Tuesday, November 23, 2010

Defending the Private Cloud

Phil - You know I love hyperbole as much as the next guy, but come on... discrediting the private cloud?? (and to those who aren't aware - I've corresponded with Phil for just over 7 years and have a sincere respect for him... but that doesn't mean I won't rip into his posts ;-)

Phil writes:
"Back in January, I made a controversial prediction that private clouds will be discredited by year end. Now, in the eleventh month of the year, the cavalry has arrived to support my prediction, in the form of a white paper published by a most unlikely ally, Microsoft."
A whitepaper from Microsoft is the cavalry? Wow - it must have been written by Bill Gates himself! Or... a couple noobs with MBA's and banking backgrounds... But to be fair, the paper rocks. It's dead on. It says that the cloud model is a good one - and that *eventually* more and more applications will be a good fit for the large scale public clouds.

The cool stuff described in the paper is evolving; it will take time (like a decade). That said... let's take a look at the realities that my clients live with on a daily basis:

1. ALL (not some) of my large clients have a mixed computing environment including some combination of AIX, Solaris and Z. NONE (not some) of the public cloud providers have options for supporting all of these environments. I know, you're thinking to yourself... well, they should just port the applications to Linux/Wintel and all would be good. However, in the vast majority of the cases, the applications are packaged software and my clients have little influence over the vendors who own them. So, to be clear - a significant portion of the applications are not targets for the current large scale cloud providers (like Amazon, Microsoft, etc.)

2. Most applications are data intensive and coupled together. This presents a problem when you want to move applications from your internal data center to a public cloud. I compare it to pulling out a paper-clip from your desk drawer only to find it bound to a bunch of other paper-clips. Enterprise applications are often glued together, with either low latency requirements between them or requiring large amounts of data to be moved between them (not good if you have remote data centers with thin pipes and ingress/egress fees.) **Phil, it's about Loose Coupling ;-)

3. Hardware and software provisioning times in the enterprise are embarrassing. The amount of time/money that is wasted waiting for new environments to be procured, stood up, tested, secured, etc. would astound you. The pain is real TODAY - and waiting a decade for a public cloud to be able to support the half-dozen hardware platforms, operating systems, COTS licenses, etc. you need to perform integration testing on isn't an option.

4. Mankind didn't suddenly change in 2010. It turns out that wholesale moves from one computing model to another is not in the corporate DNA. Enterprises who excel at mitigating risks are taking incremental steps to the cloud. First, they're interested in finding out simple things like "how will my business critical application perform if we virtualize it?" or... "If we moved our data intensive application off of our vertically scaled mainframe onto a horizontally scale commodity compute (share nothing) architecture - - will it still perform?" You see... enterprise I.T. has lots of unknowns around cloud architectures. It will take some time for them to understand the basics. Once they answer the architectural questions, figuring out who hosts it is rather simple problem (price, service & reliability).

Private cloud is a natural stepping stone. Most I.T. professionals that I have met do not understand the architectures, processes and operating models (regardless of public or private). Pushing naive people to a public cloud where their mistakes will be hidden by a magically elastic service interface is *not a good idea*. Trust me... it shows up when they get the bill. Instead, I wholeheartedly recommend a stepwise approach to learning about horizontal scaling, sharding, MapReduce, BigData, multi-tenant services, etc. in an environment where they can observe actions and outcomes.