The Complete Elasticsearch and Kibana Tutorial for beginners

Learn the core concepts of Elasticsearch, including near real time indexing, clusters and nodes, indices and types, documents, and how shards and replicas enable scalable, distributed search.

Learn to install Elasticsearch across Windows, Unix, and Mac, check Java version requirements, download the correct binaries, start the server, and access it at 127.0.0.1:9200.

Explore Elasticsearch cluster concepts, learn to check cluster health, list and create indices, understand what an index is, query documents, and delete indices using the RESTful API.

Learn how to run a basic cluster health check in Elasticsearch, read the health status (green, yellow, or red), and interpret replicas, nodes, and index readiness.

List all available indices in elasticsearch by ensuring the service is up, then query _cat/indices with curl and the verbose option to view index details.

Create an index named customer in Elasticsearch on localhost using the command, then verify it appears with five shards and one replica and zero documents.

Delete an index via a command, then verify deletion by listing indices to confirm the targeted index is no longer present.

Create a document in Elasticsearch by posting to the customer index with external type and a unique id. Elasticsearch creates the index automatically and returns readable results with pretty output.

Learn how to retrieve a document using the command curve, display the unique id from localhost /customer, and view real data; the next lecture covers indexing.

Explore how to perform Elasticsearch operations using curl on localhost:9200, including deleting, adding, and targeting specific index, type, and document ids.

Learn to modify documents in the customer index of Elasticsearch by updating data, replacing documents via index, and using export to create documents with a random or specified ID.

Learn how to update documents in Elasticsearch by deleting the old document and indexing a new version with the update API, then retrieve to verify changes.

Learn how to delete documents in Elasticsearch by specifying a document ID with the delete API. Explore deleting a document by ID and observe the result.

Learn how to perform batch operations in Elasticsearch with the bulk api, indexing, updating, and deleting multiple documents efficiently, with sequential actions, per-action status, and continuing after failures.

Import sample data into Elasticsearch using the bulk operation to create documents in the bank index or accounts. Download the resources and prepare for the next lecture on search.

Explore the basics of Elasticsearch query language, a domain-specific language for composing queries, with examples on size, from, and sorting to retrieve and order results.

Learn to run Elasticsearch searches using two basic methods: passing parameters via the rest request and using the request body for a more expressive, readable query.

Learn to customize Elasticsearch searches by filtering with source fields, using simple match queries, and composing boolean queries with must and should to refine results.

Elasticsearch filters and range queries refine search results by using balance value ranges to filter documents, improving relevance scoring and enabling efficient data querying.