With Fastly Object Storage, developers create buckets and use access credentials to interact with them through an S3-compatible API. A Fastly CDN service can also use an Object Storage bucket as a private origin, allowing objects to be delivered through Fastly's edge network.
What is the difference between object storage and file storage?
File storage organizes data into a hierarchical structure of directories, folders, and files. It behaves just like the filesystem on a laptop or traditional network file server.
Object storage uses a flatter architecture. Applications retrieve an object using its unique key through an API rather than navigating a filesystem hierarchy.
File storage can be useful when applications depend on familiar filesystem semantics. Object storage tends to be better suited to cloud-scale applications, large media libraries, backups, application assets, datasets, and other unstructured content.
What is the difference between object storage and block storage?
Block storage divides data into fixed-size blocks that an operating system can use to construct a filesystem or database volume. It is commonly used for workloads like virtual machine disks and high-performance databases.
Object storage manages complete objects through an API instead.
Block storage is generally optimized for workloads that require low-level disk-like access and frequent modifications. Object storage is better suited to large quantities of data that applications typically create, retrieve, replace, or delete as complete objects. Neither is universally better; they solve different storage problems.
What is the difference between object storage and a CDN cache?
Object storage and CDN caching are complementary technologies.
Object storage is durable. It holds the authoritative version of an object until that object is changed or deleted.
CDN caching is temporary. A CDN keeps copies of eligible content at edge locations so requests don't always need to travel back to the origin.
A common architecture looks like:
Object Storage to CDN to User
The object storage platform provides the durable origin, while the CDN caches frequently requested objects closer to users.
Fastly Object Storage can be configured as a private origin for Fastly CDN services, combining these two layers within the Fastly platform.
Can object storage be used for AI and machine learning?
Yes. AI workloads can generate and consume enormous amounts of unstructured data, making object storage a natural fit for many AI architectures.
Potential uses include storing:
Training and evaluation datasets
Model artifacts
Images, audio, and video
User-uploaded data
AI-generated content
Data required for inference pipelines
Fastly Object Storage is a durable data foundation for AI workloads and integrates it with Fastly Compute and AI Accelerator for applications that need to process or access data at the edge.
Can object storage improve content delivery performance?
Object storage alone doesn't replace a CDN, but the two can work together effectively. An object storage service can hold the durable source of a video, image, software package, or other asset. A CDN can then cache that object at edge locations closer to users.
When an object is already cached, it can be delivered without another request to the storage origin. When it isn't cached, the CDN retrieves it from object storage and may cache it for subsequent requests.
Fastly combines Object Storage with its CDN and global edge network, allowing organizations to store content and deliver it through the same platform. Fastly says this integration can help improve latency and cache-hit ratios while reducing egress costs.
Why is object storage necessary?
Modern applications generate and consume enormous quantities of unstructured data. Traditional storage architectures aren't always optimized for managing that data economically or at cloud scale.
Object storage helps address several challenges.
Scalability: Object storage is designed to accommodate very large collections of objects without requiring applications to manage traditional filesystem structures.
Cost efficiency: Organizations can use object storage for large data libraries without relying on more expensive storage technologies designed for workloads like databases or operating-system disks.
Application simplicity: API-based access allows applications to store and retrieve objects without managing the physical storage infrastructure underneath them.
Data durability: Object storage systems are typically designed to protect data through distributed storage and redundancy.
Cloud-native development: Object storage integrates naturally with APIs, serverless and edge computing, CDNs, analytics platforms, and modern application architectures.
Large-scale content delivery: Object storage can act as the durable source for content that is subsequently cached and delivered through a CDN.
The distinction between storage and caching is important. Object storage provides durable storage for the authoritative version of data. A CDN cache temporarily keeps copies closer to users to accelerate delivery.
What are object storage best practices?
Effective object storage involves more than simply uploading everything into a bucket. Organizations should consider how data is organized, accessed, secured, delivered, and managed throughout its lifecycle.
