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IAM setup
This is a short guide explaining how to setup users in [Identity and Access Management (IAM)] iam to manage access to your AWS account for setting up Snowplow, managing the Snowplow data pipeline and performing analytics on Snowplow data.
IAMs gives you fine grained control over the level of permissions each user has in accessing your AWS account. It is wise to limit the permissions to each user to the minimum to enable them to do the job required, so that if those credentials are compromised, the hacker who gains access to them has limited access to your AWS account.
You need to setup different groups / users in IAMs at different stages of your Snowplow setup:
- [A user to setup Snowplow on your AWS account (the Snowplow Installer)] install-snowplow. Create credentials for a user to install Snowplow on your AWS account. This user has lots of permissions, as she will need to setup all the relevant collectors, buckets on Amazon S3 and Redshift cluster, if required.
- [A user to run the Snowplow data pipeline (the Snowplow Operator)] operate-snowplow. Once your Snowplow stack has been setup, you create a new user with much more limited permissions than those allocated to the user who installed Snowplow, and use these credentials for EmrEtlRunner and StorageLoader to manage your data pipeline over time.
- [A user who uses EMR to crunch Snowplow data (the Snowplow Data Scientist)] crunch-snowplow-data. If you have analysts / data scientists who are using EMR to analyse Snowplow data, you will need to set them up with their own credentials.
Disclaimer: Snowplow Analytics Ltd will not be liable for any problems caused by the full or partial implementation of these instructions on your Amazon Web Services account. If in doubt, please consult an independent AWS security expert.
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COMMON
Troubleshooting
IAM Setup Guide
- IAM - Setup
- Setup a user to install Snowplow
- Setup a user to operate Snowplow
- Setup a user to analyse Snowplow data with EMR
Ruby and RVM setup
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