redhat.com facebook.com/redhatinc @redhatnews linkedin.com/company/red-hat INTRODUCTION Savvy enterprises are investing in operational analytics to help manage increasing business and technological complexity. In doing so, they are able to drive greater efficiency, enhanced customer satisfaction, increased transparency, and superior resilience. Deploying and managing operational analytics at scale is not without challenges, however, particularly with regards to data storage. In order to deliver the insights that operational analytics users demand, large amounts of information must be collected and stored. As a result, IT organizations commonly find that storage for enterprise-scale operational analytics is either too difficult to manage, or too expensive, or both. To help businesses easily and cost-effectively realize the benefits of operational analytics, Red Hat has integrated Splunk ® Enterprise, an industry-leading platform for delivering real-time operational intelligence, with Red Hat ® Gluster Storage, a software-defined storage platform for files, objects, and machine-to-machine data. Using these products together helps enterprise solve the cost and scale problems of explosive analytic data growth. The use of Red Hat software-defined storage with Splunk creates an important new opportu- nity for enterprises deploying Splunk Enterprise: as opposed to using inexpensive but difficult to manage direct-attached storage (DAS), or expensive and high-latency network-attached storage (NAS), Red Hat is pioneering a hybrid storage model that allows Splunk Enterprise to use a combination of DAS and software-defined storage to achieve a high-performance, highly manageable, and cost-effective system for operational analytics. WHITEPAPER CHOOSING THE RIGHT STORAGE PLATFORM FOR SPLUNK ENTERPRISE
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redhat.com
facebook.com/redhatinc @redhatnews
linkedin.com/company/red-hat
INTRODUCTION
Savvy enterprises are investing in operational analytics to help manage increasing business
and technological complexity. In doing so, they are able to drive greater efficiency, enhanced
customer satisfaction, increased transparency, and superior resilience.
Deploying and managing operational analytics at scale is not without challenges, however,
particularly with regards to data storage. In order to deliver the insights that operational
analytics users demand, large amounts of information must be collected and stored. As a
result, IT organizations commonly find that storage for enterprise-scale operational analytics
is either too difficult to manage, or too expensive, or both.
To help businesses easily and cost-effectively realize the benefits of operational analytics,
Red Hat has integrated Splunk® Enterprise, an industry-leading platform for delivering
real-time operational intelligence, with Red Hat® Gluster Storage, a software-defined storage
platform for files, objects, and machine-to-machine data. Using these products together
helps enterprise solve the cost and scale problems of explosive analytic data growth.
The use of Red Hat software-defined storage with Splunk creates an important new opportu-
nity for enterprises deploying Splunk Enterprise: as opposed to using inexpensive but difficult
to manage direct-attached storage (DAS), or expensive and high-latency network-attached
storage (NAS), Red Hat is pioneering a hybrid storage model that allows Splunk Enterprise to
use a combination of DAS and software-defined storage to achieve a high-performance, highly
manageable, and cost-effective system for operational analytics.
WHITEPAPER
CHOOSING THE RIGHT STORAGE PLATFORM FOR SPLUNK ENTERPRISE
2redhat.com WHITEPAPER Choosing the right storage platform for Splunk Enterprise
DATA REQUIREMENTS FOR OPERATIONAL ANALYTICS
To more rapidly identify trends, patterns, and behaviors in operational data, or to facilitate regula-
tory compliance, enterprises retain the data indexed by Splunk Enterprise for extended periods of
time. This is because Splunk’s data-hungry analytical algorithms produce more insightful results
when fed more data, both in terms of the number of unique data sources as well as the number of
retained data points from each source.
According to Splunk documentation, daily indexing volumes for medium and large enterprises
are typically:
• 100–300GB per day for a medium enterprise with tens to low hundreds of users.
• 300GB–1TB per day for a large enterprise with up to five hundred or more users.
Figure 2 illustrates the aggregate amount of storage required as the ingest rate and data retention
period vary. As can be seen in the figure, a large enterprise ingesting a moderate 500GB of data
per day will accumulate approximately 1PB of data if that data is to be retained for four years, while
an enterprise indexing 1TB of data per day will require the same 1PB of data retaining that data for
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