preface.tex

\renewcommand{\abstractname}{Preface}
\begin{abstract}

  Nowadays one can speak of an ongoing revolution in web systems which turns
  previous demands upside down. Internet companies created a need for activity
  data in an extremely high volume which has never existed before. And
  the trend holds on -- not only companies with its core business in the cloud
  also more and more companies with a traditionally
  fashioned core business are tending to create huge amount of data. This will
  sooner or later surpass the yet so overwhelming data volume of the internet
  big five (Apple, Microsoft, Google, Amazon, Facebook). The data those
  companies generate capture user and server activity. It is at the heart
  of many internet systems in the domains of advertising, relevance, search,
  recommendation systems, and security, as well as continuing to fulfil its
  traditional role in analytics and reporting. Processing of the so called
  activity data has changed too. The days are gone of nightly batch processing
  as the only way to produce valuable information -- real-time processing
  dominates the field now, where information is available as soon as data is
  generated. Being able to serve data to batch- and real-time processing systems
  requires a central hub that can handle data-load as well as latency. There are
  many alternative products on the market which are able to provide the
  necessary capabilities up to a certain point, but among some others (big five)
  LinkedIn found himself in the unsatisfied position where any existing system
  was able to process their data load and was scalable at the same time.  Thus,
  they created Kafka, which was soon open sourced under the Apache license,
  known as Apache Kafka.

\end{abstract}