Viewing Application Metrics

Quant Cloud provides comprehensive metrics monitoring for each environment, giving you detailed insights into your application’s performance, resource utilization, and behavior over time. The metrics interface is accessible through your environment’s navigation and provides both real-time and historical data visualization.

Accessing Metrics

Navigation Access your environment’s metrics through the environment details page. The metrics interface provides a comprehensive dashboard with multiple performance charts and real-time data visualization.

Time Range Controls Adjust the monitoring time window using the time range selector, which offers several predefined options:

• 5m: Last 5 minutes for real-time monitoring
• 15m: Last 15 minutes for recent activity analysis
• 1h: Last hour for short-term trend analysis
• 6h: Last 6 hours for extended monitoring periods
• 1d: Last day for daily performance review

Interactive Charts All metrics are displayed as interactive time-series charts that automatically refresh to show the latest data. Charts include gridlines, legends, and hover tooltips for detailed data point information.

Core Performance Metrics

The metrics dashboard provides several key performance indicators organized into logical sections:

Resource Utilization

CPU Utilization (%) Displays the percentage of allocated CPU resources being consumed by your application instances. This metric helps identify computational bottlenecks and is essential for CPU-based auto-scaling decisions.

Memory Utilization (%) Shows memory consumption as a percentage of allocated memory across your instances. Critical for understanding memory pressure and optimizing resource allocation.

Ephemeral Storage Used (Bytes) Tracks temporary storage usage within container filesystems. Useful for monitoring cache usage, temporary file creation, and container-local data storage patterns.

Storage Metrics

Persistent Storage Size (Bytes) Monitors the total size of your persistent storage volumes over time. Shows growth trends and helps with capacity planning for your application’s data storage needs.

Traffic and Performance

Requests Per Second (RPS) Displays incoming request volume to your application when load balancing is configured. This metric is crucial for:

• Understanding traffic patterns and peak usage times
• Configuring RPS-based auto-scaling policies
• Identifying performance correlation with request volume

Note

RPS metrics are available when your environment is configured with load balancing. For environments without load balancing, this metric may not be displayed.

Advanced Monitoring Capabilities

Database-Specific Metrics For environments with managed databases, additional metrics are available:

• Database CPU Utilization: Resource usage specific to database instances
• Database Connections: Active connection counts and patterns
• Database Memory Usage: Memory consumption for database operations
• Database Storage: Database-specific storage utilization and growth
• Database IOPS: Input/output operations per second for database performance analysis
• Database Latency: Response time metrics for database queries
• Database Throughput: Data transfer rates for database operations

Using Metrics for Optimization

Performance Analysis Use metrics data to identify performance patterns and bottlenecks:

• Monitor CPU spikes to identify computational bottlenecks
• Track memory usage trends to optimize allocation
• Analyze request patterns to understand user behavior
• Correlate storage growth with application usage

Auto-Scaling Configuration Metrics provide the data foundation for configuring effective auto-scaling policies:

• Use CPU utilization trends to set appropriate CPU-based scaling thresholds
• Monitor memory patterns to configure memory-based scaling
• Analyze RPS data to establish request-based scaling targets

Capacity Planning Historical metrics help with infrastructure planning:

• Storage growth trends inform persistent storage requirements
• Peak usage patterns guide resource allocation decisions
• Performance trends help predict future scaling needs

Troubleshooting Metrics are essential for diagnosing application issues:

• Identify resource constraints causing performance problems
• Correlate performance degradation with specific time periods
• Monitor the impact of deployments and configuration changes

Tip

Regularly review your metrics to establish baseline performance patterns. This makes it easier to identify anomalies and optimize your application’s resource utilization over time.

The comprehensive metrics dashboard provides the visibility needed to maintain optimal application performance, make informed scaling decisions, and ensure efficient resource utilization across your Quant Cloud environments.