Get started with Amazon S3 Batch Operations

Amazon S3 Batch Operations is a feature in Amazon Web Services (AWS) that allows users to manage large numbers of S3 objects simultaneously. S3 Batch Operations can perform actions across billions of objects and petabytes of data with a single request. With this feature, you can make changes to object metadata and properties, or perform other storage management tasks, such as copying or replicating objects between buckets, replacing object tag sets, modifying access controls, and restoring archived objects from S3 Glacier — instead of taking months to develop custom applications to perform these tasks.

You can use S3 Batch Operations through the AWS Management Console, AWS CLI, Amazon SDKs, or REST API.

How it works: S3 Batch Operations

To perform work in S3 Batch Operations, you create a job. The job consists of the list of objects, the action to perform, and the set of parameters you specify for that type of operation. You can create and run multiple jobs at a time in S3 Batch Operations or use job priorities as needed to define the precedence of each job and ensures the most critical work happens first. S3 Batch Operations also manages retries, tracks progress, sends completion notifications, generates reports, and delivers events to AWS CloudTrail for all changes made and tasks executed. For information about the operations that S3 Batch Operations supports, see Operations supported by S3 Batch Operations.

A batch job performs a specified operation on every object that is included in its manifest. A manifest lists the objects that you want a batch job to process and it is stored as an object in a bucket. You can use a comma-separated values (CSV)-formatted Amazon S3 Inventory report as a manifest, which makes it easy to create large lists of objects located in a bucket. You can also specify a manifest in a simple CSV format that enables you to perform batch operations on a customized list of objects contained within a single bucket.

You can use Amazon S3 Inventory to get the list of objects and use S3 Select to filter your objects.

After you create a job, Amazon S3 processes the list of objects in the manifest and runs the specified operation against each object. While a job is running, you can monitor its progress programmatically or through the Amazon S3 console. You can also configure a job to generate a completion report when it finishes. The completion report describes the results of each task that was performed by the job. For more information about monitoring jobs, see Managing S3 Batch Operations jobs.

Overview of Amazon S3 Batch Operations

  1. Modify ACLs, Metadata and Tags: Quickly applying access control lists (ACLs) or metadata tags to a large number of objects.

  2. Data Processing: Running Lambda functions on a large number of objects for data processing tasks.

  3. Copying Objects: Copying a large number of objects across S3 buckets.

  4. Encrypting un-encrypted objects: This process is vital for enhancing data security and compliance with various data protection standards. It provides a scalable, efficient, and reliable method for applying encryption to large volumes of data, which would otherwise be cumbersome and risky to handle manually or through custom scripts.

  5. Deleting Object Tagging: Perform S3 Delete Object Tagging operations using Amazon S3 Batch Operations to delete object tags across many objects with a single API request or a few clicks in the S3 Management Console.

  6. Restoring objects from S3 Glacier: Using Amazon S3 Batch Operations to restore objects from S3 Glacier is a highly effective way to manage bulk data retrieval needs from archival storage. This approach is especially beneficial for organizations dealing with large volumes of data that need to be accessed infrequently, but may require rapid and large-scale retrieval due to various operational, legal, or compliance needs. It simplifies and automates what would otherwise be a complex and resource-intensive process.

S3 Batch Operation vs Custom Scripts

  1. Scalability: S3 Batch Operations are built to handle operations at a massive scale, something that might be resource-intensive and complex to achieve with custom scripts.

  2. Reliability: AWS guarantees the execution of the tasks with error handling and retry logic, which might be challenging to implement effectively in custom scripts.

  3. Simplicity: Setting up a batch operation is generally simpler and requires less technical expertise than writing, testing, and maintaining scripts.

  4. Integrated Monitoring and Logging: AWS provides integrated monitoring, logging (with AWS CloudTrail), and reporting for operations, which can be more complex to implement with scripts.

  5. Cost-Effective: While there is a cost associated with S3 Batch Operations, it might be more cost-effective than running custom scripts, especially when considering the infrastructure and management overhead.

In essence, Amazon S3 Batch Operations provide a powerful, scalable, and reliable way to perform bulk operations on S3 objects, eliminating the need for custom scripting and manual processes. This service is especially beneficial for businesses and organizations dealing with massive data sets in S3, where managing such operations manually or through scripts would be inefficient and prone to error.

