Figure 1. Kibana Dashboard
ElasticSearch is a distributed, restful analytics search engine which is used to provide faster search through your data than the traditional databases including RDBMS and NoSQL databases. It works by regularly creating data indices from the data stored in traditional databases and use Lucene library to search through the data.
Kibana is the visualization client used to explore, visualize and discover the data.
In this post, you would learn about some of the following:
{
"name" : "lp9UsQx",
"cluster_name" : "elasticsearch",
"cluster_uuid" : "vrpmq49cQTq4E2fJ9rEEmA",
"version" : {
"number" : "6.2.2",
"build_hash" : "10b1edd",
"build_date" : "2018-02-16T19:01:30.685723Z",
"build_snapshot" : false,
"lucene_version" : "7.2.1",
"minimum_wire_compatibility_version" : "5.6.0",
"minimum_index_compatibility_version" : "5.0.0"
},
"tagline" : "You Know, for Search"
}
Figure 1. Kibana Dashboard
In this post, you learned about installing Elasticsearch and Kibana on Windows and getting started by loading the data.
Did you find this article useful? Do you have any questions or suggestions about this article in relation to setting up ElasticSearch and Kibana on Windows? Leave a comment and ask your questions and I shall do my best to address your queries.
If you've built a "Naive" RAG pipeline, you've probably hit a wall. You've indexed your…
If you're starting with large language models, you must have heard of RAG (Retrieval-Augmented Generation).…
If you've spent any time with Python, you've likely heard the term "Pythonic." It refers…
Large language models (LLMs) have fundamentally transformed our digital landscape, powering everything from chatbots and…
As Large Language Models (LLMs) evolve into autonomous agents, understanding agentic workflow design patterns has…
In today's data-driven business landscape, organizations are constantly seeking ways to harness the power of…