Cloud platforms from Amazon, Microsoft Azure, Google, and Oracle provide on-demand services that are billed on a pay-as-you-go basis. Cloud-based services provide a technical infrastructure and distributing computing building blocks that individuals and companies use as an alternative to running their own servers.
Recent cloud-based tasks for intellectual property and real estate projects have involved the following features, including those I use on a daily basis.
Amazon AWS
Route 53 for domain name registration and DNS Hosted Zones.
S3 buckets for web hosting with custom domain names and generalized file storage.
WorkMail to manage email accounts with custom domains hosted in Route53.
Lambda serverless computing for e-commerce websites
RDS for MySQL databases accessed with the standalone Oracle-based MySQL Workbench administration tool.
RDS for PostgreSQL databases accessed with the SQL Workbench/J standalone query tool.
DynamoDB to run a NoSQL database accessed through AWS.
CodeCommit for private Git repositories with IAM roles and Git credentials.
PHP Web App using a MySQL database backend with VPC (virtual private cloud) using public/private subnets, security groups, EC2 instance, key pair, and SSH access to EC2 to configure the Apache web server.
Elastic Beanstalk to manage a continuous deployment platform using CodeCommit, CodePipeline, and CloudWatch to monitor code change.
Elastic Beanstalk to run a PHP web application while tracking version updates.
Athena to analyze S3 server access logs using SQL.
SageMaker for machine learning models that involved dataframes with the pandas package and the XGBoost algorithm.
Lambda with python code and test events.
Cloud9 to run Python code.
Microsoft Azure
Blob Storage that included web hosting with CDN profile configuration, a custom domain name, SSL certificate, CNAME updates, and URL redirect rules.
SQL Database to run Microsoft SQL Server accessed through the Azure query editor.
SQL Data Warehouse accessed through the Microsoft SQL Server Management Studio standalone application to run queries against data stored in Azure.
Data Lake (Storage Gen2) accessed through the standalone application Azure Storage Explorer to upload files to a blob filesystem.
Data Lake Analytics with U-SQL (a combination of SQL and C#) linked to Data Lake Storage.
Virtual Machines to run Linux Ubuntu 18.04 LTS accessed through SSH with RSA public keys and inbound rules.