Implement Pipeline Metrics Dashboard [7](#header-7)

[fuzziecoder]

🎯 Issue Summary

Create comprehensive metrics collection and dashboard for pipeline performance monitoring.

📋 Current Behavior

Limited metrics available at 2-cite-3

Missing Metrics:

• Success/failure rates over time
• Average execution duration trends
• Resource utilization
• Stage-level performance

✨ Proposed Solution

Implement Prometheus-style metrics collection with:

• Counter: Total executions, failures
• Histogram: Execution duration distribution
• Gauge: Active executions, queue depth

🔧 Technical Requirements

1. Metrics Library

• Add prometheus-client to requirements
• Create backend/monitoring/metrics.py

2. Metric Definitions

• pipeline_executions_total (Counter)
• pipeline_execution_duration_seconds (Histogram)
• pipeline_active_executions (Gauge)
• pipeline_failures_total (Counter)
• stage_execution_duration_seconds (Histogram)

3. Instrumentation

• Instrument pipeline executor with metrics
• Track stage-level metrics
• Add labels: pipeline_id, stage_name, status

4. Metrics Endpoint

• Add GET /metrics endpoint for Prometheus scraping
• Return metrics in Prometheus format

5. Dashboard

• Create Grafana dashboard JSON
• Add panels for success rate, duration, throughput
• Include alerting rules

📝 Acceptance Criteria

• ✅ Prometheus metrics exposed at /metrics
• ✅ All executions tracked with labels
• ✅ Grafana dashboard displays key metrics
• ✅ Metrics persist across restarts (if using Prometheus)
• ✅ Documentation for setting up monitoring stack

💡 Implementation Example

# backend/monitoring/metrics.py  [8](#header-8)
from prometheus_client import Counter, Histogram, Gauge  
  
pipeline_executions_total = Counter(  
    'pipeline_executions_total',  
    'Total pipeline executions',  
    ['pipeline_id', 'status']  
)  
  
pipeline_duration_seconds = Histogram(  
    'pipeline_execution_duration_seconds',  
    'Pipeline execution duration',  
    ['pipeline_id']  
)  
  
# In executor:  [9](#header-9)
pipeline_executions_total.labels(pipeline_id=id, status='success').inc()  
pipeline_duration_seconds.labels(pipeline_id=id).observe(duration)

[KalpanaBhaskar]

Hello, Im Kalpana, an Aperte contributor. Can u please assign this issue to me? I'm interested in understanding the issue and finding a solution

[Adii0906]

did you understand the issue? @KalpanaBhaskar

[fuzziecoder]

I've assigned this issue to you @KalpanaBhaskar

[KalpanaBhaskar]

did you understand the issue? @KalpanaBhaskar

Yes, I’m working on a fix and will resolve #28 before moving on to #30.