Kibana dashboards can be customized for countless use cases across different industries and functions. This guide showcases practical examples of useful dashboards that organizations commonly implement to monitor systems, analyze data, and gain business insights.
Infrastructure Monitoring Dashboards
System Health Dashboard
Purpose: Monitor server and infrastructure health metrics in real-time
Key Visualizations:
- CPU usage by host (line chart)
- Memory utilization (gauge charts)
- Disk I/O rates (area chart)
- Network throughput (line chart)
- System uptime (metric visualization)
- Top processes by resource consumption (data table)
Common Filters:
- Host name
- Data center/region
- Environment (production, staging, development)
Use Case: DevOps teams monitoring infrastructure health to prevent outages and optimize resource allocation.
Docker/Kubernetes Dashboard
Purpose: Monitor containerized applications and orchestration platforms
Key Visualizations:
- Container status by pod (pie chart)
- CPU and memory usage per container (heat map)
- Pod restart count (bar chart)
- Node availability (status indicator)
- Resource requests vs limits (multi-line chart)
- Container logs timeline (timeline visualization)
Common Filters:
- Namespace
- Container name
- Node name
- Cluster
Use Case: Container orchestration teams tracking deployment health and resource utilization.
Application Performance Monitoring (APM) Dashboards
Application Performance Dashboard
Purpose: Track application response times, errors, and throughput
Key Visualizations:
- Average response time by endpoint (bar chart)
- Error rate over time (line chart)
- Transactions per minute (area chart)
- Apdex score (gauge)
- Slowest transactions (data table)
- Error distribution by type (pie chart)
Common Filters:
- Service name
- Environment
- Transaction type
- HTTP status code
Use Case: Development teams monitoring application performance to identify bottlenecks and improve user experience.
User Experience Dashboard
Purpose: Monitor end-user experience metrics
Key Visualizations:
- Page load time distribution (histogram)
- Geographic user distribution (map)
- Browser/device breakdown (pie charts)
- Conversion funnel (funnel visualization)
- Session duration trends (line chart)
- Error rate by page (heat map)
Common Filters:
- Geographic region
- Browser type
- Device type
- User segment
Use Case: Product teams optimizing user experience and identifying problematic user journeys.
Security Analytics Dashboards
Security Operations Center (SOC) Dashboard
Purpose: Monitor security events and threats in real-time
Key Visualizations:
- Failed login attempts by IP (bar chart)
- Security alerts by severity (metric visualization)
- Top threat actors (data table)
- Authentication events timeline (timeline)
- Geographic source of attacks (map)
- Firewall blocked connections (line chart)
Common Filters:
- Severity level
- Event type
- Source IP
- Destination IP
- Time range
Use Case: Security teams detecting and responding to security incidents.
Compliance Dashboard
Purpose: Track compliance-related events and audit logs
Key Visualizations:
- User access events (timeline)
- Privileged access by user (data table)
- Policy violations (metric count)
- System changes (audit log table)
- Access denied events (bar chart)
- Compliance score (gauge)
Common Filters:
- User
- Resource accessed
- Action type
- Result (success/failure)
Use Case: Compliance officers ensuring adherence to regulatory requirements.
Log Analysis Dashboards
Web Server Log Dashboard
Purpose: Analyze web server access and error logs
Key Visualizations:
- Requests per minute (line chart)
- HTTP status code distribution (pie chart)
- Top requested URLs (data table)
- Response time percentiles (multi-line chart)
- Geographic visitor distribution (map)
- User agent breakdown (tag cloud)
Common Filters:
- HTTP method
- Status code
- URL path
- Referrer
Use Case: Web administrators analyzing traffic patterns and troubleshooting issues.
Application Error Dashboard
Purpose: Track and analyze application errors and exceptions
Key Visualizations:
- Error count over time (area chart)
- Error types distribution (pie chart)
- Most common error messages (data table)
- Affected users count (metric)
- Error stack trace viewer (log viewer)
- Error rate by version (stacked bar chart)
Common Filters:
- Error type
- Severity
- Application version
- Environment
Use Case: Development teams prioritizing bug fixes and monitoring application stability.
Business Intelligence Dashboards
E-commerce Analytics Dashboard
Purpose: Track online sales and customer behavior
Key Visualizations:
- Revenue over time (line chart)
- Conversion rate (metric with trend)
- Top-selling products (bar chart)
- Average order value (gauge)
- Cart abandonment rate (metric)
- Customer lifetime value distribution (histogram)
Common Filters:
- Product category
- Customer segment
- Geographic region
- Date range
Use Case: E-commerce teams optimizing sales strategies and product offerings.
