At your job, you have a workload, which consists of all the tasks you need to accomplish during the course of the day. However when it comes to cloud computing, the term “workload” takes on a completely different meaning. In this context, a workload is an executable service or collection of code; because the cloud allows a number of computer assets to run the same tasks, you might think of a workload as the amount of work to be completed by computer resources within a certain period of time.
Most businesses these days have some type of hybrid cloud environment, where software and data is shared amongst devices through on-site, private and public platforms. If you are eager to boost performance and productivity within your organization, you need to be certain that your hybrid cloud workload is utterly perfect. Here’s a rundown of typical workloads suitable for the hybrid cloud, to include who should use them and why.
A batch workload processes huge volumes of data, such as information within cellphone bills or the results of thousands of online transactions. Because batch workloads consume a substantial amount of computing and storage resources, most organizations want to find ways to make batch workloads faster and easier to process.
Typically, batch workloads are not time-sensitive, and they consist of predictable, well-documented methods. As a result, they are excellent candidates for automation within the hybrid cloud. You can schedule batch workloads to execute on a regular schedule when more pressing real-time tasks are running, and because the cloud never sleeps, you can make the most of hours in the evening or at night, when your workers will go home and systems will be free to crunch numbers.
Transactions are a necessary element of every business, but in recent years, many organizations have found their transactional workloads becoming increasingly complex. Ecommerce allows businesses to reach across partners and suppliers, meaning transactional workloads must incorporate these computing environments to accurately reflect ongoing transactions. Though traditionally, transactional workloads were best kept in a single system on a private cloud, you might need to expand your transactional workloads to the hybrid cloud to facilitate its complexity.
As data has proven itself overwhelmingly important to the success of the modern business, analytic workloads have consumed more and more computing resources. In many cases, you can reduce the demand of analytics by focusing more intently on the right kinds of data; too often, businesses collect and analyze as much data they can, regardless of what it might (not) do to improve their performance. However, if analytic workloads continue to take up a significant portion of your resources, you can migrate it to the hybrid cloud. This is because analytics typically relies on a variety of data sources — from public websites, private clouds, data warehouses and more — necessitating a hybrid environment.
The objective of a high-performance workload may vary from another high-performance workload. What defines this category of hybrid cloud workload is that it contains a specialized process with highly scientific or technical requirements. As is the case with other workloads on this list, the complexity of high-performance workloads demands excessive computing capabilities —which means they are well-suited for specialized hybrid clouds that are optimized for performance.
The most common type of workload, and thus affecting essentially every environment in a data center or a cloud, database workloads must be fine-tuned and continuously managed to support the service using the data. As you assemble the cloud environment that will handle your database workload, you could consider the size of the database as well as its sophistication. It might be that you need to build an environment suited to huge, high-performance database workloads; in which case, you should be using more than the hardware’s operating system to support its requirements.
Not all workloads are well-suited for the cloud. For instance, if your workload demands high-performance network storage, low latency of legacy applications or high throughput database clustering, it is better to build an on-site data center that can provide you with the storage and speeds you need. However, if you find your systems bogged down by any of the workloads listed above, you should get help in building a hybrid environment that fits your requirements.