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After completing the command setup, you already created a user in your AWS whose AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY are displayed on your screen.
It asks if we want to modify the pipeline as it already exists select: No
After completion of this, it displays the stack name, pipeline Execution Role, Cloud Formation Execution Role, artifact Bucket. Use all in actions env's.
Update the keys you got in the Github secrets.
Permission to add:
Create a policy Named: feature-flag-lambda-db-role and Add this policy to all the Lambda's as it update values in DB and invokes rate limiter lamda.
In between setup, you are asking to watch a YouTube video of 25 minutes to do the setup.
Can you please mention all the steps required in the issue itself? I don't want to watch the YouTube video here that is 25 minutes long
In between setup, you are asking to watch a YouTube video of 25 minutes to do the setup. Can you please mention all the steps required in the issue itself? I don't want to watch the YouTube video here that is 25 minutes long
@prakashchoudhary07 Sir, That video is for reference. I will make it better till tomorrow and get back to you.
Steps to deploy for staging
Create a DB for staging.
Tables in DynamoDB
featureFlag
Partition Key - id (string)
featureFlagUserMapping
Partition Key - userId (string)
Sort Key - flagId (string)
requestLimit
Partition Key - limitType (String)
no sort key here
sam pipeline init --bootstrap
.https://www.youtube.com/watch?v=jBCf8g7VXhw This video will guide you with the command specifics (Just for reference).
Steps after running
sam pipeline init --bootstrap
After completing the command setup, you already created a user in your AWS whose AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY are displayed on your screen.
No
After completion of this, it displays the stack name, pipeline Execution Role, Cloud Formation Execution Role, artifact Bucket. Use all in actions env's.
Update the keys you got in the Github secrets.
Permission to add:
feature-flag-lambda-db-role
and Add this policy to all the Lambda's as it update values in DB and invokes rate limiter lamda.As we change the concurrency of the other Lamda's when limit is reached to close the lambda's and reset the limit and start all the lambda's again.
Things to do:
sam pipeline --bootstrap
.template.yaml
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