4 Types of S3 Replication and a Quick Tutorial

Henry Golas

What is S3 Replication?

Amazon S3 Replication is a fully managed, asynchronous service that automatically copies objects and their metadata between S3 buckets to support data redundancy, compliance, and reduced latency. Key types include Cross-Region Replication (CRR) for different regions and Same-Region Replication (SRR) for buckets in the same region.

S3 Replication can help you reduce costs, protect your data, and achieve compliance with regulatory requirements.

Here are the main S3 storage replication options:

Cross-Region Replication (CRR)—copies S3 objects across multiple Amazon Regions (ARs), representing geographically separate Amazon data centers.
Same-Region Replication (SRR)—copies S3 objects between buckets in different availability zones (AZs), which are separate data centers in the same AR.
Two-Way Replication (Bidirectional Replication)—synchronizes data and metadata between two or more buckets, either within the same region or across multiple AWS regions.
S3 Batch Replication—designed for on-demand replication of existing objects in Amazon S3.

AWS also offers a Replication Time Control (RTC) Service Level Agreement (SLA) that guarantees object replication in less than fifteen minutes.

In this article:

Amazon S3 Cross-Region Replication (CRR) and Same-Region Replication (SRR)
- AWS S3 Cross-Region Replication (CRR)
- Amazon S3 Same-Region Replication (SRR)
How to Set Up AWS S3 Replication
- Limitations of AWS S3 Replication using Replication Rule
S3 Replication with Cloudian

This is part of an extensive series of articles about S3 Storage.

Why Use Replication in S3?

S3 replication provides a flexible way to copy objects across buckets while preserving data integrity, controlling access, and meeting compliance or disaster recovery needs. It supports both automatic and on-demand replication workflows, giving you fine-grained control over how and where your data is stored.

Key reasons to use S3 replication include:

Preserve metadata: Replicated objects retain metadata such as creation time and version IDs, ensuring accurate replicas.
Control storage class: Replicate objects directly into storage classes like Glacier or Deep Archive, or transition them over time using lifecycle policies.
Change object ownership: Use the owner override option to assign replica ownership to the destination bucket’s AWS account, helping separate access control.
Distribute across regions: Store data in multiple AWS regions to meet compliance requirements and improve resilience.
Fast synchronization: With Replication Time Control (RTC), 99.99% of new objects are replicated within 15 minutes, backed by an SLA.
Replicate on demand: Use Batch Replication to sync existing objects, retry failed replications, or perform backfills.
Enable failover and sync: Two-way replication keeps buckets synchronized and supports automatic failover using Multi-Region Access Points.

4 Types of Amazon S3 Replication

1. AWS S3 Cross-Region Replication (CRR)

CRR can help you reduce latency, maintain compliance, enforce security, and implement disaster recovery. The feature lets you replicate objects into other Amazon Regions (ARs), including your object’s metadata and object tags.

How CRR works

You can configure S3 CRR to copy objects into one or more buckets in a different AR, for improved resilience. The feature lets you set up replication between buckets, shared prefixes, and individual objects. You can manage replication for individual objects using object tags.

CRR Use Cases

Here are key use cases for S3 CRR:

Compliance—the default configuration in S3 is set to store data across multiple geographically-distant Availability Zones (AZs). However, compliance often requires storing data in specific geographical locations—CRR can help achieve this.
Latency performance—customers and end-users are sometimes located in several geographic locations. CRR can help you improve their user experience by minimizing latency for data access.

2. Amazon S3 Same-Region Replication (SRR)

Amazon S3 Same-Region Replication (SRR) provides fully automated replication of S3 objects to another AZ, within the same AR. It is available in all AWS commercial regions as well as AWS GovCloud (US).

How SRR works

SRR uses asynchronous replication, meaning that objects are not copied to the other AZ immediately after they are created or modified. You can configure SRR using the S3 Management Console, API, or SDK.

