ELK Stack for Go Developers: A Complete Guide

Unlock the Power of Search in Your Go Application with Elasticsearch

When it comes to storing and retrieving data, traditional SQL and NoSQL databases have their limitations. That’s where Elasticsearch comes in – a distributed search and analytics engine that indexes data for fast search and analysis. In this tutorial, we’ll explore how to combine the powers of Elasticsearch and Golang to build a basic content management system with search capabilities.

Getting Started

To follow along, you’ll need:

• Go (version >= 1.14) installed on your machine
• Docker and docker-compose installed
• Familiarity with Docker and the Go programming language

Create a new directory for your project and initialize a new Go module. Install the required dependencies, including the PostgreSQL driver, Elasticsearch client, HTTP framework, and logger.

Project Structure

Organize your project directory with the following structure:

• cmd: Application binaries
• db: Database package and migration files
• .env: Environment variables
• handler: API route handlers
• logstash: Logstash pipeline configurations and Dockerfile
• models: Golang structs for JSON objects

Database Setup

Create a .env file with your environment variables, including database credentials. Set up the Post struct and database connection in db/database.go. Implement database operations for the posts and post_logs tables in db/posts.go.

Database Migrations

Use golang-migrate to manage database migrations. Create migration files for the posts and post_logs tables. Apply the migrations to create the tables.

Elasticsearch and PostgreSQL as Docker Containers

Create a docker-compose.yml file to declare the services needed for your application, including PostgreSQL, API, and Elasticsearch. Set up the Dockerfile to build your application.

Route Handlers with Gin

Create route handlers for creating, reading, updating, and deleting posts, as well as searching posts using Elasticsearch. Implement the CreatePost and SearchPosts functions.

Sync Database to Elasticsearch with Logstash

Configure Logstash to use the PostgreSQL database as its input and Elasticsearch as output. Set up the Logstash pipeline to sync the database with Elasticsearch.

Building the API Binary

Create the main.go file in cmd/api to set up the logger, database connection, and Elasticsearch connection. Initialize the route handler and start the API server.

Testing the Search Application

Rebuild and start the docker-compose services. Create some posts using your favorite API testing tool. Test the search endpoint to see the results.

Visualize Elasticsearch with Kibana

Add the Kibana service to your docker-compose file. Access the Kibana dashboard to visualize and explore your Elasticsearch data.

With this tutorial, you’ve successfully added search capabilities to your Go application using the ELK stack. Explore the complete source code on GitLab and get started with LogRocket’s modern error tracking today!