AWS DataSync: Simplifying Secure Data Migration to AWS
Moving large datasets between on-premises environments, other cloud providers, and AWS can be challenging. Building custom scripts for file synchronization, handling retries, validating transferred data, and monitoring network performance can add significant operational complexity.
AWS DataSync is a managed online data movement service designed to simplify and accelerate these transfers. It can move file and object data between on-premises storage, other cloud providers, and AWS storage services such as Amazon S3, Amazon EFS, and Amazon FSx. AAWS Documentation+1
What is AWS DataSync?
AWS DataSync provides a managed way to transfer large amounts of data while handling many of the operational tasks involved in data movement.
It supports common on-premises storage technologies such as:
- Network File System (NFS)
- Server Message Block (SMB)
- Hadoop Distributed File System (HDFS)
- Self-managed object storage
It can transfer data to AWS services including:
- Amazon S3
- Amazon EFS
- Amazon FSx for Windows File Server
- Amazon FSx for Lustre
- Amazon FSx for OpenZFS
- Amazon FSx for NetApp ONTAP AAWS Documentation
DataSync can also transfer data between AWS and supported storage services in other cloud providers. AAWS Documentation
Why use AWS DataSync?
Traditional data migration solutions often require custom scripts, third-party tools, or manually managed infrastructure.
DataSync provides features that simplify this process, including encryption in transit, data integrity validation, scheduling, bandwidth controls, monitoring, and task reports. AAmazon Web Services, Inc.+1
Common use cases include:
1. Migrating data to AWS
Organizations can migrate active datasets from on-premises storage to AWS storage services.
For example:
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On-Premises NFS
|
v
AWS DataSync
|
v
Amazon S3
This approach can be useful when moving existing file-based workloads into AWS without rewriting applications immediately.
2. Creating backups and replicas
DataSync can periodically copy data from an existing environment to AWS.
For example:
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Production Storage
|
| DataSync
v
Amazon S3 / Amazon EFS
Scheduled transfers can help create an additional copy of important datasets.
3. Archiving cold data
Older data that is rarely accessed can be moved from on-premises storage into Amazon S3 storage classes designed for archival workloads, including S3 Glacier Flexible Retrieval and S3 Glacier Deep Archive. AAWS Documentation
4. Hybrid cloud data processing
DataSync can move data into AWS for analytics, machine learning, media processing, and other workloads.
For example:
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On-Premises Data
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v
DataSync
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v
Amazon S3
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v
Analytics / ML / Processing
How AWS DataSync works
A typical DataSync workflow contains three important components:
- Source location – Where the data currently exists.
- Destination location – Where the data should be transferred.
- Task – Defines how DataSync performs the transfer. AAWS Documentation
When transferring data between on-premises storage and AWS, you generally deploy a DataSync agent in your storage environment. AWS provides deployment options including VMware, KVM, Hyper-V, and EC2-based deployments. AAWS Documentation
For some transfers between AWS storage services or supported cloud storage services, an agent isn't required. AAmazon Web Services, Inc.
The basic workflow looks like this:
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AWS DataSync
|
+---------+---------+
| |
Source Destination
| |
On-Premises NFS Amazon S3
On-Premises SMB Amazon EFS
Object Storage Amazon FSx
Creating a DataSync task
A DataSync task defines where and how data should move.
You configure the source and destination locations and can customize options such as file selection, metadata handling, verification, and scheduling. AAWS Documentation
A simplified workflow is:
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1. Configure source
↓
2. Configure destination
↓
3. Create DataSync task
↓
4. Configure transfer options
↓
5. Start task
↓
6. Monitor execution
Once a task is created, each run is called a task execution. AWS provides monitoring through the DataSync console and Amazon CloudWatch, while task reports can help audit transfer activity. AAWS Documentation+1
Example: On-premises NFS to Amazon S3
Imagine an organization has a large NFS file server containing application and historical data.
Instead of developing a custom migration application, the organization can:
- Deploy a DataSync agent.
- Connect the agent to the NFS storage.
- Create an Amazon S3 destination.
- Create a DataSync task.
- Configure transfer and verification options.
- Start the task.
- Monitor the transfer using DataSync and CloudWatch.
The resulting architecture could look like:
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+----------------------+
| On-Premises Network |
| |
| NFS File Server |
+----------+-----------+
|
v
+----------------------+
| DataSync Agent |
+----------+-----------+
|
v
+----------------------+
| AWS DataSync |
| Transfer Task |
+----------+-----------+
|
v
+----------------------+
| Amazon S3 |
| |
| Data / Backup / |
| Analytics Dataset |
+----------------------+
Security considerations
DataSync is designed with security and data integrity in mind. AWS documents encryption in transit and integrity validation for transfers. DataSync also integrates with AWS Identity and Access Management (IAM) for controlling access to AWS resources. AAmazon Web Services, Inc.+1
For environments requiring private network connectivity, DataSync supports VPC endpoints, allowing organizations to design transfers without sending traffic through the public internet. AAWS Documentation
As with any AWS service, use least-privilege IAM permissions and carefully review the permissions required by the DataSync resources and destination services.
Monitoring and troubleshooting
Monitoring is an important part of a production data-transfer workflow.
Useful options include:
- DataSync task execution details
- Amazon CloudWatch metrics, events, and logs
- DataSync task reports
- AWS CloudTrail for API activity
Task reports can provide information about files transferred, skipped, verified, and deleted. AAmazon Web Services, Inc.
Before running a large migration, it is also useful to test with a representative subset of the data and verify the resulting files and metadata.
AWS DataSync vs custom scripts
A simple script might work for a small data transfer, but large production migrations introduce additional requirements.
| Requirement | Custom scripts | AWS DataSync |
|---|---|---|
| Transfer automation | Build yourself | Built in |
| Scheduling | Build yourself | Supported |
| Transfer verification | Build yourself | Built in |
| Monitoring | Build yourself | AWS integrations |
| Retry/resiliency | Build yourself | Managed |
| AWS storage integration | Implement | Native integration |
| Large-scale transfers | Requires engineering | Purpose-built service |
The right choice depends on the workload, existing architecture, transfer requirements, and cost considerations. DataSync is particularly useful when the goal is managed, repeatable movement of large datasets rather than building and maintaining a custom transfer system. AAmazon Web Services, Inc.
Best practices
When using DataSync in production, consider the following:
- Start with a small test dataset before migrating everything.
- Use least-privilege IAM permissions.
- Monitor task executions and configure appropriate alerts.
- Review S3 request and DataSync costs before large transfers.
- Use scheduling for recurring synchronization workloads.
- Validate important data after migration.
- Plan network bandwidth and transfer windows carefully.
- Consider private connectivity requirements for sensitive workloads.
Conclusion
AWS DataSync provides a managed approach to moving large amounts of file and object data between on-premises environments, other cloud providers, and AWS storage services.
Instead of maintaining custom transfer infrastructure, teams can use DataSync tasks, scheduling, verification, monitoring, and AWS integrations to build repeatable data-movement workflows.
For organizations migrating to AWS, building hybrid-cloud architectures, creating replicas, or moving cold data to cloud storage, DataSync can be an important component of the overall data-migration strategy. AAWS Documentation+1
Further reading
- AWS DataSync documentation
- AWS DataSync getting started guide
- AWS DataSync service page
Description: Learn how AWS DataSync simplifies secure, high-performance data movement between on-premises storage, other cloud providers, and AWS services such as Amazon S3, EFS, and FSx.
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