akandebolaji / cloud-resume-backend Goto Github PK

Epic accomplishment, great work all around. Your Python skills in particular are impressive -- you are one of the only people I've seen make use of DynamoDB's UpdateItem "ADD" operation to incur a maximum of one DynamoDB access per API call. Great work.

Just a few overall code comments as you take your AWS and serverless development skills to the next level:

• Consider using structured JSON statements as logs -- this makes them easier to search and filter in log analysis platforms. (Very important if you have lots of users hitting your Lambdas!) Here is a great post with some ideas on how to structure Lambda logs: https://theburningmonk.com/2018/01/you-need-to-use-structured-logging-with-aws-lambda/
• Suggestion: don't give your DynamoDB table a custom name. This removes the ability to update some attributes without replacement in CloudFormation. Instead, let CloudFormation name the table, and pass the generated table name to your function as an environment variable or SSM parameter.
• Consider initializing your boto resources outside the Lambda handler, in global space - thus, they will only need to be initialized on cold start, which can speed up function performance.
• As a future improvement, you could check out creating your S3 bucket and CloudFront distribution in CloudFormation and deploying them as part of your front end CI/CD workflow -- that was not a requirement for this challenge, though!

Good luck, and I look forward to sharing your amazing work with the community.