Metric Collection & Best Practices
Motivation:
The go-metrics package (https://github.com/docker/go-metrics/) provides a consistent and structured approach to collecting metrics within Docker projects. This outline describes the package’s core functionality and highlights best practices for defining and naming metrics, adhering to Prometheus standards.
Best Practices
Metric Naming
- Descriptive: Metric names should be self-explanatory and describe the value they represent.
- Consistent: Use consistent naming conventions across the entire codebase.
- Uppercase: Metric names should be in uppercase.
- Underscores: Use underscores to separate words in metric names.
Example:
// Number of successful container starts
container_starts_total
// Duration of a container's lifecycle
container_runtime_seconds
Metric Types
The go-metrics package supports different metric types, each with its own purpose:
- Counter: Measures the number of events that have occurred.
- Gauge: Represents a single value that can change over time.
- Histogram: Measures the distribution of values over time.
- Summary: Calculates percentiles and other statistics for a set of values.
Example:
// Number of failed container starts (Counter)
container_starts_failed_total
// Current number of running containers (Gauge)
container_running_count
// Distribution of container start times (Histogram)
container_start_time_seconds
// Summary of container resource usage (Summary)
container_resource_usage_summary
Metric Labels
Labels provide additional context for metrics, allowing for grouping and filtering.
Example:
// Container start times, labeled by container image and container ID
container_start_time_seconds{image="nginx", id="container_id"}
container_start_time_seconds{image="mysql", id="container_id"}
Prometheus Compatibility
The go-metrics package integrates with Prometheus (https://prometheus.io/), a popular monitoring system, ensuring seamless metric collection and visualization.
Example:
// Exposing metrics via a Prometheus endpoint
http.HandleFunc("/metrics", func(w http.ResponseWriter, r *http.Request) {
// Collect and expose metrics
goMetrics.Registry.ServeHTTP(w, r)
})
Documentation
- Metric Definitions: Document the purpose and meaning of each metric.
- Label Descriptions: Provide a clear explanation of each label and its values.
- Units: Specify the units of measurement for each metric.
Additional Considerations
- Metric Granularity: Balance between detailed information and performance impact.
- Data Retention: Determine the appropriate retention policy for collected metrics.
- Security: Ensure secure access to metrics endpoints.
- Data Privacy: Protect sensitive information when collecting metrics.
Resources:
- Prometheus Documentation: https://prometheus.io/docs/
- Docker Blog: https://www.docker.com/blog/
