Understanding Workloads Because computing requirements are varied, so too are the  workloads. Whether you’re using an IaaS for infrastructure  or you’re developing SaaS applications using a PaaS, here are  some of the kinds of workloads you’re likely to find in a cloud  environment: ✓ Batch workload:  These workloads operate in the background and are rarely time sensitive. Batch workloads  typically involve processing large volumes of data on a  predictable schedule (for example, daily, monthly, and  quarterly). ✓ Database workload:  These are the most common type  of workload, and they affect almost every environment  in the data center and the cloud. A database workload  must be tuned and managed to support the service that  is using the data. A database workload tends to use a lot  of Input/Output (I/O) cycles. ✓ Analytic workload:  Organizations may want to use analytic services in a cloud environment to make sense  of the vast amounts of data across a complex hybrid  environment. In an analytics workload, the emphasis is  on the ability to holistically analyze the data embedded in  these workloads across public websites, private clouds,  and the data warehouse. A social media analytics workload  is a good example of this. These kinds of workloads tend  to require real-time capabilities. ✓ Transactional workload:  These are the automation of  business processes such as billing and order processing.  Traditionally, transactional workloads were restricted  to a single system. However, with the increasing use of  electronic commerce that reaches across partners and  suppliers, transactional workloads must be managed  across various partners’ computing environments. These  workloads are both compute and storage intensive.  Depending on the cost-benefit analysis, it’s likely that  complex transactional workloads are best suited to a private cloud. These materials are the copyright of John Wiley & Sons, Inc. and any  dissemination, distribution, or unauthorized use is strictly prohibited. Cloud Services For Dummies, IBM Limited Edition  36