SRR identifies objects for which you requested replication at the prefix, bucket, or tag level, and starts replication. You can set the AWS account that owns the original copy to own the replicated object. Alternatively, you can use a different account for the copies to protect them from accidental deletion.

SRR Use Cases

Here are key use cases for SRR:

Aggregate logs into a single bucket—in some cases, you may need to store logs in several buckets or across different accounts. SRR lets you easily replicate these logs into one bucket located in one AR. You can then process logs in one location.
Replication between developer and test accounts—sometimes, you may need to share data between test and developer accounts. SRR lets you use rules to replicate objects and metadata between multiple accounts.
Abide by data sovereignty laws—some laws require storing data in separate AWS accounts and prohibit moving the data from a specific AR. SRR lets you backup critical data even when compliance requirements do not allow moving the data across ARs.

3. Two-Way Replication (Bidirectional Replication)

Two-way replication in Amazon S3 allows you to synchronize data and metadata between two or more buckets, either within the same region or across multiple AWS regions. This approach ensures that changes made to objects in one bucket are automatically replicated in the corresponding bucket, including updates to metadata such as object tags, ACLs, and object locks.

How Two-Way Replication Works

Two-way replication is configured by creating replication rules that operate in both directions between two buckets. You can use replica modification sync to ensure metadata changes are also replicated, not just the object contents. This feature can be enabled on existing or new replication rules, and works with both cross-region and same-region replication.

When two-way replication is used with multi-region access points, S3 keeps the data synchronized across buckets in different regions. These access points simplify the process of managing replicated data during regional failovers or latency-based routing decisions.

Two-Way Replication Use Cases

Shared datasets across regions: When multiple regions need access to the same data, two-way replication ensures that both the data and its metadata stay in sync, making it easier to manage globally distributed applications.
Synchronized failover readiness: For disaster recovery and failover strategies, two-way replication ensures that all critical data remains updated across regions. Replication metrics and S3 Replication Time Control (S3 RTC) can help monitor sync status and performance.
High availability applications: In case of a regional disruption, having up-to-date replicas in another region allows applications to switch over with minimal impact, as both object data and metadata are already replicated and available.

4. S3 Batch Replication

S3 Batch Replication is designed for on-demand replication of existing objects in Amazon S3. Unlike live replication, which automatically copies objects as they’re uploaded or modified, Batch Replication allows you to replicate objects that already exist in a bucket. This is useful for backfilling data or handling exceptions that live replication cannot address.

How S3 Batch Replication Works

You can create a batch replication job to replicate objects to one or more destination buckets. Jobs can be scoped using filters, such as replication status, so you can target only specific objects—for example, those that failed to replicate or need to be copied to new regions or accounts. Batch Replication supports both same-region and cross-region replication.

Importantly, if objects are already replicas (created by existing replication rules), Batch Replication is the only way to further replicate those replicas to new destinations.

S3 Batch Replication Use Cases

Backfill existing data: Use Batch Replication to copy objects that were uploaded before replication was originally enabled.
Retry failed replications: Target and reprocess objects that failed to replicate in previous replication attempts by filtering for a FAILED replication status.
Create additional replicas: When compliance or business requirements call for storing data in multiple accounts or regions, Batch Replication lets you replicate previously replicated objects to new destinations.

Cascade replication of replicas: Live replication cannot replicate already-replicated objects. Batch Replication enables further replication of those replicas, extending your replication chain as needed.

Related content: Read our guide to S3 buckets

How to Set Up AWS S3 Replication

You can set up S3 replication from one bucket to another by adding a replication rule to your source bucket. Here is a quick step-by-step tutorial on how to set up this kind of replication:

1. Go to the AWS S3 management console, sign in to your account, and select the name of the source bucket.

2. Go to the Management tab in the menu, and choose the Replication option. Next, choose Add rule.

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Image Source: AWS

3. Under the Source bucket configuration, Apply to all objects in the bucket. Note that when replicating buckets encrypted with AWS Key Management Service (KMS), this stage also requires choosing the correct key.

