Configuring Logstash with Elasticsearch

Introduction

Logstash is an open source data collection engine with real-time pipelining capabilities. Logstash can dynamically unify data from disparate sources and normalize the data into destinations of your choice. Cleanse and democratize all your data for diverse advanced downstream analytics and visualization use cases. You can clean and transform your data during ingestion to gain near real-time insights immediately at index or output time. Logstash comes out-of-box with many aggregations and mutations along with pattern matching, geo mapping, and dynamic lookup capabilities.

Integrating Hadoop and Elasticsearch

Introduction

Hadoop shines as a batch processing system, but serving real-time results can be challenging. For truly interactive data discovery, ES-Hadoop (The Elasticsearch-Hadoop connector) lets you index Hadoop data into the Elastic Stack to take full advantage of the speedy Elasticsearch engine and beautiful Kibana visualizations.

Working with Elasticsearch

Introduction

Elasticsearch is a  distributed, scalable, real-time search and analytics engine built on top of Apache Lucene™,. Lucene ( a library) is arguably the most advanced, high-performance, and fully featured search engine library in existence today—both open source and proprietary. It enables you to search, analyze, and explore your data whether you need full-text search, real-time analytics of structured data, or a combination of the two. 

Configure Rsyslog with Any Log File

Modern linux distros ship with Rsyslog which has some nice additional functionality (imfile module) that provides the ability to convert any standard text file into a Syslog message.