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Introduction

This guide walks through moving data from AWS S3 to GMI Cloud Cold Storage. GMI Cloud Cold Storage is built on VAST Storage and speaks the S3 protocol, so existing S3 tooling continues to work. Use this page as a reference when planning a migration, including method selection, the standard procedure, and post-migration checks.

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Why move from AWS S3

AWS S3 is the default for object storage: scalable, durable, and easy to use. As datasets grow, long-term storage and egress costs become the main concern, and teams start looking for a cheaper place to keep archival or rarely-accessed data. GMI Cloud Cold Storage targets that workload, S3-compatible APIs, lower per-GB cost, and high throughput for large objects.

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GMI Cloud Cold Storage

GMI Cloud Cold Storage uses VAST Storage under the hood. It speaks S3, NFS, and SMB, so most existing tools work without code changes. The S3 API surface is the same as AWS S3 for the operations you care about (PutObject, GetObject, ListObjectsV2, multipart upload), so aws s3, rclone, and any S3 SDK can target a Cold Storage bucket.

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Migration methods

VAST does not ship its own migration tool. Three approaches work today:

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1. AWS CLI

Pull data down with aws s3 and push up with rclone. Good for moderate datasets and when you have a fast staging machine with enough local disk. 
# Download from AWS S3 to local
aws s3 sync s3://your-source-bucket /local-storage-path

# Upload from local to GMI Cloud
rclone sync /local-storage-path gmi-cloud:your-destination-bucket

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2. Direct transfer (S3-to-S3)

Skip the local staging step. rclone can read from AWS S3 and write to GMI Cloud in a single command. Best when both sides have good network throughput. 
rclone sync aws_s3:source-bucket gmi-cloud:destination-bucket
You can also mount Cold Storage over NFS or SMB and copy files with whatever tool you already use for local-to-LAN transfers.

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3. Third-party migration tools

Several tools handle large-scale transfers with integrity checks, retries, and incremental sync:
  • AWS DataSync
  • rclone (recommended for most cases, simple config, supports both ends)
These add data integrity verification, incremental updates, and detailed logs you can keep for audit.

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Standard procedure

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1. Plan and prepare

  • Assess the data. Type, volume, access frequency. Decide what moves now and what stays put.
  • Set up credentials. Create an AWS IAM user with S3 read access on the source buckets, and get API keys for GMI Cloud Cold Storage.

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2. Configure the tools

aws configure
rclone config
When prompted, paste the AWS IAM credentials and the GMI Cloud credentials.

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3. Run the migration

Pick a method from above and start the copy: 
# CLI route
aws s3 sync s3://source-bucket /local
rclone sync /local gmi-cloud:destination-bucket

# Or direct
rclone sync aws_s3:source-bucket gmi-cloud:destination-bucket
Watch the run, log lines and exit codes catch most issues early.

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4. Verify

Compare object counts and total bytes between the source and destination buckets. Spot-check a few large objects for byte-for-byte equality. Run smoke tests against any application that reads from the migrated data.

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5. Cut over

Update application and service configs to point at the GMI Cloud Cold Storage endpoint. Re-run your normal application test suite to verify functionality.

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Operational best practices

  • Security. Use HTTPS for transfers and rotate credentials after the migration completes.
  • Backups. Keep a copy in AWS S3 until you’ve verified the migration in production.
  • Logs. Capture rclone or DataSync output so you can audit the migration later.
  • Bandwidth. Schedule big transfers off-hours to avoid impacting production traffic.

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Conclusion

Moving from AWS S3 to GMI Cloud Cold Storage lowers long-term storage cost without changing your tooling: the S3 API stays the same, and aws, rclone, and similar tools work out of the box. Plan the migration, pick the method that fits the dataset size, verify the copy, then cut over.