Aggregate Logs with Elasticsearch, Kibana, Logstash & Docker

In this article you'll find out how Aggregate Logs with Elasticsearch, Kibana, Logstash & Docker. ELK stack comprises of Elasticsearch,Logstash, and Kibana tools. Elasticsearch is a highly scalable open-source full-text search and analytics engine.

“Is that it?”

“No. That’s a wall.”

“It could be disguised.”

“You’re not very good at looking for things, are you?”

“I’m good at looking for walls. Look, I found another one.”

_― Derek Landy, _**Kingdom of the Wicked**

When a system was monolithic we had access to the full execution stack trace. However, in Microservices architecture, any single operation in any service can trigger a chain of downstream microservice calls, as all are isolated among themselves which leads to a challenging task to debug an actual flow.

And let’s be honest, we all hate those “

something went wrong” or “unknown” system errors.

Well, this situation can be smoothly handled if we externalize and centralize the storage of our logs. Which I believe will increase our chances of tracking down and fixing issues.

Complete project can be found here :

https://github.com/vrushofficial/Utter-Microservices-Territory

Checklist

E-L-K Stack

• ElasticSearch
• Kibana
• Beats
• LogStash

Logs as Streams of events

• Logging with LogBack & SLF4J
• Enhancing log in with tracing and JSONformat

Example

• Playing with Docker images
• Spinning docker containers
• Investigation of logs on Kibana server

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