The debates rage on about "Public Clouds" and "Private Clouds" and which is more appropriate for serious computing efforts, including in business systems and all across the universe of applications.
Most vendors, not surprisingly, line up behind the approach that best suits their product offerings.
For example, SAAS vendors (Salesforce, NetSuite, SuccessFactors) say that multi-tenant applications are the Cloud, citing the need for a business solution with shared, multi-tenant software resources, including databases, are needed to truly make the Cloud useful. Yet many of these vendors are often criticized for not providing "open" models, so still some long-term questions remain. Yes, these Clouds are easy get into, but how do you get out of them if necessary?
The infrastructure-as-a-service crowd (Amazon's EC2, Google App Engine, Rackspace) will suggest that only infrastructure is the "true" Cloud, meaning essentially renting clean servers by the minute and storage by the byte represent the original "open" Cloud vision, enabling applications to be moved from Cloud to Cloud without difficulty. However, this is just servers and storage in the end (at least for now), so the user still has to build everything themselves. Ok for some, not entirely useful for most.
And of course the enterprise software folks (Oracle, SAP, IBM) often claim that the Cloud can and should be "Private" because it's a better security model and enables you to manage it within the organization. This enables them to capitalize on the hype of the Cloud without having to change too much of their actual offerings. Of course the challenge with this model is the lack of sharing licenses or hardware across organizations becomes quite expensive, and quite frankly we have had this model before under other names such as "mainframe", "client-server" and other "in-house" architectures. Sure, there is some incremental innovation and usefulness, but it's not too much different than what has always been offered, just another iteration.
So while there are valid use cases for each of the above scenarios, there is one thing I want to point out with Public versus Private Cloud discussions when businesses are unsure which route to go. It goes all the way back to the birth of the Cloud as a concept itself.
The reason we even have the Cloud in the first place is that heavily-trafficked Web sites such as Google and Amazon found they had to build massive, high performance, scalable systems to be able to handle the processing load at peak times (Amazon at Christmas for example). This meant that during non-peak times, they found themselves with lots of excess, unused computing capacity.
This of course spawned the idea that they could leverage this excess capacity, as well as their expertise in managing high-performance, distributed, "Web scale" computing technology as an additional line of revenue, and possibly launching a brand new industry of opportunities. Hence, the Cloud was born.
The one key piece of this Cloud concept is "expertise". This is something that you get in Public Cloud environments that you don't get in Private Clouds. With Private Clouds, you get all of the hardware and software (and the corresponding purchased licenses) that you need, but you don't have a team of experts that have been running that platform for years monitoring, managing, and supporting that platform in real-time while you use it, including having visibility into it as it runs. By definition you therefore don't have engineers supporting the success of your application systems on a minute-by-minute basis.
This real-time team of experts, and their associated expertise developed over time, is something you get inherently in the Public Cloud scenario. The folks who run these systems have as their core mission in life to keep the platform up and running, battle test it over time, improve it, enhance it, test it, analyze operational data, review performance charts, improve and enhance it again, and on and on, day after day.
Although a bit overused, the electric generator is a good example of demonstrating the difference. If you have your own electrical generators powering your home, it doesn't matter that thousands of other people have one just like it in their homes. If it goes down, you are on your own, and it's your responsibility to keep the electricity flowing from room to room. But if you plug into the electric grid run by your local power company, and there is an outage while you are having dinner somewhere, likely it will be fixed before you even get home from the restaurant. And you might not even notice there was a problem since you weren't at home (you were out dining in the "Dinner Cloud" and outsourcing the washing of dishes). This is because the system was monitored, a problem was detected, and a team was ready to spring into action once the outage occurred.
How long would it have taken to call the generator repairman to get him scheduled to come out with a power outage in your own generator? There's a reason electricity grids have evolved the way they have.
Oh, and all of the innovation occuring behind the scenes at the power company on a day to day basis? It comes to you automatically, often while you sleep, as opposed to a new giant chunk of hardware arriving every 18-24 months that you have to figure out how to configure and get up and running again.
So how is this relevant to StrikeIron?
Well, the same is also true in our case. While we are more the Software-as-a-Service variety of Cloud Computing (and in our case "data-as-a-service"), we recognize that users have a choice in the way to obtain the type of functionality we offer. A lot of the powerful capabilities we have such as our Cloud-managed Contact Record Verification Suite, such as real-time telephone, address, and email verification, could also be purchased and brought in-house as software applications and raw data sources, and a similar result could be achieved in terms of better, more usable customer data assets. The approach would just be a heck of a lot different.
In the latter scenario, all of the verification reference data would have to be managed and maintained internally. One would have to acquire the software and data files, and then get the functionality up and running. It would then have to be designed and delivered in such a way to be able to handle the various loads of data verification that might appear from different applications at different times, and often in high volume scenarios. Also, all of the other expertise around availability, testing, updating, and the usual effort associated with in-house solutions would have to be developed internally.
With us, all we do day in and day out is focus on verifying and delivering our real-time data verification capabilities to thousands of applications simultaneously with a very high level of performance at all times, delivering 24x7x365. All you need to do, just like the electric company, is plug into us. All of the data management, updating, software maintenance, and performance testing and improving is done by us, with all of the heavy lifting abstracted from you.
Since we launched our system in 2005, we have constantly improved our finely-tuned delivery and fault-tolerant capabilities, including load-balancing, high speed data I/O, redundancy, external monitoring, and everything else we have to provide to be able to support our customers and their production applications. And we are getting smarter and better about how we go about it every day. This expertise is something that each and every one of our customers gets to leverage with every single call to our system. This is why we have only had minutes of downtime over the last four years.
So could in-house solutions provide the same end result? Maybe in the sense that yes you could end up with good clean customer data somehow on your own. But at what cost, effort, and with what missed opportunities? Focus on your core business, and leave the external data verification effort to us. We will keep the lights on. Guaranteed.
