changed @connection directives make `amplify push` unusable
See original GitHub issueDescribe the bug
It seems like the @connection
directives are broken in some fundamental way with respect to amplify push
.
To Reproduce Steps to reproduce the behavior:
- Create a GraphQL api
- Use some
@connection
directives - After a couple pushes involving deleting a directive, and maybe adding it back under a different field or name,
amplify push
will stop working with theResource is not in the state stackUpdateComplete
error.
Stack Trace I can post a stack trace the next time this happens.
Expected behavior
When I use Amplify, I have this constant fear that my app will fall into this push
state where it’s completely unrecoverable. What I expect/would be nice is some way to back out, or rollback, to a point where everything works again. This has happened now a couple times now and the only way forward, which it now looks like I will have to do yet again, is to nuke the entire API and start over.
Issue Analytics
- State:
- Created 5 years ago
- Reactions:12
- Comments:15 (2 by maintainers)
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Top GitHub Comments
@hew I’m also concerned about pushing new features to production. Even after coding and testing in a
dev-something
environment, sometime the new schema will be merged with the old one - and at this point I feel that the problems will arise. Right now my plan is to deploy a new master with all the features, transfer the data from old to new database and finally change the clients endpoint.During development iterations I did several changes to the API, but 99% of them were not pushed by
amplify api push
. I believe the worst part is the time that the CLI take to figure the errors or send the updates. With ~10 types, the stack takes around 20 minutes to complete. Depending the stage it fails, it takes 30 minutes for one try.I’m afraid that due some deadlines there won’t be another option to deliver our product, but I’m counting the amplify-cli will evolve in such a way that the push will work flawlessly.
What would be a good temporary strategy if this happens in a production environment?
Checking out to a new env would mean new datasources (which we dont want) and at the same point cannot stop updating the models if there is an urgent need.