diff --git a/README.md b/README.md index 2ef91dc980a13b5c9da75f569219742f199d9223..060d2f0964ec0ab51426d2f0e956c94db067d90a 100644 --- a/README.md +++ b/README.md @@ -62,10 +62,11 @@ The following image represent the application workflow. Each step in the flowcha #### Create a blank step function * Log into the AWS Management Console and navigate to the AWS Step Functions page. * Click on Create state machine to start the process of creating your workflow template. -* Choose **Blank** to create a workflow from scratch. +* Choose **Blank** to create a workflow from scratch. +* Choose a relevant name for your Step function (VERY IMPORTANT: do not forget that you are working on the same AWS Amazon account with the other students) Inside the workflow studio, navigate to the left-hand panel and select **Flow** control. #### Step 1: Map block -Choose **Map**, which allows for parallel processing: +Choose **Map**, which allows for parallel worflow for each item in a dataset (in our case each .tif file is an item): * Assign a suitable name * Select the processing mode as 'Distributed,' facilitating the creation of separate child workflows for each image. * Choose the item source as 'Amazon S3,' then select 'S3 object list' as the S3 item source. Navigate to the S3 bucket **'satellite-images-ndvi'**, where the NDVI images are stored.