Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Solving Big Data Challenges for Enterprise Application Performance
  Management   As the complexity of enterprise systems increases, the need for monitoring
and analyzing such systems also grows. A number of companies have built
sophisticated monitoring tools that go far beyond simple resource utilization
reports. For example, based on instrumentation and specialized APIs, it is now
possible to monitor single method invocations and trace individual transactions
across geographically distributed systems. This high-level of detail enables
more precise forms of analysis and prediction but comes at the price of high
data rates (i.e., big data). To maximize the benefit of data monitoring, the
data has to be stored for an extended period of time for ulterior analysis.
This new wave of big data analytics imposes new challenges especially for the
application performance monitoring systems. The monitoring data has to be
stored in a system that can sustain the high data rates and at the same time
enable an up-to-date view of the underlying infrastructure. With the advent of
modern key-value stores, a variety of data storage systems have emerged that
are built with a focus on scalability and high data rates as predominant in
this monitoring use case. In this work, we present our experience and a
comprehensive performance evaluation of six modern (open-source) data stores in
the context of application performance monitoring as part of CA Technologies
initiative. We evaluated these systems with data and workloads that can be
found in application performance monitoring, as well as, on-line advertisement,
power monitoring, and many other use cases. We present our insights not only as
performance results but also as lessons learned and our experience relating to
the setup and configuration complexity of these data stores in an industry
setting.

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The categories of this paper are: math-ph
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The categories of this paper are: cmp-lg
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The categories of this paper are: dg-ga
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The categories of this paper are: stat
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The categories of this paper are: q-alg
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The categories of this paper are: nucl-ex
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The categories of this paper are: q-fin
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The categories of this paper are: nlin
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The categories of this paper are: eess
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The categories of this paper are: econ
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The categories of this paper are: q-bio
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The categories of this paper are: acc-phys
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The categories of this paper are: plasm-ph
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The categories of this paper are: funct-an
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The categories of this paper are: chem-ph
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The categories of this paper are: adap-org