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In this aricle I cover creating rudimentary Data Lake on AWS S3 filled with historical Weather Data consumed from a REST API. The S3 Data Lake is populated using traditional serverless technologies like AWS Lambda, DynamoDB, and EventBridge rules along with several modern AWS Glue features such as Crawlers, ETL PySpark Jobs, and Triggers.
In this article I give an introduction to Online Analytical Processing databases comparing them against traditional Online Transaction Processing Systems. Emphasis is put on designing and building Star Schemas and Reporting tables using Data Engineering processes like Extract, Transform and Load all within a Aurora PostgreSQL database.
In this article I demonstrate how utilize Lambda Layers to share reuable code among multiple Python AWS Lambda functions within AWS Serverless Application Model (SAM) applications.
In this article I demonstrate how to setup a AWS Serverless Application Model (SAM) project for near realtime streaming of CloudWatch logs to S3 using Kinesis Data Firehose. To keep things interesting I'll be using a Python based demo application that exposes two REST APIs, one for scraping and saving quotes from the web to a DyanmoDB table and another for listing the saved quotes.
In this article I discuss the merits of using Lambda versioning and aliases along with the AWS Serverless Application Model's (SAM) built-in capability to utilize CodeDeploy with weighted traffic routing for Gradual Deployments
In this article I demonstrate how to build a serverless REST API using the AWS Serverless Application Model (SAM) framework along with the popular Python based Flask micro web framework.