Today, one of the key advantages of cloud computing is the speed at which you can customize your environment to suit your changing business needs. In a more traditional data center environment, that’s not necessarily the case.
As an example, imagine that you have a project that has an unexpected need for an additional 10TB of storage, but you don’t have 10TB available and the project is time sensitive. In a traditional data center environment, this would mean evaluating storage options; creating purchase orders, delivery, installation and configuration of storage systems – all of which is time consuming and may interfere with your ability to win a case. Even with the best will in the world, this is likely going to take a couple of weeks for implementation.
In a cloud environment, an information-on-demand requirement of this size can be achieved in less than 15 minutes. You simply provision the type of storage that you want, in the region that you want, and you are done in a matter of minutes.
Due to the cost model of cloud computing, you typically only pay for what you use, on a per-hour basis. This has clear advantages when your imaginary 10TB project completes, because you simply securely wipe and decommission the storage and cease paying for it. When we consider scalability, we naturally think about scaling up, but with the cloud environment we can also consider scaling down in real time. This is potentially important for your organization with respect to project-specific matters, overall data management efficiencies and even performance. In these instances, having the ability to scale down can prove helpful in saving significant costs when your needs decrease.
Should you need more processing power at short notice, additional IOPS (Input/Output Operations per Second) can be provisioned for the time that you need it. Again, it can be scalable both for increase and decrease as business needs require. In addition, as hosted platforms (like your hosted document review tool, for example) are typically scalable, that service can also be scaled up and down, in addition to servers and storage.
While our hypothetical 10TB example is storage, the same holds true for servers. Imagine you need five new servers, all running an enterprise version of SQL, to perform some advanced analytics. With cloud capabilities, this can be provisioned in a matter of minutes, instead of the weeks other methods might take, and cloud scaling doesn’t require additional software or hardware purchases. Again, once the project has finished, the servers can be decommissioned, and you no longer have to manage the additional environment or bear the cost for its now-unused servers and storage.