Marketing Campaign Dashboard
Purpose: Measure marketing campaign effectiveness
Key Visualizations:
- Campaign ROI (metric)
- Click-through rate by campaign (bar chart)
- Lead generation over time (area chart)
- Cost per acquisition (gauge)
- Channel performance comparison (grouped bar chart)
- Attribution model visualization (sankey diagram)
Common Filters:
- Campaign name
- Marketing channel
- Target audience
- Date range
Use Case: Marketing teams optimizing campaign spend and measuring ROI.
Customer Support Dashboard
Purpose: Monitor support ticket metrics and team performance
Key Visualizations:
- Ticket volume over time (line chart)
- Average resolution time (metric)
- Tickets by status (pie chart)
- First response time (gauge)
- Agent performance metrics (data table)
- Customer satisfaction scores (trend line)
Common Filters:
- Priority level
- Category
- Agent
- Status
Use Case: Support teams managing ticket queues and improving response times.
IoT and Sensor Data Dashboards
IoT Device Monitoring Dashboard
Purpose: Track IoT device status and sensor readings
Key Visualizations:
- Device online/offline status (status map)
- Sensor readings over time (multi-line chart)
- Temperature heat map by location (heat map)
- Battery levels (gauge charts)
- Alert count by device (bar chart)
- Data transmission rate (area chart)
Common Filters:
- Device ID
- Location
- Device type
- Alert status
Use Case: IoT operations teams monitoring distributed sensor networks.
Database Monitoring Dashboards
Elasticsearch Cluster Dashboard
Purpose: Monitor Elasticsearch cluster health and performance
Key Visualizations:
- Cluster status (status indicator)
- Index size and document count (metrics)
- Query rate and latency (line charts)
- JVM heap usage (gauge)
- Shard allocation (visualization)
- Indexing rate (area chart)
Common Filters:
- Node name
- Index name
- Time range
Use Case: Elasticsearch administrators ensuring cluster stability and performance.
Best Practices for Dashboard Design
- Start with key metrics: Identify the most important KPIs first
- Use appropriate visualizations: Match chart types to data types
- Maintain visual hierarchy: Place critical information prominently
- Add context: Include benchmark lines and targets
- Enable interactivity: Add filters and drill-downs
- Keep it simple: Avoid cluttering with unnecessary elements
- Use consistent colors: Maintain color schemes for similar metrics
- Update regularly: Ensure dashboards reflect current needs
Dashboard Templates and Resources
Where to Find Dashboard Examples
- Kibana Sample Data: Built-in sample dashboards for exploration
- Elastic Solutions: Pre-built dashboards for specific use cases
- Community Forums: User-shared dashboard configurations
- GitHub Repositories: Open-source dashboard templates
- Integration Modules: Beats modules include pre-configured dashboards
Loading Sample Dashboards
- Navigate to Home in Kibana
- Click Try sample data
- Select a dataset (e.g., Sample web logs, Sample e-commerce orders)
- Click Add data
- Click View data to see pre-built dashboards
Frequently Asked Questions
Q: Can I customize these dashboard examples for my needs?
A: Yes, all dashboard examples can be customized by adding, removing, or modifying visualizations to match your specific requirements.
Q: How do I create these dashboards from scratch?
A: Start by identifying your key metrics, create individual visualizations for each metric, then combine them into a dashboard using Kibana's dashboard builder.
Q: Are these dashboards suitable for real-time monitoring?
A: Yes, most of these dashboards can be configured with auto-refresh intervals for real-time monitoring, though refresh rates should be adjusted based on data volume and performance requirements.
Q: Can I use multiple dashboards together?
A: Yes, you can create dashboard links and drill-downs to navigate between related dashboards, creating a comprehensive monitoring solution.
Q: Do I need special plugins for these dashboards?
A: Most examples use standard Kibana features. However, some specialized visualizations may require additional plugins or Elastic Stack integrations.
Q: How do I share these dashboards with my team?
A: Use Kibana's sharing features to generate links, export PDFs, or embed dashboards in other applications. Configure appropriate access controls for security.
Q: Can I schedule automated reports from these dashboards?
A: Yes, use Kibana's reporting features to schedule PDF or PNG snapshots that can be emailed to stakeholders automatically.
Q: What's the recommended number of visualizations per dashboard?
A: For optimal performance and usability, limit dashboards to 8-12 visualizations. Create multiple focused dashboards rather than one overcrowded dashboard.
Q: How do I optimize dashboard performance?
A: Use appropriate time ranges, optimize queries, limit the number of panels, use summary indices for historical data, and consider using Canvas for complex layouts.
Q: Can I export and reuse these dashboards across environments?
A: Yes, export dashboards using Kibana's saved objects feature, then import them into other Kibana instances. Ensure index patterns and field mappings are consistent.
