Visualizing Spring Boot Microservices Logs in Kibana

Logs provide vital insights into the performance and behavior of Spring Boot microservices, helping developers debug issues, track transactions, and monitor errors. But raw logs can quickly become overwhelming without a proper visualization tool. Enter Kibana, a powerful frontend visualization platform in the ELK stack that allows you to explore logs effectively, spot trends, and gain actionable insights.

This guide will walk you through the process of visualizing Spring Boot logs in Kibana. From setting up index patterns to creating dashboards for error tracking, you’ll learn how to make the most of Kibana’s rich features.

Table of Contents

1. Why Use Kibana for Log Visualization?
2. Creating Index Patterns in Kibana
3. Searching Logs by Service Name, traceId, and Error Level
4. Creating Dashboards for Error Rates and Warnings
5. Using Discover and Dashboard Views Effectively
6. Official Documentation Links
7. Summary

Why Use Kibana for Log Visualization?

Kibana transforms raw log data into meaningful metrics and visualizations. When logs from Spring Boot microservices are indexed in Elasticsearch, Kibana provides a seamless way to analyze that data. Key advantages include:

1. Centralized Log Analysis: Consolidate logs across services to troubleshoot distributed applications.
2. Custom Queries: Filter and search logs for specific attributes, such as traceId, error level, or timestamps.
3. Interactive Dashboards: Build real-time dashboards to monitor error rates, system performance, and warnings.
4. Drill-Downs with Search: Use the Discover view to identify the root cause of issues by drilling into log data.

Now, let’s get hands-on by configuring Kibana to visualize Spring Boot microservices logs effectively.

Creating Index Patterns in Kibana

Index patterns in Kibana are the starting point for exploring your log data. They act as a bridge between Kibana and the data stored in Elasticsearch.

Step 1. Ensure Logs Are Indexed in Elasticsearch

Before setting up an index pattern, ensure your logs are reaching Elasticsearch. Use a naming convention such as spring-logs-* for logging indices. You can check Elasticsearch for active indices using:

GET _cat/indices?v

Step 2. Access Kibana and Open Index Management

1. Navigate to Kibana.
2. Go to Management > Data Views (Index Patterns).

Step 3. Create a New Index Pattern

1. Click Create Data View.
2. Enter your index pattern name, e.g., spring-logs-*.
3. Use @timestamp as the time field to enable time-based searches.
4. Save the index pattern.

Kibana will now use this pattern to access your Spring Boot logs.

Benefits of Using Index Patterns:

• Enables filters and visualizations based on date and time fields.
• Provides a structured way to query logs across services sharing a naming convention.

We’re now set to start searching logs.

Searching Logs by Service Name, traceId, and Error Level

Kibana’s Discover view is a powerful search interface where you can filter, group, and explore logs. For Spring Boot microservices, you often need to locate logs by service context, trace IDs for transaction monitoring, or error severity.

Step 1. Open the Discover View

1. From the Kibana home, select Discover.
2. Choose your index pattern (spring-logs-*) from the dropdown menu.

Step 2. Search by Service Name

Assuming your logs contain a service_name field:

• Use the search bar to filter logs by a specific microservice: service_name:"order-service"
• Refine the time range using the time picker in the top-right corner.

Step 3. Search by traceId for Transaction Debugging

traceId fields help trace transactions across microservices:

• Query logs with a specific traceId: traceId:"12345-abcde"
• Use this to see all logs associated with a single transaction.

Step 4. Filter by Error Level

To view error logs, use the level field:

• Filter for errors only: level:"ERROR"
• Combine queries for granular results, e.g.: service_name:"payment-service" AND level:"ERROR"

Step 5. Save Your Searches

Save frequently used searches for quick access:

1. Perform your search.
2. Click Save Query on the top-right and name it appropriately.

By mastering search queries, you can quickly pinpoint problem areas in your Spring Boot logs.

Creating Dashboards for Error Rates and Warnings

Dashboards in Kibana are a visual way to monitor log metrics like error rates, warning trends, and service performance.

Step 1. Create a New Dashboard

1. Navigate to Dashboard > Create Dashboard.
2. Click Add from library or start adding visualizations from scratch.

Step 2. Visualize Error Rates

1. Create a new visualization:
   • Go to Visualize > Create Visualization and choose Metric.
   • Use the metric to count logs where level is ERROR: level:"ERROR"
   • Save the visualization as Error Count.
2. Add the saved visualization to your dashboard.

Step 3. Plot Warnings Over Time

1. Create a line chart to track warnings:
   • Select Visualize > Line Chart.
   • X-Axis: Use @timestamp to group logs by time.
   • Y-Axis: Count logs where level is WARN.
   • Save and add it to the dashboard.

Step 4. Monitor Service-Specific Logs

Create a table showing logs grouped by service_name:

1. Use the Data Table visualization.
2. Split rows by service_name to group logs per service.
3. Add additional fields like traceId or log messages.

Step 5. Save and Share Dashboards

Save dashboards for your team and share them via a link or embed them in your monitoring tools.

Dashboards provide real-time insights, helping teams monitor application health and spot anomalies.

Using Discover and Dashboard Views Effectively

Kibana offers two key views for log analysis:

Discover View

The Discover View is perfect for:

• Debugging issues by manually exploring logs.
• Running complex search queries for root cause analysis.
• Drilling into granular log details like traceId or specific user actions.

Tips:

• Use filters and query syntax to refine log data.
• Export logs as CSV for offline analysis, if needed.

Dashboard View

The Dashboard View is best for:

• Summarizing key metrics like error density or response time trends.
• Monitoring system health in real-time with error/warning charts.
• Providing stakeholders with high-level insights without technical search queries.

Tips:

• Use refresh intervals to keep dashboards up to date.
• Combine metrics, charts, and tables for comprehensive monitoring.

Together, the Discover and Dashboard views make Kibana a highly efficient tool for log visualization and analysis.

Official Documentation Links

Deepen your understanding with official Kibana documentation:

1. Kibana Discover Docs
2. Kibana Dashboards Docs

These resources provide in-depth explanations of features and best practices.

Summary

Visualizing Spring Boot logs in Kibana provides clarity and actionable insights into your microservices’ behavior. From efficient query building to creating dashboards for high-level monitoring, Kibana empowers both developers and operations teams to diagnose issues quickly and effectively.

Key Takeaways:

1. Index Patterns: Create index patterns to enable structured log exploration.
2. Queries: Master search by service name, traceId, or log levels.
3. Dashboards: Build real-time dashboards for error monitoring and performance tracking.
4. Effective Analysis: Use Discover for deep dives and Dashboards for overview reporting.

Start leveraging Kibana today to unlock the full potential of your Spring Boot logs and improve system observability!