4. Under the Set destination configuration, choose the Buckets in this account option. If you wish to replicate to another account, select this option and specify a bucket policy for the destination.

5. To change the storage class of the object after replication, go to the Destination options configuration, and select a different storage class for the destination objects.

6. You can also set the replication time. Go to Replication time control settings, and select the Replication time control option. This configuration provides you with 99.99% assurance that the system will replicate new objects within 15 minutes. However, this service level agreement (SLA) incurs additional costs.

7. IAM role option—lets you create a new AWS identity and access management (IAM) rule. However, if you already have an existing role with replication permissions, you can use it instead of creating a new one.

8. Click on the Save button to create the replication rule. You will be asked if you want to start the replication via a pop up message. After that you will be redirected to main replication screen as shown in the following screenshot.

Limitations of AWS S3 Replication using Replication Rule

Here are key limitations of replication rules:

Difficult to set up for sources outside S3—it is relatively easy to set up S3 replication for S3 sources. However, configuring replication to source outside S3—inside AWS or in another cloud—may require writing custom modules.
Limited ability to apply transformation—enterprises often require applying transformation before replicating a date.
Non-transparent pricing—it can be difficult to understand how Replication time control is priced and implemented, and this may result in operational overhead.

S3-Compatible Storage On-Premises with Cloudian

Cloudian® HyperStore® is a massive-capacity object storage device that is fully compatible with Amazon S3. It can store up to 1.5 Petabytes in a 4U Chassis device, allowing you to store up to 18 Petabytes in a single data center rack. HyperStore comes with fully redundant power and cooling, and performance features including 1.92TB SSD drives for metadata, and 10Gb Ethernet ports for fast data transfer.

HyperStore is an object storage solution you can plug in and start using with no complex deployment. It also offers advanced data protection features, supporting use cases like compliance, healthcare data storage, disaster recovery, ransomware protection and data lifecycle management.

Learn more about Cloudian® HyperStore®.

What Is Object Storage?

Object storage is a data storage architecture that stores and manages unstructured data in units called objects. Objects can be any size or format, and can include data, metadata, and a unique identifier.

Unlike other storage systems, object storage is not organized into folders or a hierarchical path, so objects can be reached through multiple paths. In object storage, objects are stored in a flat data environment and can be accessed through multiple paths, rather than being organized into folders.

Objects can store photos, videos, emails, audio files, network logs, or any other type of structured or unstructured data. All of the major public cloud services, including Amazon, Google and Microsoft, employ object storage as their primary storage.

This is part of an extensive series of guides about data security.

In this article:

Object Storage Definition
Object Storage Architecture: How Does It Work?
Object Storage Benefits
Object Storage Use Cases
Selecting the Best Object-Based Storage Solution

Object Storage Definition

Object storage is a technology that manages data as objects. All data is stored in one large repository which may be distributed across multiple physical storage devices, instead of being divided into files or folders.

It is easier to understand object-based storage when you compare it to more traditional forms of storage – file and block storage.

File Storage

File storage stores data in folders. This method, also known as hierarchical storage, simulates how paper documents are stored. When data needs to be accessed, a computer system must look for it using its path in the folder structure.

File storage uses TCP/IP as its transport, and devices typically use the NFS protocol in Linux and SMB in Windows.

Block Storage

Block storage splits a file into separate data blocks, and stores each of these blocks as a separate data unit. Each block has an address, and so the storage system can find data without needing a path to a folder. This also allows data to be split into smaller pieces and stored in a distributed manner. Whenever a file is accessed, the storage system software assembles the file from the required blocks.

Block storage uses FC or iSCSI for transport, and devices operate as direct attached storage or via a storage area network (SAN).

Object Storage

In object storage systems, data blocks that make up a file or “object”, together with its metadata, are all kept together. Extra metadata is added to each object, which makes it possible to access data with no hierarchy. All objects are placed in a unified address space. In order to find an object, users provide a unique ID.

