Webinar: Which Storage Architecture is Best for Splunk Analytics?

Watch On Demand

According to IDC, by 2020 40 percent of all data will be machine-generated. Much of this data is unstructured log data from web/app servers, mobile app/devices, and internet of things (IoT). Enterprises of all types and sizes are looking at ways to analyze this data to decrease security threats, identify new revenue opportunities and increase operational efficiency. Applications like Splunk are enabling the rapid analysis of this machine-generated data.

But the storage infrastructure is ill-prepared to allow Splunk to achieve its full potential. Join Storage Switzerland and ClearSky Data for our on demand webinar, “Which Storage Architecture is Best for Splunk Analytics?

We discuss the pros and cons of the three most common storage architectures for Splunk, enabling you to decide which makes the most sense for your organization.

  1. Leverage existing storage resources
  2. Deploy a cloud storage and SaaS solution
  3. Deploy a hybrid, Splunk-ready solution

George Crump is the Chief Marketing Officer of StorONE. Prior to StorONE, George spent almost 14 years as the founder and lead analyst at Storage Switzerland, which StorONE acquired in March of 2020. In his spare time, he continues to write blogs on Storage Switzerland to educate IT professionals on all aspects of data center storage. He is the primary contributor to Storage Switzerland and is a heavily sought-after public speaker. With over 30 years of experience designing storage solutions for data centers across the US, he has seen the birth of such technologies as RAID, NAS, SAN, Virtualization, Cloud, and Enterprise Flash. Prior to founding Storage Switzerland, he was CTO at one of the nation's largest storage integrators where he was in charge of technology testing, integration, and product selection.

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One comment on “Webinar: Which Storage Architecture is Best for Splunk Analytics?
  1. […] storage, applications, servers, networks, sensors and security systems. By 2020, IDC projects that more than 40 percent of all data will be machine generated. It’s a giant snowball rolling downhill, and your company’s IT department is standing […]

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