Summary

In this chapter, we learned about the importance of collecting log records from microservices in a system landscape into a common centralized database where analysis and searches of the stored log records can be performed. We used the EFK stack, Elasticsearch, Fluentd, and Kibana, to collect, process, store, analyze, and search for log records.

Fluentd was used to collect log records not only from our microservices but also from the various supporting containers in the Kubernetes cluster. Elasticsearch was used as a text search engine. Together with Kibana, we saw how easy it is to get an understanding of what types of log records we have collected.

We also learned how to use Kibana to perform important tasks such as finding related log records from cooperating microservices and how to perform root cause analysis, finding the real problem for an error message.

Being able to collect and analyze log records in this way is an important capability in a production environment...