Object-based storage uses TCP/IP as its transport, and devices communicate using HTTP and REST APIs.

Metadata is an important part of object storage technology. Metadata is determined by the user, and allows flexible analysis and retrieval of the data in a storage pool, based on its function and characteristics.

The main advantage of object storage is that you can group devices into large storage pools, and distribute those pools across multiple locations. This not only allows unlimited scale, but also improves resilience and high availability of the data.

Object Storage Architecture: How Does It Work?

Anatomy of an Object

Object storage is fundamentally different from traditional file and block storage in the way it handles data. In an object storage system, each piece of data is stored as an object, which can include data, metadata, and a unique identifier, known as an object ID. This ID allows the system to locate and retrieve the object without relying on hierarchical file structures or block mappings, enabling faster and more efficient data access.

Objects can be any size or format, and can store photos, videos, emails, audio files, network logs, or any other type of structured or unstructured data.

Data Storage Layer: Flat Data Environment

The data storage layer is where the actual data objects are stored. Object storage is not organized into folders or a hierarchical path, so objects can be reached through multiple paths. Objects are stored in a flat data environment and can be accessed through multiple paths.

In an object storage system, data is typically distributed across multiple storage nodes to ensure high performance, durability, and redundancy. Each storage node typically contains a combination of hard disk drives (HDDs) and solid-state drives (SSDs) to provide the optimal balance between capacity, performance, and cost. Data objects are automatically replicated across multiple nodes, ensuring that data remains available and protected even in the event of hardware failures or other disruptions.

Metadata Index

The metadata index is a critical component of object storage architecture, as it maintains a record of each object’s unique identifier, along with other relevant metadata, such as access controls, creation date, and size. This information is stored separately from the actual data, allowing the system to quickly and efficiently locate and retrieve objects based on their metadata attributes. The metadata index is designed to be highly scalable, enabling it to support millions or even billions of objects within a single object storage system.

API Layer

The API layer is responsible for providing access to the object storage system, allowing users and applications to store, retrieve, and manage data objects. Most object storage systems support a variety of standardized APIs, such as the Simple Storage Service (S3) API from Amazon Web Services (AWS), the OpenStack Swift API, and the Cloud Data Management Interface (CDMI). These APIs enable developers to easily integrate object storage into their applications, regardless of the underlying storage technology or vendor.

5 Expert Tips

Object Storage Benefits

Exabyte Scalable

Unlike file or block storage, object storage services enable scalability that goes beyond exabytes. While file storage can hold many millions of files, you will eventually hit a ceiling. With unstructured data growing at 50+% per year, more and more users are hitting those limits, or they expect to in the future.

Scale Out Architecture

Object storage makes it easy to start small and grow. In enterprise storage, a simple scaling model is golden. And scale-out storage is about as simple as it gets: you simply add another node to the cluster and that capacity gets folded into the available pool.

HyperStore is an S3-compatible storage system. HyperFile is a connector that allows files to be stored on HyperStore.

Customizable Metadata

While file systems have metadata, the information is limited and basic (date/time created, date/time updated, owner, etc.). Object storage allows users to customize and add as many metadata tags as they need to easily locate the object later. For example, an X-ray could have information about the patient’s age and height, the type of injury, etc.

High Sequential Throughput Performance

Early object storage systems did not prioritize performance, but that’s now changed. Now, object stores can provide high sequential throughput performance, which makes them great for streaming large files. Also, object storage services help eliminate networking limitations. Files can be streamed in parallel over multiple pipes, boosting usable bandwidth.

Flexible Data Protection Options

To safeguard against data loss, most traditional storage options utilize fixed RAID groups (groups of hard drives joined together), sometimes in combination with data replication. The problem is, these solutions generally lead to one-size-fits-all data protection. You can not vary the protection level to suit different data types.

