How can I load data from the Slack app to Amazon S3 by using Amazon AppFlow?
Last updated: 2022-10-24
I want to extract my data from the Slack app, and load it to Amazon Simple Storage Service (Amazon S3). How can I use Amazon Appflow to do this do this?
To load your Slack data to Amazon S3, first create an app on Slack. Then, extract data from that app to Amazon S3 using Amazon Appflow. You can also use the method in this article to load data from an existing Slack app to Amazon S3.
To do this, you need to:
- Note your client ID, client secret, and Slack instance name.
- Set a redirect URL.
- Set the required user scopes in Slack.
- Log in to Slack, and create a workspace.
- Create a channel, and give access to your users by adding their email ID.
- Create an app in the workspace that you created by adding a name, and then choosing the Create App button.
- After you create an app, note the following information on the confirmation page. You need this information to create an Amazon AppFlow connector to Slack. See this example:
- App ID: A0****D
- Date of app creation: October 20, 2021
- Client ID: 2****97.2**9
- Client secret: 5****95
- Signing secret: d0****f4
- Verification code: U******q
- On the same page, under Install your app section, choose permission scope.
- Under User Token Scopes, add an OAuth Scope for your user token.
- Under Redirect URLs, add a URL similar to this:
- For us-eas-1 Region use: https://console.aws.amazon.com/appflow/oauth
- For all other Regions, use: https://region.console.aws.amazon.com/appflow/oauth
Note: Be sure to replace "region" in this URL with the Region you are using.
- Open the Amazon AppFlow console.
- Choose Create flow, and then under Source name, choose Slack.
- Under Choose Slack connection, choose Create new connection.
- Under Connect to Slack, Enter the details that you noted in step 4.
- For Destination name, choose Amazon S3, and for Destination bucket, choose the S3 bucket that you want to use.
- Map all fields, and then choose Run flow.
- After your flow is finished running, check the output file in the S3 bucket that you specified as a destination.
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