Google leader says cloud deployment is not the complete answer

August 21

At first I was tempted to not post the analysis performed by Google’s Vijay Gill which concludes that an on-premise deployment may be cheaper than an Amazon cloud deployment if usage is high and constant.

It’s not because I don’t agree, but because the statement seems quite obvious to anyone coming from with any operational background.

In general, if demand is constant and predictable, it makes sense to apply fixed resources such as in-house servers or full time employees against the problem.  If demand is variable or unpredictable, it makes sense to invest more in variable resources such as use-as-you-go cloud resources and seasonal employees.

But ultimately I decided to post Gill’s analysis because it allows me to remind people that most demand models have both a fixed and variable component.

Furthermore, if fixed on-premises and variable cloud deployment models are the resources of the future, doesn’t it make sense to design hybrid applications today that span across both types of resources: your in-house datacenters and the cloud?

Elastic architecture provides you the scalability you need to span; cloud escrow provides you the ability to choose your deployment model.  Stay tuned to DivConq as we continue to explore these concepts and the technologies behind them.

About Jonathan Lampe

Author of 44 articles on this blog.

I have about 12 years of experience designing secure, partially distributed systems (e.g., web farm with some extra load in one remote data center), often in industries such as finance and defense. My solutions and software are currently deployed in mission-critical roles at about 1000 enterprises worldwide. In the last 2-3 years I have turned my technical attention toward more geographically distributed systems and heterogeneous environments (e.g., a mix of operating systems or on-premises and cloud deployments) while maintaining my focus on good UX and great security.


Posted by on 2010-Aug-08 in Amazon EC2, Cloud

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