I have an account in DEV for quicksight which has all sets of datasets, analysis and dashboards. We need to now move from DEV to PROD (separate accounts) . I have all the information provided by many members in this community using aws cli, cloud front etc. and got a lot of information- Deployment Approach for QuickSight Artifacts from DEV to PROD - Need suggestion!
Have a few questions, would really appreciate if anyone can provide a thought on this- The pipeline would be purely in python in backend I guess, where we have to create, modify and replace assets. I saw where we can move the resources from one account to the other but the thing is, the examples /code that have been shown, that is only involving 1 dataset/1analysis or 1 dashboard.
My questions are,
Can we be able to move all datasets, dashboards, analysis using dome some looping technic?
The other block is, terraform keeps track of what is deployed already, but since this will be in python, and we dont have terraform, how aws is going to behave, if we have created something in prod and we re-run the pipeline, will it override the previous ones or will it fail??The below methodology doesn’t show any statefile creation like terraform.
Should I check the cloudfront option?
Please could you let me know, if there is an easy way of migrating the things from dev to prod or any other other account? or we should just go ahead and manually create an account in those environments and start from scratch???
Thank you so much for the information, I tested on using the quicksight APIs including the new one as well for migration and it is working well, I can see the objects in my new quicksight account migrated from the old. This is the API method that I used.
However, I am leaning more towards using the Cloud Formation and will use CFT for transferring the assets, is there any link or page where we can have the steps for moving the objects cross accounts using cloud formation and CF Template? Like the procedure for exporting the infrastructure as code from the quicksight (environment 1) and making changes in the script( as requirement ) and uploading in the CF as stack and then running against specific environment to show that particular (analysis/dashboard in the environment 2).