![]() ![]() ![]() Lambda permissions to read and write to S3 buckets.AWS Identity and Access Management (IAM) permissions to create Amazon S3 buckets and Lambda Functions.The following prerequisites are required before continuing: Configure S3 Bucket Permissions and an object upload trigger.Create a Docker Image for Lambda, bundle the prerequisite dependencies (e.g.Write application code that will run on AWS Lambda to compress and archive satellite imagery.Create S3 Buckets for input and output.To set up the solution, we cover the following steps: Delete the original image from the input bucket.Īfter the function has executed, you can then access the compressed and archived original files in the output bucket.Copy the original image to an archive prefix in the output bucket in an S3 Glacier storage class.Upload the compressed image to the output bucket. ![]() Users will upload images to an S3 bucket and an object upload notification will trigger a Lambda function which will: In this solution we’ll create a pipeline for processing imagery data. As a result, engineers have quicker access to data for use cases such as ML model training and inference while maintaining access to the high-resolution original images, all at a lower cost than storing the high-resolution images in S3 Standard alone. In this post, we propose a low-cost solution to compress satellite imagery with Geospatial Data Abstraction Library (GDAL) and archive the original images using Amazon S3 and the Amazon S3 Glacier storage classes. This reduction in file size reduces storage and data transfer costs, as well as improves data transfer speeds for imagery data. Using standard compression techniques lets us achieve reductions in file size with low loss to an image’s visual quality. Additionally, large imagery files can take time and resources when downloaded for use with machine learning (ML), data analytics tools, or manual analyst review. For more information, see Reducing the cost of SSE-KMS with Amazon S3 Bucket Keys.Satellite imagery often comes as large, high-resolution files, and organizations that work with this data typically have high storage costs. S3 Bucket Keys lower the cost of encryption by decreasing request traffic fromĪmazon S3 to AWS KMS. When you configure your bucket to use default encryption with SSE-KMS, you can alsoĮnable S3 Bucket Keys. For more information about using AWS KMS withĪmazon S3, see Using server-side encryption with AWS KMS keys For more information, see Identifying symmetric andĪsymmetric KMS keys in the AWS Key Management Service Developer Guide.įor more information about creating an AWS KMS key, see Creating keys in theĪWS Key Management Service Developer Guide. Amazon S3 supports only symmetric encryption KMS keys and notĪsymmetric KMS keys. When you use an AWS KMS key for server-side encryption in Amazon S3, you mustĬhoose a symmetric encryption KMS key. For more information on SSE-KMS, see Specifying server-side encryption with AWS KMS For more information on cross account permissions for KMS keys, see Creating KMS keys that other accounts can use in the AWS Key Management Service Developer Guide. Key and then you must enter the KMS key ARN. If you want to useĪ KMS key that is owned by a different account, you must first have permission to use the To use a KMS key that is not listed, you must enter your KMS key ARN. The Amazon S3 console lists only the first 100 KMS keys in the same Region as the bucket. You can use only KMS keys that are available in the same AWS Region as theīucket. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |