Elastic

We at rdslab work to offer the best service, we believe that Elasticsearch can help companies with the need to analyze big data, this is why we have a team that deals with Elasticsearch technology so as to be always ready to use the latest technologies to help with your needs.

Elasticsearch

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. It is developed alongside a data collection and log-parsing engine called Logstash, and an
analytics and visualisation platform called Kibana. The three products are designed for use as an integrated solution, referred to as the “Elastic Stack”.

ELK Stack

The ELK Stack is a collection of three open-source products — Elasticsearch,Logstash, and Kibana — all developed, managed and maintained by Elastic. Elasticsearch is a NoSQL database that is based on the Lucene search engine. Logstash is a log pipeline tool that accepts inputs from various sources, executes different transformations, and exports the data to various targets. Kibana is a visualization layer that works on top of Elasticsearch.

The stack also includes a family of log shippers called Beats, which led Elastic to rename ELK as the Elastic Stack.

Together, these different open source products are most commonly used for centralized logging in IT environments (though there are many more use cases for the ELK Stack including business intelligence, security and compliance, and web analytics). Logstash collects and parses logs, and then Elasticsearch indexes and stores the information. Kibana then presents the data in visualizations that provide actionable insights into one’s environment. The elements of the stack are further explained below

Beats are given light shippers that collect and transport various types of data to elasticsearch. The beats have been modularized and are already prepared to collect data from different types of sources, to name a few exist: filebeat (read log files), winlogbeat (read WS events), packetbeat (read data on network traffic ), metricbeat (system and application metrics law) and many others.
Logstash is the module of the Elastic Stack suite that has the function of collecting and processing data and logs from any source allowing the normalization and variation of schemes and formats. Compared to Beats it performs more advanced functions on the data, allowing todo actions such as parsing, enrichment and others/
Kibana is the data visualization tool of the Elastic Stack suite that allows a native interaction withall data and the simplified creation of dashboards, graphs and tables, histograms and thermal maps based on geo-location. Kibana produces visualization layouts that allow you to capture the entire data value at a glance, facilitating overall vision and monitoring.Some advatage in the use of elasticsearch are: SPEED When you get answers instantly, your relationship with your data changes. You can afford to iterate and cover more ground. And since everything is indexed, you’re never left with index envy. You can leverage and access all of your data at ludicrously awesome speeds. SCALABILITY Run It on Your Laptop or Hundreds of Servers with Petabytes of Data. Go from prototype to production seamlessly; you talk to Elasticsearch running on a single node the same way you would in a 300-node cluster. It scales horizontally to handle kajillions of events per second, while automatically managing how indices and queries are distributed across the cluster for oh-so smooth operations. RESILIENCY Hardware rebels. Networks partition. Elasticsearch detects failures to keep your cluster (and your data) safe and available. With cross-cluster replication, a secondary cluster can spring into action as a hot backup. Elasticsearch operates in a distributed environment designed from the ground up for perpetual peace of mind. FLEXIBILITY Numbers, text, geo, structured, unstructured. All data types are welcome. Application search, security analytics, metrics, and logging only scratch the surface of how companies around the world are relying on Elasticsearch to solve a variety of challenges. Interact with Elasticsearch in the Programming Language You Choose Elasticsearch uses standard RESTful APIs and JSON. We also build and maintain clients in many languages such as Java, Python, .NET, SQL, and PHP.