Workload modeling becoming essential to reducing the risk of new storage
Data storage is growing at a rate of 30-50% per year and storage-related expenditures to support this growth are fast approaching 40% of the typical global 1000 IT infrastructure budget. As more applications are deployed in big data, virtualized and cloud environments, application workloads are increasing in complexity. Users are accessing data in new, more dynamic ways--at unpredictable times--which is causing ‘workload drift’ and demand spikes. Solutions that understand and can model these traffic patterns and predict response times will be essential to ensuring business-critical application performance under worst-case conditions.
“Successful storage deployments require a thorough understanding of application workloads. With deep insight into these workloads, IT organizations can make optimal decisions on storage architecture, technologies, products, and configurations and reduce the risks associated with infrastructure changes,” said
“I compare Load DynamiX with my smart phone,” says
The new Load DynamiX Workload Insight Manager provides detailed analysis of production application workloads including a full command mix, file size, and block size distribution. It uses a web-based GUI to create workload scenarios that can be run on purpose-built high-performance load generation appliances. A new visual testbed interface enables easy test configuration, automated running of simulations, and a shared library for multiple users to collaborate across the enterprise.