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Monitoring and Logging

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Unraveling Software Maintenance and Evolution
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Abstract

In production, we must have visibility of what is going on within our system. Part of the DevOps culture is to share the burden of providing such supervising capability by both development and operations teams. In parallel to shipping metrics and log messages to a central location, we must also have facilities to trigger alarms if something goes awry. This chapter primarily illustrates how to properly collect/send metrics in an application and how to structure/send logs toward the appropriate infrastructure node. The aim is to showcase techniques of squeezing out the maximum insight with minimal effort (expressed in data collection, transmission, and processing time as well as cost).

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References

Further Reading

  1. Turnbull J (2016) The art of monitoring. www.artofmonitoring.com. Accessed 20 Sep 2017. This book gives you an overview about monitoring and logging, and introduces you to Riemann, Graphite, and the ELK stack. It covers both topics: collecting data on clients as well as processing them on the central location

Regular Bibliographic References

  1. Leskovec J, Rajaraman A, Ullman DJ (2014) Mining of massive datasets, 2nd edn. Cambridge University Press, Cambridge

    Book  Google Scholar 

  2. Neil NG (2016) Time is an illusion: lunchtime doubly so. queue.acm.org/detail.cfm?id=2878574. Accessed 22 Sep 2017

  3. Ratzel R, Greenstreet R (2012) Toward higher precision. Commun ACM 55(10):38–47

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  4. Brewer B, Zeman M, Souders S (2015) Creating meaningful metrics that get your users to do the things you want. O’Reilly, Sebastopol, CA

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  5. Tseitlin A (2013) The Antifragile organization. Commun ACM 56(8):40–44

    Article  Google Scholar 

  6. Kreps J (2014) I ♥ logs. O’Reilly Media, Sebastopol, CA

    Google Scholar 

  7. Pacheco D (2011) Postmortem debugging in dynamic environments. Commun ACM 54(12):44–51

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Varga, E. (2017). Monitoring and Logging. In: Unraveling Software Maintenance and Evolution. Springer, Cham. https://doi.org/10.1007/978-3-319-71303-8_9

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  • DOI: https://doi.org/10.1007/978-3-319-71303-8_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-71302-1

  • Online ISBN: 978-3-319-71303-8

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