Centralized Logging with ELK Stack
Set up and use Elasticsearch, Logstash, and Kibana for centralized logging and log analysis.
Centralized Logging with ELK Stack is a free Spring Boot 4 Microservices & REST APIs lesson on CoddyKit — lesson 1 of 3. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the Spring Boot 4 Microservices & REST APIs learning path, one of 3 lessons in the course, and your progress syncs across the web and the CoddyKit app.
Why Centralized Logging?
In a microservices world, applications don't run as one big piece. Instead, they're many small, independent services.
This means logs are scattered across many servers and containers. Finding issues becomes a huge challenge without a central place to view them all.
- Debugging: Hard to trace requests across services.
- Monitoring: Difficult to spot trends or errors.
- Maintenance: Manually checking logs is time-consuming.
Meet the ELK Stack
The ELK Stack is a popular solution for centralized logging. It's a powerful collection of three open-source tools:
- Elasticsearch: Stores and indexes logs.
- Logstash: Processes and transforms logs.
- Kibana: Visualizes and analyzes logs.
Together, they create a robust pipeline for all your application logs.
Elasticsearch: Data Storage
Elasticsearch is a highly scalable search engine. It's built for speed and can handle vast amounts of data, like all your application logs.
- Indexing: Organizes logs for fast searching.
- Scalability: Easily handles growing log volumes.
- Powerful Search: Allows complex queries to find specific events or patterns.
Think of it as the super-efficient database for your logs.
Logstash: Data Pipeline
Logstash is the data processing engine of the ELK stack. It collects logs from various sources, transforms them, and then sends them to Elasticsearch.
It works like a funnel with three main stages:
- Inputs: Where logs are collected from (e.g., files, network, message queues).
- Filters: Where logs are parsed, enriched, or modified (e.g., extract data, remove sensitive info).
- Outputs: Where processed logs are sent (e.g., Elasticsearch).
Kibana: Visualization & Analysis
Kibana is the user interface that sits on top of Elasticsearch. It lets you explore, visualize, and build dashboards from your log data.
With Kibana, you can:
- Search and filter logs in real-time.
- Create interactive charts and graphs.
- Build custom dashboards to monitor application health.
- Identify trends and troubleshoot issues quickly.
Spring Boot Logging Basics
Spring Boot applications use SLF4J as a logging facade and Logback as the default implementation.
By default, Spring Boot logs to the console. These logs include timestamps, log levels (INFO, DEBUG, WARN, ERROR), thread names, and the actual log message.
This console output is a common source for Logstash or other agents to pick up.
Simple Spring Boot Logger
Here's a minimal Spring Boot application that demonstrates basic logging at different levels. Run it and observe the console output.
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
@SpringBootApplication
public class LoggingApp {
private static final Logger logger = LoggerFactory.getLogger(LoggingApp.class);
public static void main(String[] args) {
SpringApplication.run(LoggingApp.class, args);
logger.info("Spring Boot LoggingApp started!");
logger.debug("This is a debug message.");
logger.warn("A warning in the app.");
logger.error("An error occurred!");
}
}Getting Logs to ELK
How do logs from your Spring Boot app reach the ELK stack?
A common approach is to use Filebeat. Filebeat is a lightweight shipper that runs on your application servers. It monitors log files or console output and forwards them to Logstash or Elasticsearch.
This makes sure logs are collected reliably without burdening your application.
The ELK Stack Workflow
Let's summarize the typical flow for centralized logging with ELK:
- Your Spring Boot Application generates logs (e.g., to console or a file).
- Filebeat collects these logs from the source.
- Logstash receives logs from Filebeat, processes them (parses, filters).
- Logstash sends processed logs to Elasticsearch for storage and indexing.
- Kibana queries Elasticsearch to visualize and analyze the log data.
ELK Component Roles
Each component in the ELK stack has a distinct and crucial role. Understanding these roles is key to effective logging.
Lesson Summary
We've explored the importance of centralized logging for microservices and introduced the ELK (Elasticsearch, Logstash, Kibana) stack.
- Elasticsearch: Stores and indexes logs for fast searching.
- Logstash: Processes and transforms logs from various sources.
- Kibana: Provides powerful visualization and analysis tools.
- Filebeat: A common agent for collecting logs from applications.
This powerful combination ensures you can effectively monitor and troubleshoot your distributed applications.
Frequently asked questions
Is the “Centralized Logging with ELK Stack” lesson free?
Yes — the full text of “Centralized Logging with ELK Stack” is free to read here on the web, and the Spring Boot 4 Microservices & REST APIs course includes 3 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the Spring Boot 4 Microservices & REST APIs course, upgrade to CoddyKit PRO.
What will I learn in “Centralized Logging with ELK Stack”?
Set up and use Elasticsearch, Logstash, and Kibana for centralized logging and log analysis. You practise Spring Boot 4 Microservices & REST APIs with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start Spring Boot 4 Microservices & REST APIs?
No prior experience is required. Spring Boot 4 Microservices & REST APIs on CoddyKit is structured for beginners through advanced learners; this is — lesson 1 of 3, so you can start here or from the beginning and move at your own pace.
How long does the “Centralized Logging with ELK Stack” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this Spring Boot 4 Microservices & REST APIs lesson?
Yes. Every Spring Boot 4 Microservices & REST APIs lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.
All lessons in this course
- Centralized Logging with ELK Stack
- Health Checks and Metrics
- Alerting and Dashboarding