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April 19, 2008

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Nicholas Fiekowsky

Karen - you & Guy are getting closer, but you haven't touched on infrastructure - the wind beneath the cloud. Google has a 10x - 100x capacity / dollar advantage. Plus scalability, massive multi-threading, distributed operation...

Start with traditional IS design assumptions:

- Any specific application or middleware runs on a small number of servers and dedicated storage systems.

- Hardware efficiency is relatively unimportant since capacity / dollar constantly improves, and is relatively small compared to total project cost or business value.

- Therefore the servers and storage should be bulletproof. Redundancy provides reliability - dual data paths, dual power supplies, parity checked memory, RAID for disk, clustered processors, DR site with replicated configuration...

- Since the component count per application is relatively low, management cost per component is relatively unimportant. Also, specific component failures will be rare. They should not stop the application but are likely to introduce a potential single point of failure. They therefore require prompt human intervention to address the problem - replace the failed drive in the RAID array, failed processor in the cluster, broken SAN or network component...

- Since applications run on a small number of servers, parallelism/threading is relatively unimportant. Transaction-level parallelism with record-level locking is adequate.

Microsoft SharePoint is a poster-child for this design heritage. ALL data is in MS SQL Server. MS SQL Server needs lots of disk acreage per megabyte of data, and it's gotta be high-performance disk to support a database. Oh - did you remember to set up a duplicate configuration featuring those acres of high-performance storage to provide high availability / disaster recovery?

An online Microsoft hosting vendor (with appealing Exchange prices) lists $70 / month ($840 / year) to host 5 GBytes of SharePoint data. Compare that with Google with 25 GBytes for $50 per year. Is SharePoint 17 times better before factoring in the difference between 5 & 25 GBytes?

Google's technology is shaped by a different set of assumptions:

- Servers are hard to get if you're a grad student at Stanford so the infrastructure should extract maximum value from each one.

- Servers are fallible (grad students getting by on scrounged hardware; later scaling out with thousands of servers) so the infrastructure should insulate service delivery from any specific component failure.

- There are tens or hundreds of thousands of servers, so the infrastructure should require zero human involvement to bring a new machine into full production, or to cope with failure.

- Hardware is a large percentage of operating cost, so the infrastructure should automatically maintain the proper degree of redundancy, while extracting maximum business value from that redundancy - see commercial success driver.

- Since an individual server failure is unimportant, servers should be designed to provide maximum output from the least expensive hardware and lowest possible power consumption. This means no redundancy except probably dual NICs to separate network switches, and commodity class components.

- Commercial success depends on rapidly processing huge volumes of complex search queries. The infrastructure should natively farm each work item across the optimum number of servers to provide eye-blink response time.

- Plus Google grabbed oodles of fiber at fire-sale prices after the telecom meltdown earlier this century.

How can the incumbents develop this kind of sustaining design & scale as they move into the cloud?

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