Linking AWS S3
In this guide, we’ll link a private AWS S3 bucket to a Valohai project.
For this tutorial you will need:
- an Amazon Web Services (AWS) account you can administer
- a Valohai project which to link the S3 bucket to
2. Create the S3 bucket
Create an S3 bucket through AWS console (https://s3.console.aws.amazon.com/s3/home).
2.1 Select bucket name and region
- Throughout this guide, we will assume the name of the bucket is
my-valohai-bucket; be sure to replace this with the actual name of your bucket when copying in any example configuration!
- Create the bucket in the region you’ll be running your training to minimize data transfer costs. If you don’t have a preference, we recommend using Ireland (eu-west-1) as most of our computation resides there.
2.2 Use default bucket properties
Default bucket properties are fine, no need to activate versioning or anything else.
2.3 Use default bucket permissions
Default bucket permissions are fine, but double check that your bucket is not public.
3. Configure CORS for the S3 bucket
If you wish to be able to upload files to the store using the app.valohai.com web UI, you will need to
add a CORS policy document to the S3 bucket.
First you navigate to the AWS S3 bucket you created.
Then you go to the “CORS settings” and add the rules below.
<?xml version="1.0" encoding="UTF-8"?>
Now your bucket allows POSTs for your user on https://app.valohai.com website
4. Create an IAM user
Using the AWS console, start creating a new IAM user with programmatic access credentials (access key ID / secret access key).
4.1 Select name for your programmatic user
- User name can be anything, try to be descriptive.
- Double check that programmatic access is turned on.
4.2 Skip the permission configuration
We will add permissions later, you can skip to the next step.
4.3 Save access key ID and secret for later usage
Download the CSV or copy-paste the “Access key ID” and “Secret access key” somewhere safe.
If you lose these credentials, you can generate new ones though IAM > Select user > Security credentials > Create access key.
5. Allow the IAM user to access the bucket
Now we have a user without any permissions, let’s allow the user to access our new bucket.
Find and open the user you created in the previous section.
Add a new inline policy. You can use any other AWS IAM policy definition methods just as well. Inline policies are the easiest get started.
The user needs to have full access to the S3 bucket; an example of a suitable access policy document is below.
Make sure to change the resource name my-valohai-bucket!
Give your policy a descriptive name and we are done with the mandatory AWS setup!
5. Large file uploads (optional)
If executions need to upload outputs larger than 5 GB, additional setup is needed.
This is optional and only required for large outputs.
To upload large outputs using Amazon’s multi-part upload API,
a temporary AWS IAM role will be dispensed to the worker machines when required.
Be sure to replace the following placeholders in the following policy examples!
- BUCKET – the target S3 bucket
- ACCOUNTNUMBER – your AWS account number
- USERNAME – the username liked to the access keys that are being used with the store
Create a new AWS IAM Role. The role policy document should look like:
The trust relationship document should look like:
Take note of the role’s AWS ARN (
arn:aws:...), that will be configured to your Valohai project.
6. Link the store to Valohai
Navigate to Project > Settings > Data Stores > Add S3 store
Name your store and paste in the bucket name and the IAM credentials in the fields provided.
If you also created the optional IAM Role for large uploads, paste the ARN in in the “Multipart Upload IAM Role ARN” field. You may leave this field empty.
When you create the store, the credentials provided will be checked by creating a small test file in the bucket.
Once set up, you can set the store as your project’s default store in the Settings > General view. This ensures outputs will be stored in your S3 bucket.