EZINE:
In this week's Computer Weekly, we look at how artificial intelligence is being used to automate existing jobs, such as IT administrators and customer service agents. Capital One's European CIO talks about how to create an agile business. And we offer tips on how to deal with an Oracle software audit. Read the issue now.
EGUIDE:
Hyper-converged platforms have grown to include secondary storage space; however secondary-storage still faces a plethora of issues. Discover how to best address the problems facing secondary storage and how vendors are promising to make life easier for storage administrators.
EGUIDE:
This expert resource serves as your full guide to object storage implementation, with cloud workload, sync-and-share, API-accessible storage, and more use cases examined. Download now to gain full access, learning how object storage maintains the unstructured data deluge, and view an object vs. file vs. block storage bake off.
VIDEO:
Watch this brief video to discover a storage strategy that can solve these that helps solve your most difficult storage issues. Tune in to learn how you can implement that strategy in your business.
EGUIDE:
Whether physical servers or VMs, there are any number of places where data can be held up. Download this e-guide to learn how to troubleshoot server bottlenecks created by running multiple VMs, and solve NAS and software-defined storage performance problems.
EZINE:
Hyper converged and converged storage in ASEAN: In this issue we look at a software-defined approach to storage management that combines storage, compute, networking and virtualization technologies.
EBOOK:
In this buyer's checklist, learn how hyper-converged systems differ from traditional storage systems and find insights into some of their unique features, as well as guidance for evaluating, purchasing and deploying these systems.
WHITE PAPER:
Highlighted in this custom white paper is a storage solution that offers the simplicity of NAS coupled with the scalability, performance, and simplified management that machine learning, AI, and analytics workloads require.
