Elasticsearch
A complete 25-lesson Elasticsearch course from installation and the core data model through mapping, the Query DSL, aggregations, performance tuning, security, and the Node.js client, culminating in hands-on search backend, autocomplete, and analytics dashboard projects.
25 Lessons · 750 min · Learning Platform Editorial Team
Getting Started — Elasticsearch Course Roadmap
What you need on the desk
- Docker Desktop or a native Elasticsearch installation
- curl or a REST client (Postman, Insomnia)
- Kibana (via Docker) for the Dev Tools console lessons
- Node.js 20+ for the client and project lessons
- No external Elastic Cloud account is required — self-hosted via Docker is enough
Know this much before you start
- Basic JSON familiarity
- Comfort using a terminal and curl (or a REST client)
- No prior Elasticsearch experience is required
- The PostgreSQL course is helpful for context but not required — this course explains what it needs as it goes
By the end, you can
- Design Elasticsearch mappings with the right field types (text, keyword, date, numeric) for search and aggregations
- Write Query DSL queries — match, term, bool, filters — and understand relevance scoring and highlighting
- Build metric and bucket aggregations to turn search results into analytics
- Tune performance and design mappings that avoid mapping explosion and slow queries
- Secure a cluster with API keys, role-based access control, and TLS
- Use the official Node.js/TypeScript client and reindexing to build and evolve a production-ready search backend