The Elasticity of the Cloud
Today's podcast discussion focuses on the economic benefits of cloud computing -- of how to use cloud-computing models and methods to control IT cost by better supporting application workloads.
As we've been looking at cloud computing over the past several years, a long transition is under way, of moving from traditional IT and architectural method to this notion of cloud -- be it private cloud, at a third-party location, or through some combination of the above.
Traditional capacity planning is not enough in these newer cloud-computing environments. Elasticity planning is what's needed. It's a natural evolution of capacity planning, but it's in the cloud.
Therefore, traditional capacity planning needs to be reexamined. So now we'll look at how to best right-size cloud-based applications, while matching service delivery resources and demands intelligently, repeatedly and dynamically. The movement to pay-per-use model also goes a long way to promoting such matched resources and demand, and reduces wasteful application practices.
We'll also examine how quality control for these cloud applications in development reduces the total cost of supporting applications, while allowing for a tuning and an appropriate way of managing applications in the operational cloud scenario.
Here to help unpack how Cloud Assure services can take the mystique out of cloud computing economics and to lay the foundation for cost control through proper cloud capacity management methods, we're joined by Neil Ashizawa, manager of HP's Software as a Service (SaaS) Products and Cloud Solutions. The discussion is moderated by me, BriefingsDirect's Dana Gardner, principal analyst at Interarbor Solutions.
Listen to the podcast (21:38 minutes).
Here are some excerpts:
Neil Ashizawa: Old-fashioned capacity planning focuses on the peak usage of the application, and it had to, because when you were deploying applications in-house, you had to take into consideration that peak usage case. At the end of the day, you had to be provisioned correctly with respect to compute power. Oftentimes with long procurement cycles, you'd have to plan for that.
In the cloud, because you have this idea of elasticity, where you can scale up your compute resources when you need them, and scale them back down, obviously that adds another dimension to old-school capacity planning.
The new way look at it within the cloud is elasticity planning. You have to factor in not only your peak usage case, but your moderate usage case and your low-level usage as well. At the end of the day, if you are going to get the biggest benefit of cloud, you need to understand how you're going to be provisioned during the various demands of your application.
If you were to take, for instance, the old-school capacity-planning ideology to the cloud, you would provision for your peak use-case. You would scale up your elasticity in the cloud and just keep it there.
But if you do it that way, then you're negating one of the big benefits of the cloud. That's this idea of elasticity, and paying for only what you need at that moment.
One of the main factors why people consider sourcing to the cloud is because you have this elastic capability to spin up compute resources when usage is high and scale them back down when the usage is low. You don't want to negate that benefit of the cloud by keeping your resource footprint at its highest level.
What we're now bringing to the market works in all three cases [of cloud capacity planning]. Whether you're a private internal cloud, doing a hybrid model between private and public, or sourcing completely to a public cloud, it will work in all three situations.
The new enhancement that we're announcing now is assurance for cost control in the cloud. Oftentimes enterprises do make that step to the cloud, and a big reason is that they want to reap the benefits of the cost promise of the cloud, which is to lower cost. The thing here, though, is that you might fall into a situation where you negate that benefit.
If you deploy an application in the cloud and you find that it's underperforming, the natural reaction is to spin up more compute resources. It's a very good reaction, because one of the benefits of the cloud is this ability to spin up or spin down resources very fast. So no more procurement cycles, just do it and in minutes you have more compute resources.
The situation, though, that you may find yourself in is that you may have spun up more resources to try to improve performance, but it might not improve performance. I'll give you a couple of examples.
If your application is experiencing performance problems because of inefficient Java methods, for example, or slow SQL statements, then more compute resources aren't going to make your application run faster. But because the cloud allows you to do so very easily, your natural instinct may be to spin up more compute resources to make your application run faster.
When you do that, you find yourself in is a situation where your application is no longer right-sized in the cloud, because you have over-provisioned your compute resources. You're paying for more compute resources and you're not getting any return on your investment. When you start paying for more resources without return on your investment, you start to disrupt the whole cost benefit of the cloud.
Applications need to be tuned so that they are right-sized. Once they are tuned and right-sized, then, when you spin up resources, you know you're getting return on your investment, and it's the right thing to do.
Whether you have existing applications that you are migrating to the cloud, or new applications that you are deploying in the cloud, Cloud Assure for cost control will work in both instances.
Cloud Assure for cost control solution comprises both HP Software and HP Services provided by HP SaaS. The software itself is three products that make up the overall solution.
The first one is our industry-leading Performance Center software, which allows you to drive load in an elastic manner. You can scale up the load to very high demands and scale back load to very low demand, and this is where you get your elasticity planning framework.
The second solution from a software's perspective is HP SiteScope, which allows you to monitor the resource consumption of your application in the cloud. Therefore, you understand when compute resources are spiking or when you have more capacity to drive even more load.
The third software portion is HP Diagnostics, which allows you to measure the performance of your code. You can measure how your methods are performing, how your SQL statements are performing, and if you have memory leakage.
When you have this visibility of end user measurement at various load levels with Performance Center, resource consumption with SiteScope, and code level performance with HP Diagnostics, and you integrate them all into one console, you allow yourself to do true elasticity planning. You can tune your application and right-size it. Once you've right-sized it, you know that when you scale up your resources you're getting return on your investment.
You want to get a grasp of the variable-cost nature of the cloud, and you want to make this variable cost very predictable. Once it's predictable, then there will be no surprises. You can budget for it and you could also ensure that you are getting the right performance at the right price. ... If you're thinking about sourcing to the cloud and adopting it, from a very strategic standpoint, it would do you good to do your elasticity planning before you go into production or you go live.
Dana Gardner is president and principal analyst at Interarbor Solutions, which tracks trends, delivers forecasts and interprets the competitive landscape of enterprise applications and software infrastructure markets for clients. He also produces BriefingsDirect sponsored podcasts. Follow Dana Gardner on Twitter. Disclosure: HP sponsored this podcast.