From 6d7d3edfb47f2bb85a66d8a84b6e3c580cc5ae40 Mon Sep 17 00:00:00 2001 From: Cedric Chan Date: Thu, 14 Nov 2019 15:42:03 +0800 Subject: [PATCH 1/2] Update README ref to deleted IAMPolicy --- README.md | 26 +++++++++----------------- 1 file changed, 9 insertions(+), 17 deletions(-) diff --git a/README.md b/README.md index b78db81..2117aa1 100644 --- a/README.md +++ b/README.md @@ -25,31 +25,23 @@ Note that the role itself has become a link. Open that link in a new tab. Here you will update the policies of your instance to allow it to work with Forecast. Click the `Attach policies` button. Search and check the box next to the following policies: --IAMFullAccess --AmazonForecastFullAccess + +- `IAMFullAccess` +- `AmazonForecastFullAccess` +- `AWSKeyManagementServicePowerUser` Finally click the `Attach policy` button on the bottom right corner. Now click on `Trust relationship` tab > click on `Edit trust relationships` button > update the json file with the following: - "Service": [ + +``` +"Service": [ "forecast.amazonaws.com", "sagemaker.amazonaws.com" ] - -Next click the `Create policy` button at the top. In the new page, click the `JSON` tab. - -Erase all of the content that is in the editor and paste the content in [IAM_Policy.json](IAM_Policy.json). - -After pasting, click the `Review policy` button. Give the policy again a personalize name like `FirstNameLastNameForecastIAMPolicy`. - -For the description, enter in something about it being used to demo Forecast. Finally click `Create policy`. Close this tab or window. - -Once closed you should see the tab for adding permissions to your SageMaker role. Click the `Filter Policies` link, then select -`Customer managed`. After that, you should see the policy you just created, if the list is long, just paste the name in the search bar to reduce the number -of items. If you do not see it still, click the refresh icon in the top right of the page. +``` -After clicking the checkbox next to the policy, click `Attach policy` at the bottom of the page. Then close this window. Back at the SageMaker Notebook Instance creation page, now click `Create notebook instance` at the bottom of the page. This process will take 5-10 minutes to complete. Once the status says `InService` you are ready to continue to the next session. @@ -75,4 +67,4 @@ If prompted for a kernel, select `conda_python3`. From here you will follow the instructions outlined in the notebook. -**Read Every Cell FULLY Before Executing It** \ No newline at end of file +**Read Every Cell FULLY Before Executing It** From aa21a014b9bc04be7799634f3239f65efdd510e5 Mon Sep 17 00:00:00 2001 From: Cedric Chan Date: Thu, 14 Nov 2019 15:56:51 +0800 Subject: [PATCH 2/2] Add prewarning for creating data bucket --- README.md | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/README.md b/README.md index 2117aa1..736aeb1 100644 --- a/README.md +++ b/README.md @@ -4,6 +4,11 @@ This guide will walk through the creation of a new SageMaker Notebook Instance, and your first project with Amazon Forecast. The Notebook Instance can then be used again for additional exploratory work with Amazon Forecast. +## Creating your S3 Data Bucket + +Go the s3 Console. Create a bucket named `amazon-forecast-data-` in the `us-east-1` region. +Leave everything else as default. + ## Creating Your Notebook Instance First you will need to create a new Notebook Instance, to do that begin by logging into the AWS Console.