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Spring microservices monitoring: /metrics endpoint and ELK, Part II: Improvements

 Introduction

 As we saw in the first part of this series, it is essential necessary to monitor the health of our microservices, and  to improve the tool we developed which helps us get metrics and forward them to an Elasticsearch instance. In this chapter we will pursue the question of how can we improve the processing of the result of the metrics endpoint?

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DDD eXchange 2017

Last year I went to several conferences, one about JavaScript and at least two about Java. Unfortunately, the last conference was rather boring since at every Java conference they are talking about the same cool Java 8 and Java 9 stuff, for example project Jig-Saw or Lambda expressions. After listening to several “Java User Group” talks and attending one Java conference there will not be a lot of new content in another three-day conference. In my opinion this is sad and I decided this year to go to more specialised conferences.

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Alfresco Beecon in Zaragoza

What is BeeCon

Started back in 2016, BeeCon is the developer conference of the Alfresco community (the people not the edition). The event is organised by “Order of The Bee” which coordinates the main community contributors and actors. A big presence of Alfresco engineers and specialists acknowledges the seriousness of this endeavour. Last year the convention took place in Brussels, and this year it was located in the wonderful city of Zaragoza.

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QCON London 2017

I found this experience really nice – to be able to get some insights on how people have solved big issues and how they got pwned.  What is more, it was good to see that I am personally going in the right direction (or at least, let’s say, getting on the trends)

These are technologies and trends that got my attention as the most used:

  •  Technologies/languages/tools:
    • Go
    • ELK
    • Luigi/Airflow – Tools for pipelining jobs
    • Redis
    • Hadoop
    • Kafka
    • Java 9
  • Trends:
    • Data Science
      •  Machine learning for prediction and fraud detection
    • Microservices
      • NodeJS

I chose to follow two main paths, with some extra things from here and there: Machine Learning/Data science, Microservices, and let’s call it “miscellaneous”. Below, an overview of the most interesting things:

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