1. Introduction to Elasticsearch and the ELK stack
About this article:
In this article, we are discussing Elasticsearch. We would be starting with the introduction of Elasticsearch, will be having a brief discussion over so-called ELK stack. We would then move to the architecture of Elasticsearch and what the heck are nodes, clusters, shards, indexes, documents, replication and so on. So let's start.

Table of contents:

• 1. Introduction to Elasticsearch
• 2. Understanding Elastic Stack
  • Elasticsearch (We have already covered it under section 1!)
  • Kibana
  • Logstash
  • Beats
• 3. The Architecture of Elasticsearch
  • Nodes and Clusters
  • Indices and Documents
  • Sharding
  • Replication
    • Keeping Replicas Synchronized
• 4. How Search Query Executed(Quick Overview)
• 5. End Notes
• 6. Recommended Articles

Link to the article: Introduction to Elasticsearch and the ELK stack

2. Upgrading the Existing Architecture to Elasticsearch | ELK Stack
About this article:
Suppose that we have an e-commerce application running on a web server. The data is stored within a database, such as the product categories and the products themselves. So when a product page is requested, the web application looks up the product within the database, renders the page, and sends it back to the visitor’s browser. This is how a common Client-Server-Database Architecture looks like.

Table of contents:

• Existing Architecture
• Step Wise approach for Upgrading to Elasticsearch/ELK Stack
  • [Step 1] - Adding Elasticsearch
  • [Step 2] - Adding Kibana
  • [Step 3] - Adding Metricbeat and Filebeat
  • [Step 4] - Adding Logstash
  • Conclusion
• Recommended Articles

Link to the article: Upgrading the Existing Architecture to Elasticsearch | ELK Stack

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