We're long into the hype cycle of cloud computing. That means clear criteria to assess and evaluate the different options are critical. Which of the many cloud approaches should medium to large enterprises take to optimize their data center operations?
Typically, the cloud is envisioned as an accessible and low-cost compute utility in the sky that's always available. Despite this lofty promise, companies will need to select and build their cloud environment carefully to avoid fracturing their computing capabilities, locking themselves into a single, higher-cost environment, diminishing their ability to differentiate themselves and gain competitive advantage -- or all three.
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The chart below provides a primer on the different types of cloud computing. Note the positioning of the two dominant cloud types:
-- Specialized software-as-a-service (SaaS), where the entire stack, from server to application (even version), is provided with minimal variation.
-- Generic infrastructure- and platform-as-a-service (IaaS and PaaS), where a set of server and operating versions is available with types of storage. Any compatible database, middleware or application can be installed to then run.
A private cloud essentially is IaaS that an enterprise builds for itself. The private cloud is the evolution of the corporate virtualized server and storage farm to a more mature instance with clearly defined service configurations, offerings and billing, as well as highly automated provisioning and management.
Another technology that affects the data center is the engineered stack. This is a further evolution of the computer appliancesthat have been available for decades -- tightly specified, designed and engineered components integrated to provide superior performance and cost.
These devices typically have been in the network, security, data warehouse and specialized compute areas. Firewalls and other security devices have long leveraged this approach, whereby generic technology -- CPU, storage, OS -- is closely integrated with special-purpose software and sold and serviced as a packaged solution. The engineered stack approach has moved into data analytics, application servers and middleware.