Dashboard Overview
Access the dashboard at the main application page after login. The interface is organized into panels showing system health, active jobs, queue status, and performance metrics.System Health
CPU, memory, and database status checks
Active Jobs
Real-time encoding progress tracking
Queue Status
Pending jobs and estimated completion
Performance
Throughput, savings, and efficiency metrics
Active Jobs Panel
Shows encoding tasks currently being processed across all nodes.Job Information Display
Progress Indicators
Active jobs display real-time progress bars:- Green bar: Encoding progressing normally (>5 fps)
- Yellow bar: Slow encoding (1-5 fps, CPU-only nodes)
- Red bar: Stalled job (no progress for >10 minutes)
Node Assignment
Each job shows which node is processing it. This helps identify:- Load distribution across nodes
- Node performance differences (GPU vs CPU)
- Potential bottlenecks (one node handling too many jobs)
Queue Status
Pending Jobs
Shows jobs waiting to be processed:Estimated Completion Time
Calculated based on:- Current throughput: Average jobs completed per hour (last 24h)
- Queue depth: Total jobs in
QUEUEDandANALYZINGstages - Active workers: Number of concurrent encoding processes
System Stats
CPU Usage
- Current Load: 1-minute load average
- CPU Cores: Total cores available for encoding
- Load Ratio: Load per core (ideal: under 1.5, warning: over 1.5, critical: over 2.0)
Memory Usage
- Used/Total: Memory consumption (e.g.,
12.4 GB / 16 GB) - Percentage: Memory utilization (warning at >85%, critical at >95%)
- Trend: Memory usage over time (chart)
Disk Space
Shows storage statistics for all configured library paths:Node Status
Health Indicators
Each node displays a status badge:- 🟢 ONLINE: Node is healthy and accepting jobs
- 🔴 OFFLINE: Node unreachable or not responding to health checks
- 🟡 DEGRADED: Node online but experiencing high load or errors
Active Jobs Per Node
Track workload distribution across your encoding cluster:Load Distribution
Shows how jobs are distributed across nodes:- Main node: Primary encoding node (usually GPU-accelerated)
- Child nodes: Worker nodes for parallel processing
- Balanced: Jobs distributed evenly based on node capacity
- Overloaded: One node handling disproportionate workload (>2x average)
Job History
Completed Jobs (Last 30 Days)
Shows encoding activity over the past month:Failed Jobs
Track encoding failures to identify problematic files:
Failure Categories:
- Corrupted File: Source file is damaged or incomplete (40%)
- Disk Space: Insufficient storage for output file (25%)
- Codec Issues: Unsupported or proprietary codec (20%)
- FFmpeg Errors: Encoding process crashed (10%)
- Other: Miscellaneous errors (5%)
Auto-Retry: Failed jobs are automatically retried
up to 3 times with different encoding settings before being marked as permanently failed.
Performance Metrics
Average Encode Speed (fps)
Frames per second processed by the encoding engine:
Factors Affecting Speed:
- Resolution: 4K files encode slower than 1080p (~60% speed reduction)
- Codec: AV1 is ~40% slower than HEVC, HEVC is ~30% slower than H.264
- Bitrate: Higher bitrate source files take longer to process
- Concurrent Jobs: Multiple jobs share GPU/CPU resources
Storage Saved
Total space saved by re-encoding to HEVC/AV1:Total Encoding Time
Cumulative time spent encoding across all nodes:- CPU Time: Total processing time (sum of all node hours)
- Wall Time: Real-world time elapsed (accounts for parallel processing)
- Efficiency: CPU Time / Wall Time (ideal: close to node count)
- over 2.5x (3 nodes): Excellent parallelization
- 1.5 to 2.5x (3 nodes): Good, some bottlenecks
- under 1.5x (3 nodes): Poor distribution, investigate load balancing
Advanced Monitoring
Codec Distribution
See/insights/codecs endpoint for codec usage analytics:
- Pie chart showing H.264, HEVC, AV1, VP9 distribution
- Percentage of library using each codec
- Helps identify remaining H.264 files to convert
Savings Trend (30-Day)
Track space savings over time:- Daily savings bar chart
- Cumulative savings line graph
- Identify encoding velocity (GB saved per day)
Node Performance Comparison
Compare encoding efficiency across nodes:
Use Cases:
- Identify underperforming nodes
- Compare GPU vs CPU efficiency
- Plan hardware acceleration upgrades
Health Checks
The system continuously monitors (see health check):Overall Status: Aggregated from all health checks. Dashboard
displays: - HEALTHY (green): All checks passing - WARNING (yellow): One or more warnings -
CRITICAL (red): One or more critical failures
Troubleshooting Dashboard Issues
No Active Jobs Showing
Possible causes:- No jobs in
ENCODINGstage (check queue status) - All nodes offline (check node status panel)
- Dashboard data not refreshing (refresh browser)
Incorrect Storage Stats
Possible causes:- Library paths not configured in database
- NFS mounts not accessible
- Permission issues reading disk stats
Stuck Progress Bars
Possible causes:- Job actually stalled (no FFmpeg progress updates)
- WebSocket connection lost (no real-time updates)
- Node crashed mid-encode
- Check backend logs for FFmpeg errors
- Refresh dashboard to reconnect WebSocket
- Verify node is still online in node status panel
API Endpoints
Access dashboard data programmatically:
Get your JWT token from the browser’s developer tools (F12 → Application → Local Storage →
token) or from the login API response.
Example: Get dashboard JSON:
Related Guides
Understanding Jobs
Job lifecycle, statuses, and auto-healing
Troubleshooting
Fix stuck jobs, disk space, and node issues
Multi-Node Setup
Track distributed encoding performance
GPU Acceleration
Speed up encoding with hardware acceleration