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Overview Tracer automatically captures detailed metrics for every process in your pipeline, providing deep visibility into resource usage, performance, and execution patterns without requiring any code changes.
Key Metrics Tracked Resource Utilization
CPU Usage: Per-process utilization, saturation levels, and hotspots
Memory Usage: Allocation, peak consumption, and memory efficiency
I/O Ops: Disk reads/writes, throughput, and bottleneck detection
Network Activity: Bandwidth usage, transfer volume, and congestion
GPU Utilization: Compute load and VRAM usage (when applicable)
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Execution Time: Wall-clock, CPU, and wait times per task
Throughput: Data processed per unit time (e.g., samples/hour)
Latency: Startup delays, scheduling lag, and queueing overhead
Parallelization: Concurrency levels and contention across workers
Cost Metrics
Compute Costs: Per-task and per-pipeline cost attribution
Resource Costs: Storage, network, and transfer charges
Efficiency: Cost per sample, cost per GB processed
Waste Detection: Idle resources, over-provisioning, and inefficiencies
Your browser does not support the video tag. Real-Time Monitoring Inspect live metrics as your pipeline runs, with immediate visibility into performance, utilization, and potential bottlenecks.
Historical Analysis
Analyze past runs to uncover long-term patterns and optimization opportunities:
Performance Trends: How execution times shift across versions
Utilization Patterns: Persistent over/under-use of compute or memory
Cost Evolution: Impact of configuration changes on total spend
Regression Detection: Automatic alerts for performance degradation
