wings/environment/docker/stats.go

package docker

import (
	"context"
	"encoding/json"
	"github.com/apex/log"
	"github.com/docker/docker/api/types"
	"github.com/pkg/errors"
	"github.com/pterodactyl/wings/environment"
	"io"
	"math"
	"sync/atomic"
)

// Attach to the instance and then automatically emit an event whenever the resource usage for the
// server process changes.
func (e *Environment) pollResources(ctx context.Context) error {
	l := log.WithField("container_id", e.Id)

	l.Debug("starting resource polling for container")
	defer l.Debug("stopped resource polling for container")

	if e.st.Load() == environment.ProcessOfflineState {
		return errors.New("cannot enable resource polling on a stopped server")
	}

	stats, err := e.client.ContainerStats(context.Background(), e.Id, true)
	if err != nil {
		return errors.WithStack(err)
	}
	defer stats.Body.Close()

	dec := json.NewDecoder(stats.Body)

	for {
		select {
		case <-ctx.Done():
			return ctx.Err()
		default:
			var v *types.StatsJSON

			if err := dec.Decode(&v); err != nil {
				if err != io.EOF {
					l.WithField("error", errors.WithStack(err)).Warn("error while processing Docker stats output for container")
				} else {
					l.Debug("io.EOF encountered during stats decode, stopping polling...")
				}

				return nil
			}

			// Disable collection if the server is in an offline state and this process is still running.
			if e.st.Load() == environment.ProcessOfflineState {
				l.Debug("process in offline state while resource polling is still active; stopping poll")
				return nil
			}

			var rx uint64
			var tx uint64
			for _, nw := range v.Networks {
				atomic.AddUint64(&rx, nw.RxBytes)
				atomic.AddUint64(&tx, nw.RxBytes)
			}

			st := &environment.Stats{
				Memory:      calculateDockerMemory(v.MemoryStats),
				MemoryLimit: v.MemoryStats.Limit,
				CpuAbsolute: calculateDockerAbsoluteCpu(&v.PreCPUStats, &v.CPUStats),
				Network: struct {
					RxBytes uint64 `json:"rx_bytes"`
					TxBytes uint64 `json:"tx_bytes"`
				}{
					RxBytes: rx,
					TxBytes: tx,
				},
			}

			if b, err := json.Marshal(st); err != nil {
				l.WithField("error", errors.WithStack(err)).Warn("error while marshaling stats object for environment")
			} else {
				e.Events().Publish(environment.ResourceEvent, string(b))
			}
		}
	}
}

// The "docker stats" CLI call does not return the same value as the types.MemoryStats.Usage
// value which can be rather confusing to people trying to compare panel usage to
// their stats output.
//
// This math is straight up lifted from their CLI repository in order to show the same
// values to avoid people bothering me about it. It should also reflect a slightly more
// correct memory value anyways.
//
// @see https://github.com/docker/cli/blob/96e1d1d6/cli/command/container/stats_helpers.go#L227-L249
func calculateDockerMemory(stats types.MemoryStats) uint64 {
	if v, ok := stats.Stats["total_inactive_file"]; ok && v < stats.Usage {
		return stats.Usage - v
	}

	if v := stats.Stats["inactive_file"]; v < stats.Usage {
		return stats.Usage - v
	}

	return stats.Usage
}

// Calculates the absolute CPU usage used by the server process on the system, not constrained
// by the defined CPU limits on the container.
//
// @see https://github.com/docker/cli/blob/aa097cf1aa19099da70930460250797c8920b709/cli/command/container/stats_helpers.go#L166
func calculateDockerAbsoluteCpu(pStats *types.CPUStats, stats *types.CPUStats) float64 {
	// Calculate the change in CPU usage between the current and previous reading.
	cpuDelta := float64(stats.CPUUsage.TotalUsage) - float64(pStats.CPUUsage.TotalUsage)

	// Calculate the change for the entire system's CPU usage between current and previous reading.
	systemDelta := float64(stats.SystemUsage) - float64(pStats.SystemUsage)

	// Calculate the total number of CPU cores being used.
	cpus := float64(stats.OnlineCPUs)
	if cpus == 0.0 {
		cpus = float64(len(stats.CPUUsage.PercpuUsage))
	}

	percent := 0.0
	if systemDelta > 0.0 && cpuDelta > 0.0 {
		percent = (cpuDelta / systemDelta) * cpus * 100.0
	}

	return math.Round(percent*1000) / 1000
}