Open this lesson in your favourite AI. It'll walk you through the why, explain the demo, and quiz you on the try-it list.
Each provider has a personality: AWS is the most complete and the most byzantine, Azure is the enterprise/Microsoft shop default, GCP is the data and ML house, and DigitalOcean is the developer-experience and predictable-pricing play. You will pick differently for a side project, a Series B SaaS, and a regulated bank — and the wrong default costs you both money and migration pain.
Query each provider's compute catalog for a comparable small instance to feel the shape of each CLI and pricing surface.
Use these three in order. Each builds on the one before.
In one paragraph, explain how AWS, Azure, GCP, and DigitalOcean differ in target audience and pricing philosophy like I'm new to cloud.
Walk me through how each provider's pricing model actually works step by step — list price vs sustained-use vs reserved vs flat-rate — and why DigitalOcean can quote a flat monthly number while AWS cannot.
Given a fintech that needs HIPAA + SOC2 + a strong data-warehouse story and predictable monthly cost, rank AWS, Azure, GCP, and DigitalOcean for them and explain the trade-offs.
# AWS — t3.micro on-demand price in us-east-1
aws pricing get-products --service-code AmazonEC2 --region us-east-1 \
--filters Type=TERM_MATCH,Field=instanceType,Value=t3.micro \
Type=TERM_MATCH,Field=location,Value="US East (N. Virginia)" \
Type=TERM_MATCH,Field=operatingSystem,Value=Linux \
Type=TERM_MATCH,Field=tenancy,Value=Shared \
Type=TERM_MATCH,Field=preInstalledSw,Value=NA \
Type=TERM_MATCH,Field=capacitystatus,Value=Used \
--max-results 1