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Observability Metrics

Comprehensive metrics collection and monitoring system for RecoAgent applications.

Overview​

The observability metrics system provides detailed metrics collection, aggregation, and monitoring capabilities for all aspects of RecoAgent operations.

Core Features​

  • Custom Metrics: Define and collect custom metrics
  • System Metrics: CPU, memory, disk usage monitoring
  • Application Metrics: Request rates, response times, error rates
  • Business Metrics: User engagement, conversion rates
  • Alerting: Automated alerts based on metric thresholds

Usage Examples​

Basic Metrics Collection​

from recoagent.observability.metrics import MetricsCollector

# Create metrics collector
metrics_collector = MetricsCollector()

# Record custom metric
metrics_collector.record_counter("queries_processed", 1)
metrics_collector.record_gauge("active_users", 150)
metrics_collector.record_histogram("response_time", 1.5)

Advanced Metrics​

# Create custom metrics
custom_metrics = metrics_collector.create_custom_metrics({
    "user_satisfaction": "gauge",
    "api_errors": "counter",
    "processing_time": "histogram"
})

# Record metrics
custom_metrics.user_satisfaction.set(0.85)
custom_metrics.api_errors.inc()
custom_metrics.processing_time.observe(2.3)

API Reference​

MetricsCollector Methods​

record_counter(name: str, value: float) -> None​

Record counter metric

Parameters:

  • name (str): Metric name
  • value (float): Counter value

record_gauge(name: str, value: float) -> None​

Record gauge metric

Parameters:

  • name (str): Metric name
  • value (float): Gauge value

See Also​