New Network Metrics Now Available in Cloud.gov Logs
We're excited to announce that Cloud.gov now provides application container network metrics, giving you deeper visibility into your application's network behavior. The new rx_bytes (received bytes) and tx_bytes (transmitted bytes) metrics are now automatically collected and available in Cloud.gov Logs.
What's New?
Cloud.gov now captures two essential network metrics for all application containers:
- Received network traffic (
containermetric.rx_bytes): Total bytes received by your application container - Transmitted network traffic (
containermetric.tx_bytes): Total bytes sent by your application container
These metrics are derived from Diego container telemetry and are automatically collected alongside existing CPU, memory, and disk metrics.
Why This Matters
Network metrics provide crucial insights for:
- Performance monitoring: Track network throughput and identify potential bottlenecks
- Troubleshooting: Correlate network activity with application behavior and performance issues
- Capacity planning: Make informed decisions about scaling based on actual network usage patterns
How to Access the New Metrics
The network metrics are available in the logs-metrics-* index pattern in Cloud.gov Logs. Here are some useful queries:
View all network metrics for your app:
@type: app_metric AND (containermetric.name: rx_bytes OR containermetric.name: tx_bytes)
Filter for received bytes only:
@type: app_metric AND containermetric.name: rx_bytes
Filter for transmitted bytes only:
@type: app_metric AND containermetric.name: tx_bytes
Combine with other filters:
@type: app_metric AND containermetric.name: tx_bytes AND @cf.app: "your-app-name"
What You Can Do With This Data
- Create visualizations: Build dashboards showing network traffic patterns over time
- Set up alerts: Monitor for unusual spikes in network activity
- Analyze trends: Identify peak usage times and seasonal patterns
- Correlate with other metrics: Compare network usage with CPU and memory to get a complete picture of application performance