Tutorial: Replace objects tags by using S3 Batch Operations via AWS Management Console

Replacing object tags in an Amazon S3 bucket using S3 Batch Operations through the AWS Management Console is a straightforward process. This method is particularly useful when dealing with a large number of objects. Here's a step-by-step tutorial:

Prerequisites

  • Ensure that you have the necessary permissions to use S3 Batch Operations and to modify tags on S3 objects.

  • Have an S3 bucket with the objects you want to tag. This bucket also stores manifest and report files.

Steps to Replace Object Tags Using the AWS Management Console

1. Create an IAM Role for S3 Batch Operations

You need an IAM role that S3 Batch Operations can assume to perform actions on your behalf.

  1. Go to the IAM Console:

    • Create a new policy that grants permission to modify S3 object tags (like s3:PutObjectTagging and s3:PutObjectVersionTagging). Use the following permission policy:

        {
          "Version":"2012-10-17",
          "Statement":[
            {
              "Effect":"Allow",
              "Action":[
                "s3:PutObjectTagging",
                "s3:PutObjectVersionTagging"
              ],
              "Resource": "arn:aws:s3:::TargetResource/*"
            },
            {
              "Effect": "Allow",
              "Action": [
                "s3:GetObject",
                "s3:GetObjectVersion"
              ],
              "Resource": [
                "arn:aws:s3:::ManifestBucket/*"
              ]
            },
            {
              "Effect":"Allow",
              "Action":[
                "s3:PutObject"
              ],
              "Resource":[
                "arn:aws:s3:::ReportBucket/*"
              ]
            }
          ]
        }
      

      Replace TargetResource, ManifestBucket and ReportBucket with your S3 bucket name. For simplicity all files will be stored in one bucket. You can optionally configure separate S3 buckets to store the manifest and report files.

    • Create a new IAM role and attach the policy. Select S3 as the trusted entity for this role.

    • To allow the S3 Batch Operations service principal to assume the IAM role, attach the following trust policy to the role.

        {
           "Version":"2012-10-17",
           "Statement":[
              {
                 "Effect":"Allow",
                 "Principal":{
                    "Service":"batchoperations.s3.amazonaws.com"
                 },
                 "Action":"sts:AssumeRole"
              }
           ]
        }
      
    • Note the ARN of the IAM role you've created.

2. Prepare a List of Objects to Tag

You need a CSV file listing the objects you want to tag.

  1. Create a CSV File:

    • Format the file with a single column named S3Key, listing the keys of the objects you want to tag.

    • Example:

      
        bucket-name,path/to/object1.png
        bucket-name,path/to/object2.png
      

  2. Upload the CSV to S3:

    • Upload this file to your S3 bucket.

3. Create a Job in S3 Batch Operations

Now, set up and run the batch operation to replace the tags.

  1. Open the Amazon S3 Console:

    • Go to the "Batch Operations" section.
  2. Create a New Job:

    • Click on "Create job."

    • Select the S3 bucket where your CSV manifest file is located.

    • Choose "Specify an S3 object" and input the path to your CSV file.

    • Click "Next."

  3. Select Operation:

    • Choose “Replace all object tags.”

    • Input the new tags you want to apply to the objects.

    • Click "Next."

  4. Configure Job:

    • Choose the IAM role you created earlier.

    • Optionally, set up a report to track the job’s progress. Specify an S3 bucket for the report.

    • Click "Next."

  5. Review and Create the Job:

    • Review the job settings.

    • Click "Create job."

4. Monitor the Job

  • After creating the job, you can monitor its progress in the S3 console under "Batch Operations." To run the job confirm it to run by pressing the "Run job" button.

Conclusion

By following these steps, you can use the AWS Management Console to set up an S3 Batch Operation to replace tags on a large number of objects. This approach is highly efficient for managing and categorizing data in S3, especially when dealing with vast amounts of objects, and it doesn't require any coding or scripting knowledge.

References:

  1. Amazon S3 Batch Operations

  2. How to use Amazon S3 Batch Operations

  3. Managing Tens to Billions of Objects at Scale with S3 Batch Operations

  4. Granting permissions for Amazon S3 Batch Operations

  5. Creating an S3 Batch Operations job

  6. Operations supported by S3 Batch Operations