PE2-6.5 Cloud Platforms & Case Studies
You can describe Google App Engine including traffic management, traffic splitting and scaling types, compare Compute Engine with App Engine, and outline AWS, GCP, Azure, Eucalyptus, OpenNebula and OpenStack.
The App Engine versus Compute Engine comparison is the SaaS/PaaS/IaaS ladder made concrete on one provider, and it is the clearest way to feel the trade rather than recite it. Traffic splitting is worth knowing beyond this course: it is how canary releases and A/B tests are actually performed in production. The open-source stacks matter because they are how a private cloud gets built, and because they show the same architecture without the marketing.
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Google App Engine: traffic management
The first platform studied in detail, and how it routes requests between versions. Traffic management is the feature that makes safe deployment possible.
Traffic splitting and canary releases
Sending a small share of users to a new version first, which is how large services deploy without downtime. It is a practice worth knowing regardless of the platform.
Compute Engine versus App Engine
Two products from the same provider at different levels of abstraction. Comparing them makes the service models from the earlier topic concrete.
Scaling types
The ways a service can grow, vertically and horizontally, automatically or not. Horizontal scaling is what the cloud is actually good at.
Amazon Web Services (AWS)
The largest provider, surveyed. Read for the shape of the service catalogue rather than individual product names.
Google Cloud Platform (GCP) and Azure
The other two major providers. The useful exercise is mapping equivalent services across all three, because the concepts transfer and the names do not.
Cloud software environments: Eucalyptus and Open Nebula
Two open source platforms, which let you run the model on your own hardware. They matter for the private deployment case from the earlier topic.
Open Stack
The open source platform that actually won, which closes the subject. It is what most private deployments are built on today.
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