Distributed Processing
Distributed processing is a revolutionary development in computing models in analytics, scientific tasks, and more computation-heavy applications, as processing loads of direct and dependent jobs as processing tasks is getting bigger in size and more complex, and it would be expensive in terms of resources spent on a single processor to handle them alone. In distributed processing, computation tasks are distributed to multiple processors for efficient processing. Distributed computing offers advantages over traditional processing in terms of real-time scalability, reliability, flexibility, and speed in processing. These products are generally found in SaaS (Software as a Service) platform vendors that offer expanded functionality and cost effectiveness.
Flexibility and Speed in Implementation
It is easier to add computing power in a few minutes by adding a few servers in a cloud or/and computing capacity from a single window, than to take weeks and months going through the purchasing cycle and implementation of on-premises hardware.
Flexibility and Speed in Processing
Distributed processing reduces the risk of failure arising out of lack of enough computing power for jobs to run or waiting for dependent jobs to complete. The more data there is to process, the more time is saved in processing with this strategy.
Flexibility and Better Control on Costs
All vendors propose the flexibility to choose distributed processing when required and switch it off when required to save computer resources. CPU and memory are important factors in cost saving for cloud-based distributed computing. One caveat is that without governance and policy controls, this functionality can be misused by individuals, and instead they can get a massive bill. Flexibility means offering a broad range of virtual machine (VM) sizes, non-virtualized servers, VM on a single tenant’s hosts, and multiple hypervisor choices.
Storage
Storage technology has evolved rapidly, as Gordon Moore predicted. You can say the performance capability of chips is roughly doubling every 18 months, and this amount of time is decreasing every year. The size of devices with the same storage are getting smaller compared to previous years. From a data-warehousing perspective, storage is used as a placeholder before processing, while processing, and after processing data according to business rules.
Note Gordon Moore was one of the pioneers of integrated circuits who gave a prediction which is known as Moore’s Law.
