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66 lines
2.1 KiB
Plaintext
66 lines
2.1 KiB
Plaintext
---
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title: "Metrics"
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description: "Track and analyze comprehensive pipeline metrics with Tracer"
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---
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## Overview
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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.
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## Key Metrics Tracked
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### Resource Utilization
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- CPU Usage: Per-process utilization, saturation levels, and hotspots
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- Memory Usage: Allocation, peak consumption, and memory efficiency
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- I/O Ops: Disk reads/writes, throughput, and bottleneck detection
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- Network Activity: Bandwidth usage, transfer volume, and congestion
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- GPU Utilization: Compute load and VRAM usage (when applicable)
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### Performance Metrics
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- Execution Time: Wall-clock, CPU, and wait times per task
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- Throughput: Data processed per unit time (e.g., samples/hour)
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- Latency: Startup delays, scheduling lag, and queueing overhead
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- Parallelization: Concurrency levels and contention across workers
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### Cost Metrics
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- Compute Costs: Per-task and per-pipeline cost attribution
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- Resource Costs: Storage, network, and transfer charges
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- Efficiency: Cost per sample, cost per GB processed
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- Waste Detection: Idle resources, over-provisioning, and inefficiencies
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## Real-Time Monitoring
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Inspect live metrics as your pipeline runs, with immediate visibility into performance, utilization, and potential bottlenecks.
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## Historical Analysis
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- Analyze past runs to uncover long-term patterns and optimization opportunities:
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- Performance Trends: How execution times shift across versions
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- Utilization Patterns: Persistent over/under-use of compute or memory
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- Cost Evolution: Impact of configuration changes on total spend
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- Regression Detection: Automatic alerts for performance degradation
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