AWS Snowball, a part of the AWS Snow Family, is a data migration and edge computing device that comes in two options. Snowball Edge Storage Optimized devices provide both block storage and Amazon S3-compatible object storage, and 40 vCPUs. They are well suited for local storage and large scale-data transfer. Snowball Edge Compute Optimized devices provide 52 vCPUs, block and object storage, and an optional GPU for use cases like advanced machine learning and full motion video analysis in disconnected environments. You can use these devices for data collection, machine learning and processing, and storage in environments with intermittent connectivity (like manufacturing, industrial, and transportation) or in extremely remote locations (like military or maritime operations) before shipping them back to AWS. These devices may also be rack mounted and clustered together to build larger temporary installations.
Snowball supports specific Amazon EC2 instance types and AWS Lambda functions, so you can develop and test in the AWS Cloud, then deploy applications on devices in remote locations to collect, pre-process, and ship the data to AWS. Common use cases include data migration, data transport, image collation, IoT sensor stream capture, and machine learning.
Easy data movement
Snowball moves terabytes of data in about a week. You can use it to move things like databases, backups, archives, healthcare records, analytics datasets, IoT sensor data and media content, especially when network conditions prevent realistic timelines for transferring large amounts of data both into and out of AWS.
Simple to use
Jobs are created in the AWS Management Console. Once a job is created, AWS automatically ships a pre-provisioned Snowball Edge device to your location. When you receive the device, simply attach it to your local network and connect your applications. Once the device is ready to be returned, the E Ink shipping label automatically updates, and your freight carrier transports it to the correct AWS facility where the upload begins. Job status can be tracked via Amazon SNS-generated text or email messages or directly in the AWS Management Console.
Process & analyze data locally
Run EC2 AMIs and deploy AWS Lambda code on Snowball Edge devices to run local processing or analysis with machine learning or other applications. You can run applications directly on the device as a consistent AWS environment without network connectivity. This capability helps you develop your machine learning and analysis tools and test them in the cloud, but operate them in locations with limited or non-existent network connections before shipping the data back to AWS.
Snowball Edge devices can provide local storage to existing on-premises applications through a file sharing protocol (NFS) or object storage interface (the S3 API). Additionally, you can use on-board block storage volumes for applications running on Amazon EC2 instances on the Snowball. You can also cluster Snowball Edge devices together into a single, larger storage tier with increased durability. If a Snowball Edge device needs to be replaced, it can be removed from the cluster and replaced with a new device.
Snowball Edge devices use tamper-evident enclosures, 256-bit encryption, and industry-standard Trusted Platform Modules (TPM) designed to ensure both security and full chain-of-custody for your data. Encryption keys are managed with the AWS Key Management Service (KMS) and they are never stored on the device.
Snowball can transport multiple terabytes of data and multiple devices can be used in parallel or clustered together to transfer petabytes of data into or out of AWS. Snowball is currently available in select regions and your location will be verified once you create a job in the AWS Management Console.
How it works
In the AWS Snowball console, select your preferred device, either Snowball Edge Compute Optimized or Snowball Edge Storage Optimized. Create a job with an Amazon S3 bucket, select Amazon Simple Notification Service (Amazon SNS) for tracking, and configure options like Amazon EC2 AMIs and a GPU. AWS prepares and ships the device to you, and you receive it in approximately 4-6 days. Once the device arrives, power it up and use AWS OpsHub to unlock it. Connect to your LAN. Use AWS OpsHub to manage the device, transfer data, or launch EC2 instances. When done, shut down and return the device to AWS. The shipping label automatically appears on the E Ink screen. When the device arrives at the AWS Region, any data stored in your on-board bucket(s) is moved to your S3 bucket and verified in about the same time it took you to load the device. All data is then securely erased from the device, and it is sanitized of any customer information.
Cloud data migration
Shifting an application to the cloud? Shutting off a storage array, or closing a data center? If you have large quantities of data you need to migrate into AWS, offline data transfer with AWS Snowball can overcome the challenge of limited bandwidth, and avoid the need to lease additional bandwidth. It also makes logistics simpler with automatic E Ink shipping labels.
Many industries require secure distribution of content. Airlines, VFX houses, studios, banks, hospitals, and even sports teams need to move media files for viewing, rendering, processing, and analysis. Use AWS Snowball devices if you regularly receive or share large amounts of data with clients, customers, or partners. Snowball devices can be sent directly from AWS to client or customer locations.
Tactical Edge Computing
Public sector organizations responsible for defense, public safety, disaster response, and other missions increasingly require data collection from cameras, sensors, or drones. Collection and even some processing has to happen where these critical teams operate – in the field, under variable conditions. AWS Snowball's powerful computing, flexible storage, security, and ruggedization helps tactical teams focus on the mission, and not on setting up and moving around storage racks.
With AWS Snowball, you can deploy and run machine learning models, such as document classification and image labeling, directly on the device to tune processes, improve efficiency and productivity, and even anticipate model failures. Additionally, Snowball devices can be used to transport data from remote or mobile locations to AWS for in-cloud machine learning.
On-site factory locations use AWS Snowball for manufacturing data collection and analysis to tune processes and improve safety, efficiency, productivity, and even anticipate failure. And over time, this data arrives back in AWS for analytics on a large scale that can highlight meaningful trends or patterns.
Remote locations with simple data
AWS Snowball is ideal for remote applications that benefit from pre-processing, such as image tagging, validation, compression, or organization. Collect the data, get quick results and/or prepare it in advance for your cloud analytics application. Then, ship it back to AWS.
In this video, NGA describes how they are using AWS Snowball as part of their mission.
In this video, Netflix describes how they built content delivery workflows with AWS Snowball.
In this video, AWS APN partner Novetta, describes how they worked with the AWS Disaster Response Team to use AWS Snowball, IoT, and machine learning in a disaster response exercise.
Photobox wanted to get out of the business of owning and maintaining its own IT infrastructure so it could redeploy resources toward innovation in artificial intelligence and other areas to create a better customer experience. By migrating from its Dell EMC Isilon and IBM Cleversafe on-premises storage arrays to Amazon S3 using AWS Snowball Edge, Photobox saved a significant amount on storage costs for its 10 PB of photo storage.
Blog posts & articles
Vinod Pulkayath and Ryan Starck | 09 MAR 2020
Grace Kitzmiller, James Devine, and Paul Bockelman | 04 DEC 2019