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Amazon S3 Bucket Set Up For Automation Process
Amazon S3 Bucket Set Up For Automation Process
Updated over a week ago

Setting up an Amazon S3 bucket

Gelato needs to be able to access the files that are to be used in the automatic approval process via public URLs. Gelato can read your files from anywhere as long as they are publicly available and can be accessed in a structured way. If you do not have this today (for example if you use Google Drive or Dropbox as your primary cloud storage) then you can opt to set up an Amazon AWS account and use their S3 storage solution. Note that the below guide is a recommendation on how one type of setup can be done to create publicly available files that Gelato can access. However, Gelato takes no responsibility for your files as these are owned and hosted by you. You need to ensure that you have configured Amazon in a way that adheres to your own security policies who has access and who you share the file links with.

  1. Start by signing up for Amazon AWS. Once signed up click to Sign-in to console.

    Screenshot_2020-10-10_at_14.24.10.png
  2. Once signed-in type in 'S3' in the search field and select S3.

    Screenshot_2020-10-10_at_14.24.55.png


    Then S3 is opened. Now you need a new bucket. The bucket is the location where your files will be stored. Click 'Create bucket'.

    Screenshot_2020-10-10_at_14.25.05.png


    Set a name and select which region you want your bucket to be in.

    Screenshot_2020-10-10_at_14.25.28.png


    Click Next. You do not need to make any changes in Step 2.

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    In step 3 you need to deselect "Block all public access" and acknowledge that you understand what this means.

    Screenshot_2020-10-10_at_14.26.39.png


    In step 4 review your settings and click 'Create bucket'.

    Screenshot_2020-10-10_at_14.26.46.png
  3. Your bucket is now created. Let's add a file to it manually. Go into the bucket and click 'Upload'. Follow the instructions and then open the file in the bucket. You will see a screen similar to the one below.
    Note the Object URL path. Everything up until the file name is the domain and folder structure that you should include in your full file path for Gelato to process the orders. See the file name section for more info.

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  4. To make the files publicly available which is needed so that Gelato can read them you need to update the permissions by setting a ‘Bucket policy’ with the below text.
    Go to your bucket and click Permissions.

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    Scroll down to Bucket Policy and click “Edit” (the edit button might also be on the right-hand side or as in the image below).

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    Paste the below text in the Policy input text area. It should look like below.
    Note that you have to change from “myzapierbucket” (which is just a test bucket that Gelato has used) to your own bucket name here in the text. If you don’t change you will get an error when saving.

    mceclip4.png

The text to paste in the bucket policy text area

{

"Version": "2012-10-17",

"Statement": [

{

"Sid": "AllowPublicRead",

"Effect": "Allow",

"Principal": {

"AWS": "*"

},

"Action": "s3:GetObject",

"Resource": "arn:aws:s3:::myzapierbucket/*"

}

]

}

You are now done setting up your S3 bucket!

Common questions

Q: If I have products that don't require a print file such as a frame or a hanger will the system understand there should be no print file for it?

A: Yes, for line items that are non-printable such as frames or hangers which don't require a print file the system will approve the order without any file.

If you have an order with a poster and a frame as 2 line items then the system will look for the print file for the poster. Once the poster file is detected then the order will be approved and processed.

If you have an order that only has items that don't require a print file (examples being frames and hangers) then the order will be automatically approved immediately.

Q: Can I also use this on old orders that are not yet approved?

A: Yes, you can. As long as the order status is "Pending approval", you have file names that are according to the file naming convention and that they are in the S3 bucket they will also be processed.

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