Serverless Python on AWS Lambda using the Serverless Framework
summary
Claims a practical path to run Python on AWS Lambda using the Serverless Framework and demonstrates it end to end: uses Serverless Framework with AWS Lambda, API Gateway, DynamoDB, S3 and AWS Comprehend, packages Python 3.6/3.7 with a Docker-based build to avoid compiled dependency issues, and runs commands like SLS deploy/remove and SLS logs. Builds a working hashtag sentiment analyzer that fetches ~50 tweets every 10 minutes, stores them in DynamoDB, analyzes sentiment, generates a Jinja HTML page and serves it from S3.
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chapters (11)
- 0:00Start
- 1:27About TRIBE
- 4:37Setting up a Traditional Server-based Architecture
- 5:57Serverless Computing
- 8:01Considerations when venturing into serverless
- 11:19Let's create a simple AWS Lambda function!
- 14:06Events that trigger AWS Lambda Functions
- 15:28Use-cases of AWS Lambda Functions
- 16:55What is Serverless Framework?
- 18:45Why use Serverless Framework?
- 26:04Serverless Framework with Python runtime caveats
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