Object storage solutions employ a flexible tool called erasure coding that is similar to old-fashioned RAID in some ways, but is far more flexible. Data is striped across multiple drives or nodes as needed to achieve the needed protection for that data type. Between erasure coding and configurable replication, data protection is both more robust and more efficient.

Support for the S3 API

Back when object storage solutions were launched, the interfaces were proprietary. Few application developers wrote to these interfaces. Then Amazon created the Simple Storage Service, or “S3”. They also created a new interface, called the “S3 API”. The S3 API interface has since become a de-facto standard for object storage data transfer.

The existence of a de facto standard changed the game. Now, S3-compatible application developers have a stable and growing market for their applications. And service providers and S3-compatible storage vendors such as Cloudian have a growing user set deploying those applications. The combination sets the stage for rapid market growth.

Lower Total Cost of Ownership (TCO)

Cost is always a factor in storage. And object storage services offer the most compelling story, both in hardware/software costs and in management expenses. By allowing you to start small and scale, this technology minimizes waste, both in the form of extra headcount and unused space. Additionally object storage systems are inherently easy to manage. With limitless capacity within a single namespace, configurable data protection, geo replication, and policy-based tiering to the cloud, it’s a powerful tool for large-scale data management.

To learn more about Cloudian’s fully native S3-compatible storage in your data center, and how it can cut down your TCO, check out our free trial. Or visit cloudian.com for more information.

Object Storage Use Cases

There are numerous use cases for object storage, thanks to its scalability, flexibility, and ease of use. Some of the most common use cases include:

Backup and archiving
Object storage is an excellent choice for storing backup and archive data, thanks to its durability, scalability, and cost-effectiveness. The ability to store custom metadata with each object allows organizations to easily manage retention policies and ensure compliance with relevant regulations.

Big data analytics
The horizontal scalability and programmability of object storage make it a natural choice for storing and processing large volumes of unstructured data in big data analytics platforms. Custom metadata schemes can be used to enrich the data and enable more advanced analytics capabilities.

Media storage and delivery
Object storage is a popular choice for storing and delivering media files, such as images, video, and audio. Its scalability and performance make it well-suited to handling large volumes of media files, while its support for various data formats and access methods enables seamless integration with content delivery networks and other media delivery solutions.

Internet of Things (IoT)
As the number of connected IoT devices continues to grow, so too does the amount of data they generate. Object storage is well-suited to handle the storage and management of this data, thanks to its scalability, flexibility, and support for unstructured data formats.

How to Choose an Object-Based Storage Solution

When choosing an object storage solution, there are several factors to consider. Some of the most important factors include:

Scalability: One of the primary strengths of object storage is its ability to scale horizontally, so it’s essential to choose a platform that can grow with your organization’s data needs. Look for a solution that can easily accommodate massive amounts of data without sacrificing performance or manageability.
Data durability and protection: Ensuring the integrity and availability of your data is critical, so look for an object storage platform that offers robust data protection features, such as erasure coding, replication, or versioning. Additionally, consider the platform’s durability guarantees – how likely is it that your data will be lost or corrupted?
Cost: Cost is always a consideration when choosing a storage solution, and object storage is no exception. Be sure to evaluate the total cost of ownership (TCO) of the platform, including factors such as hardware, software, maintenance, and support costs. Additionally, if you’re considering a cloud-based solution, be sure to factor in the costs of data transfer and storage.
Performance: While object storage is not typically designed for high-performance, low-latency workloads, it’s still important to choose a platform that can deliver acceptable performance for your organization’s specific use cases. Consider factors such as throughput, latency, and data transfer speed when evaluating performance.
Integration and compatibility: The ability to integrate the object storage platform with your existing infrastructure and applications is essential. Look for a solution that supports industry-standard APIs and protocols, as well as compatibility with your organization’s preferred development languages and tools.

See Additional Guides on Key Data Security Topics

Together with our content partners, we have authored in-depth guides on several other topics that can also be useful as you explore the world of data security.