The following are best practices to incorporate:
Design a logical key structure. Establish predictable object-naming conventions that make data easier for applications and teams to manage.
Use metadata intentionally. Metadata can provide useful context about an object's content, type, origin, or purpose without requiring an application to inspect the object itself.
Apply least-privilege access. Credentials should have only the permissions and bucket access required for their workload. Fastly Object Storage, for example, supports access keys with different permissions and bucket scopes.
Protect credentials. Don't hard-code or store production access credentials in insecure locations. Use appropriate secret-management mechanisms and rotate credentials according to organizational security policies.
Separate workloads when appropriate. Different buckets or access policies can help isolate applications, environments, teams, or data types.
Put frequently accessed content behind a CDN. Object storage provides the durable source of data, while CDN caching can reduce repeated storage requests and improve delivery performance.
Plan for large uploads. Large objects may require multi-part uploads so data can be transferred in manageable pieces.
Consider data location. For latency-sensitive applications, placing data closer to where applications process or users consume it can reduce unnecessary data movement.
Monitor storage and request patterns. Understanding capacity, read/write operations, delivery traffic, and access patterns can help teams improve both performance and cost.
Plan migration carefully. Moving large existing datasets between providers can create substantial transfer costs and operational complexity, so migration architecture should be considered alongside the target storage design.
Who needs object storage?
Object storage is useful for organizations of nearly every size, but it is particularly valuable for workloads involving large quantities of unstructured data.
Media and streaming companies can use object storage for video, audio, images, and large content libraries.
Ecommerce companies can store product images, videos, catalogs, and other digital assets.
SaaS companies can use it for application assets, customer-generated files, exports, and other persistent data.
Gaming and software companies can store game assets, software packages, installers, patches, and downloadable content.
Publishers and digital platforms can manage large libraries of images, documents, video, and other editorial assets.
AI and machine learning teams can store datasets, model artifacts, generated content, and other data required by training and inference workflows.
Analytics and data teams can store large datasets for subsequent querying or processing.
Organizations running global applications can combine object storage with edge computing and content delivery to move stored data closer to applications and end users.
Fastly specifically positions Object Storage for active, high-throughput unstructured data, including images, videos, media libraries, AI and machine learning datasets, application assets, software packages, user-generated content, and analytics datasets.
What does Fastly offer for object storage?/ How Fastly can help
Fastly Object Storage is an S3-compatible object storage service designed to work directly with Fastly's edge cloud platform. It allows developers to store and access large objects using familiar S3-compatible tools, APIs, and workflows while integrating storage with Fastly CDN and Compute.
Key capabilities include:
S3 API compatibility: Fastly Object Storage operates as an S3-compatible storage service, making it possible to use familiar tooling and existing S3-oriented application patterns rather than adopting an entirely new storage interface.
Integration with Fastly CDN: An Object Storage bucket can serve as an origin for a Fastly CDN service. Content can therefore be stored in Object Storage, cached at the edge, and delivered through Fastly's network.
Integration with Compute: Object Storage works with Fastly Compute, allowing applications running at the edge to access stored data as part of application workflows.
Zero egress fees within Fastly: Fastly doesn't charge an additional egress fee when data is transferred from Fastly Object Storage through Fastly's network to its CDN or Compute layers. This can reduce the cost associated with repeatedly moving data from a separate cloud storage provider into the delivery or compute layer.
High durability: Fastly Object Storage is engineered to provide 11 nines (99.999999999%) of data durability.
Edge-oriented architecture: By integrating storage with Fastly's global platform, organizations can bring stored data closer to the applications and delivery infrastructure consuming it, reducing unnecessary data movement and supporting lower-latency architectures. Fastly expanded the Object Storage footprint with five additional regions in February 2026.
Support for existing workflows: Developers can manage buckets and objects using the Fastly control panel and APIs, and the S3-compatible interface works with tooling like the AWS CLI.
This combination makes Fastly Object Storage particularly relevant for organizations that already use, or want to use, Fastly for delivery and edge computing and want to bring the storage layer into the same platform.