Tech Trek: A Software Engineer's Guide to Code and Beyond

In my previous blog , we have done ELK installation on windows 10 and we have even tried to push messages from input console to Elastic Search and finally viewed on Kibana Server. I will write a separate blog on why do we need ELK? In this blog, I’ll show you how can we push spring boot application log directly to Elastic search using Logstash which we can analyze on Kibana and If you don’t know how to install ELK on windows 10 then you can refer my previous blog and start Elastic Search and Kibana server. Prerequisite Elastic Search and Kibana running on your machine Basic knowledge of Spring boot application If you don’t want to start your application from scratch then you can download one spring boot application from my GitHub repository as well. I am assuming that the Elastic Search and Kibana server are running on your machine and you have a fair idea of how to start the Logstash server and what is Logstash conf file. So, to push spring boot logs cont...

In this blog, I’ll show you how can we install ELK on our windows 10 machine - that is ElasticSearch, Logstash, and Kibana. These three different products are most commonly used together for log analysis. Using ELK stack, we can achieve centralized logging which helps in identifying the problems.  ELK is heavily used in microservices architecture where your docker images are running on 1000's of POD and you can't go to each pod to trace the logs. Logstash: It is the data collection pipeline tool. It is the first component of ELK Stack which collects data inputs and feeds it to the Elasticsearch. It collects various types of data from different sources, all at once and makes it available immediately for further use. Elasticsearch: It is a NoSQL database which is based on Lucene search engine and is built with RESTful APIs. It is a highly flexible and distributed search and analytics engine. Also, it provides simple deployment, maximum reliability, and easy managemen...