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You're reading from  Machine Learning with the Elastic Stack - Second Edition

Product typeBook
Published inMay 2021
Reading LevelBeginner
PublisherPackt
ISBN-139781801070034
Edition2nd Edition
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Authors (3):
Rich Collier
Rich Collier
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Rich Collier

Rich Collier is a solutions architect at Elastic. Joining the Elastic team from the Prelert acquisition, Rich has over 20 years' experience as a solutions architect and pre-sales systems engineer for software, hardware, and service-based solutions. Rich's technical specialties include big data analytics, machine learning, anomaly detection, threat detection, security operations, application performance management, web applications, and contact center technologies. Rich is based in Boston, Massachusetts.
Read more about Rich Collier

Camilla Montonen
Camilla Montonen
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Camilla Montonen

Camilla Montonen is a Senior Machine Learning Engineer at Elastic.
Read more about Camilla Montonen

Bahaaldine Azarmi
Bahaaldine Azarmi
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Bahaaldine Azarmi

Bahaaldine Azarmi, Global VP Customer Engineering at Elastic, guides companies as they leverage data architecture, distributed systems, machine learning, and generative AI. He leads the customer engineering team, focusing on cloud consumption, and is passionate about sharing knowledge to build and inspire a community skilled in AI.
Read more about Bahaaldine Azarmi

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Understanding the importance and limitations of KPIs

Because of the problem of scale and the desire to make some amount of progress in making the collected data actionable, it is natural that some of the first metrics to be tackled for active inspection are those that are the best indicators of performance or operation. The KPIs that an IT organization chooses for measurement, tracking, and flagging can span diverse indicators, including the following:

  • Customer experience: These metrics measure customer experience, such as application response times or error rates.
  • Availability: Metrics such as uptime or Mean Time to Repair (MTTR) are often important to track.
  • Business: Here we may have metrics that directly measure business performance, such as orders per minute or number of active users.

As such, these types of metrics are usually displayed, front and center, on most high-level operational dashboards or on staff reports for employees ranging from technicians...

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Machine Learning with the Elastic Stack - Second Edition
Published in: May 2021Publisher: PacktISBN-13: 9781801070034

Authors (3)

author image
Rich Collier

Rich Collier is a solutions architect at Elastic. Joining the Elastic team from the Prelert acquisition, Rich has over 20 years' experience as a solutions architect and pre-sales systems engineer for software, hardware, and service-based solutions. Rich's technical specialties include big data analytics, machine learning, anomaly detection, threat detection, security operations, application performance management, web applications, and contact center technologies. Rich is based in Boston, Massachusetts.
Read more about Rich Collier

author image
Camilla Montonen

Camilla Montonen is a Senior Machine Learning Engineer at Elastic.
Read more about Camilla Montonen

author image
Bahaaldine Azarmi

Bahaaldine Azarmi, Global VP Customer Engineering at Elastic, guides companies as they leverage data architecture, distributed systems, machine learning, and generative AI. He leads the customer engineering team, focusing on cloud consumption, and is passionate about sharing knowledge to build and inspire a community skilled in AI.
Read more about Bahaaldine Azarmi