Daily Resource For Devs

Introduction In order to be able to search our logs based on a key/value pattern, we need to prepare our application to log and send information in a structured way to our log aggregation tool. In this article I am going to show you how to send structured log to ElasticSearch using Logstash as a data pipeline tool and how to visualize and filter log information using Kibana. According to a definition from the Wikipedia website: Elasticsearch is a search engine based on the Lucene library. It provides a distributed, multitenant-capable full-text search engine with an HTTP web interface and schema-free JSON documents. According to Elasticsearch platform website , Elasticsearch is the heart of the Elastic stack, which centrally stores your data for lightning fast search. The use of Elasticsearch, Kibana, Beats and Logstash as a search platform is commonly known as the ELK stack. Next we are going to start up Elasticsearch, Kibana and Logstash using docker so we can better underst...

Introduction As a software engineer, we are quite used to deal with logs in our daily lives, but in addition to ensuring that the necessary logs are being sent by the application itself or through a service mesh, we often have to go a little further and interact with some log tool to extract more meaningful data. This post is inspired by a problem I had to solve for a client who uses Splunk as their main data analysis tool and this is the first in a series of articles where we will delve deeper and learn how to use different Splunk commands. Running Splunk with Docker To run Splunk with docker, just run the following command: docker run -d —rm -p 8000:8000 -e SPLUNK_START_ARGS=--accept-license -e SPLUNK_PASSWORD=SOME_PASSWORD --name splunk splunk/splunk:latest Sample Data We are going to use the sample data provided by Splunk. You can find more information and download the zip file from their web site . How does it work? In order to be able to interact with Splunk t...