Real-time Kafka Dashboard Design
Master the art of building effective Kafka monitoring dashboards that provide actionable insights, reduce mean time to resolution, and keep your team informed.
Why Kafka Dashboards Matter
A well-designed Kafka dashboard is the control center for your streaming infrastructure. It transforms raw metrics into actionable insights, helping teams detect issues before they impact users and understand system behavior at a glance.
Faster MTTR
Reduce mean time to resolution with clear visibility into system state
Proactive Monitoring
Spot trends and anomalies before they become production incidents
Team Alignment
Keep everyone on the same page about system health and performance
Essential Dashboard Panels
1. Cluster Health Overview
The first thing anyone should see - a high-level summary of cluster health with clear status indicators.
Key Metrics
- • Active broker count vs expected
- • Under-replicated partitions
- • Offline partitions (critical!)
- • Active controller indicator
Visualization
- • Traffic light status indicators
- • Single stat panels with thresholds
- • Gauge charts for capacity
- • Cluster topology map
2. Throughput Metrics
Track message flow through your cluster to understand capacity usage and detect anomalies in traffic patterns.
Key Metrics
- • Messages in/out per second
- • Bytes in/out per second
- • Per-topic breakdown
- • Producer request rate
Visualization
- • Time series line charts
- • Stacked area charts by topic
- • Comparison with historical baseline
- • Top N topics table
3. Consumer Lag Panel
The most critical metric for streaming applications - are your consumers keeping up with producers?
Key Metrics
- • Lag by consumer group
- • Lag by topic-partition
- • Lag rate of change
- • Time-based lag (seconds behind)
Visualization
- • Heatmap for partition lag
- • Bar chart for group comparison
- • Trend line with thresholds
- • Alert annotations
4. Latency Metrics
Track request latencies to identify performance bottlenecks and ensure SLA compliance.
Key Metrics
- • Produce request latency (p50, p95, p99)
- • Fetch request latency
- • End-to-end latency
- • Network round-trip time
Visualization
- • Histogram for distribution
- • Percentile line charts
- • SLA threshold lines
- • Latency breakdown by stage
5. Resource Utilization
Monitor broker resources to prevent capacity issues and plan for scaling.
Key Metrics
- • CPU utilization per broker
- • Memory/heap usage
- • Disk usage and I/O
- • Network throughput
Visualization
- • Gauge charts with thresholds
- • Per-broker comparison
- • Trend prediction
- • Capacity planning charts
Dashboard Design Best Practices
Follow the Inverted Pyramid
Start with high-level health indicators at the top, then drill down into details. Users should understand overall health within 3 seconds of viewing.
Use Consistent Color Coding
Green = healthy, Yellow = warning, Red = critical. Apply this consistently across all panels so users can scan quickly.
Include Threshold Lines
Show warning and critical thresholds on time series charts so operators can immediately see when values are approaching problematic levels.
Add Context with Annotations
Overlay deployment events, config changes, and alerts on your charts. This context is invaluable during incident investigation.
Design for Different Audiences
Create separate dashboards for different roles: executive summary for leadership, detailed operational dashboards for SREs, and debugging dashboards for developers.
Optimize Refresh Rates
Not everything needs to update every second. Use 5-15 second refresh for most metrics, faster updates only for critical real-time indicators.
Common Dashboard Mistakes to Avoid
Information Overload
Too many panels overwhelm users. Each panel should answer a specific question. If you can't explain why a panel exists, remove it.
No Baseline Context
Showing current values without historical context makes it hard to know if numbers are normal. Include week-over-week comparisons.
Hidden Drill-Down Paths
Users need clear paths to investigate. Add links from summary panels to detailed dashboards and from dashboards to logs.
Ignoring Mobile/TV Views
Dashboards displayed on NOC screens or mobile devices need different layouts. Test your dashboards at different resolutions.
Recommended Dashboard Hierarchy
Level 1: Executive Overview
Single screen showing overall Kafka health, key SLIs, and any active incidents. Designed for leadership and quick status checks.
Level 2: Operational Dashboard
Detailed cluster metrics, consumer lag, throughput, and resource utilization. This is the primary dashboard for day-to-day operations.
Level 3: Component Dashboards
Dedicated dashboards for brokers, topics, consumer groups, and Connect clusters. Deep-dive views for troubleshooting specific issues.
Level 4: Debug Dashboards
JVM metrics, network details, request-level tracing. Used during active incidents to drill into root causes.
Pre-Built Kafka Dashboards with KLogic
Skip the dashboard building and get production-ready Kafka monitoring out of the box. KLogic includes expertly designed dashboards following all these best practices.