![]() ![]() All the aggregated logs will be visible in Kibana. We will have the Syslog driver to push the logs generated from different microservices to Logstash, which will filter the logs and push them to Elasticsearch. In the above design, different microservices will be spitting out logs. In this tutorial, we will use the Docker image of ELK and set it up in EC2. Kibana can also be installed in on-premise infrastructure. Elasticsearch and Kibana can be deployed as a cloud service and hosted on AWS or GCP. Kibana is a software to visualize the Elasticsearch data. Logstash can take logs from various sources using different input plugins and send the output in a desired manner. Logstash is the log aggregator, which has a pipeline to take the input, filter the data, and send the output. Elasticsearch can be installed on-premise or can be used as a SaaS application. It is an open-source software owned by Elastic.Įlasticsearch is an Apache Lucene-based search engine which searches, stores, and analyzes huge volumes of data in almost real time. ![]() What Is ELK?ĮLK is an acronym for Elasticsearch, Logstash, and Kibana. In this tutorial, I will cover what ELK is and how to aggregate the logs from different microservices and push them to one common location. When multiple applications spit out different logs in different systems, it is important to collate them in one place for the IT team to manage. One of the important phases in IT is the post-production phase, and one of the major challenges is to identify issues in post-production. ![]()
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