Here's my top 3 concept shifts that are a kind of learning curve to technologists who are moving from traditional IT to Cloud:
- pet versus herd - the "pet versus herd" mentality is a crude term that reduces compute resources to a commodity yet exposes emotional baggage. Technologists traditionally treated their systems like pets, including the humorous personification of computers, whereas Cloud treats systems like herds, including the expected losses and gains of components. This has little to do with DR (Disaster Recovery) and everything to do with perspective. A less caricatured comparison is seeing how the traditional datacenter design goal was to provide always-on services by keeping the component instances always-up, while the Cloud design expects components to be in various states of utility but the services themselves are to never be interrupted. This design shift has been epitomized by Netflix's Chaos Monkey.
- Infrastructure as code - some have assigned the concepts of "infrastructure as code" to a new role called DevOps, but whatever you call this change the fundamental shift is:
- a) from infrastructure responding to the application
- b) the application requesting infrastructure.
- don't repeat yourself - a key differentiator with Cloud versus traditional datacenter hosting is using services the Cloud provider offers. Some of these services are akin to SOA (Service Oriented Architecture) but that has been around for awhile, instead I mean the IaaS (Infrastructure as a Service) concept that keeps popping up in Cloud discussions, as well as automation. Automation always reeks of job insecurity in IT but actually addresses long standing waste in operations where we think our infrastructure requires some unique solution but really boils down to reinventing the wheel. The shift is similar to developers switching to "don't repeat yourself" frameworks.
- eMail and messaging
- virtual machines and images
- network storage and disk volumes
- virtual and private networks
- firewalls and routers
- databases and datasets
- authentication and access mechanisms
- logging and auditing
- load distribution
- web services
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