Elasticsearch is coupled with the integrated Kibana visualization and reporting tool, this allows users to visualize complex data and present it in an easily understandable manner.
Elasticsearch, Logstash and Kibana coupled with the tools like Beats is referred to as the ELK stack. Integration with Beats and Logstash, enables users to easily transform source data and load it into your Elasticsearch cluster.
The Elastic cluster is easily scalable and can hold large amounts of data scaling even to Petabytes. It is offered in popular languages like PHP, .NET, Python, Java etc and works well with popular web-frameworks like Laravel.
LiteBreeze has been actively using the ELK stack for the last few years. For example: as a product catalog for a webstore client. It enables search and advanced filtering, text analysis and processing, collects and monitors logs and visualizes the application/infrastructure metrics.
Few of our recent use-cases were:
- Storing product catalog and enabling search and advanced filtering on it.
- Store document and files content and metadata, creating advanced filtering, retrieval and aggregations on it.
- Ingest system logs from different sources and visualize in Kibana for identifying issues.
Many large companies use Elasticsearch for storing and searching their documentation. Airbus is one example. They have two billion blocks of technical documents related to their aircraft.
Elasticsearch allows them to give efficient support to all partners involved in manufacturing and servicing their various airplane models. Searches are made through a modern document search platform.
