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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 a practical introductory tutorial to using Amazon Redshift as an OLAP Data Warehouse solution for the popular Pagila Movie Rental dataset. I start with a basic overview of the unique architecture Redshift uses to accomplish its scalable and robust use case as an enterprise cloud data warehouse. Then armed with this basic knowledge of Redshift architecture I move on to give a practical example of designing a schema optimal for Redshift based off the Pagila sample dataset.
In this article I demonstrate how to provision Linux based EC2 Virtual Private Servers along with Elastic Block Storage (EBS) Volumes using Terraform. Then I complete the use case by demonstrating how to mount the EBS volume devices on Linux XFS filesystems.
In this article I dive into partitions for S3 data stores within the context of the AWS Glue Metadata Catalog covering how they can be recorded using Glue Crawlers as well as the the Glue API with the Boto3 SDK.
In this article I demonstrate using a Python based AWS Lambda SAM project with the AWS Data Wrangler Lambda Layer to perform data format translation from GZipped JSON files into Parquet upon an S3 upload event.
In this How To article I demonstrate how to use the AWS CLI to create an Amazon Elastic Map Reduce (EMR) Cluster along with some common supplementary resources for experimentation and development on an EMR cluster.
In this article I review key characteristics and functionality of Apache Hive and how you can utilize Amazon Elastic MapReduce (EMR) to provision a Apache Hive Cluster for experimentation and big data processing and analytics.
In this article I present the concepts of AWS Virtual Private Cloud (VPC) Endpoints through simple examples of setting up and consuming AWS services made explicitly accessible through VPC endpoints.
In this article I present a demonstration of how one can use Cloud Watch Metrics and Alarms to monitor CPU Utilization for an AWS RDS database consisting of a primary read/write instance and a read-only replica.
In this article I discuss the benefits of architecting observability into your AWS Aurora PostgreSQL deployments through the use of CloudWatch Logs, Metric Filters, and Alarms.
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