Files
seaweedfs/weed/admin/dash/dashboard_metrics.go
T
Chris Lu d47cc45b1f admin: fold dashboard sparklines into the existing cards (de-dup) (#9964)
admin: fold dashboard sparklines into the existing cards

The trend sparklines added in #9957 lived in a separate "Cluster Trends"
row that duplicated the existing summary cards (Volumes, Files, Disk Used,
EC Shards). Remove that row and instead render each sparkline inside the
matching summary card, so every headline number shows its recent trend
without duplication. The two maintenance metrics that have no existing
card — Active Tasks and Workers — now fill the previously-empty columns of
the EC row (also with sparklines).

DashboardTrends changes from a Cards slice to named per-card sparkline
SVGs (+ current values for the two maintenance cards). Drops the now-unused
trendBytes helper (disk size keeps using the existing formatBytes).
2026-06-14 14:17:43 -07:00

180 lines
5.6 KiB
Go

package dash
import (
"fmt"
"strings"
"time"
)
// dashMaxSamples bounds the in-memory trend ring buffer. At the 15s sample
// cadence (piggy-backed on publishMaintenanceMetrics) this is ~15 minutes.
const dashMaxSamples = 60
// dashSample is one point-in-time snapshot of a few headline cluster numbers,
// derived from data the admin already holds (cluster topology + the in-process
// maintenance queue) — no Prometheus scrape required.
type dashSample struct {
t time.Time
volumes float64
ecShards float64
diskUsed float64
files float64
tasks float64 // pending/assigned/in-progress maintenance tasks
workers float64
}
// DashboardTrends carries inline-SVG sparklines of recent cluster history,
// keyed to the dashboard's existing summary cards so each card shows a value
// plus its trend (rather than a separate, duplicate row). Maintenance metrics
// that have no existing card carry their current value too, and fill the
// previously-empty columns of the EC row.
type DashboardTrends struct {
Samples int `json:"samples"`
// Sparklines (raw <svg>) for the existing summary cards.
Volumes string `json:"-"`
Files string `json:"-"`
DiskUsed string `json:"-"`
EcShards string `json:"-"`
// Maintenance cards: value + sparkline.
Tasks string `json:"-"`
TasksValue string `json:"tasks"`
Workers string `json:"-"`
WorkersValue string `json:"workers"`
}
// recordDashboardSample snapshots headline cluster numbers into the ring
// buffer. Cheap: topology is already cached, and the maintenance stats are
// in-memory. Called on the existing maintenance-metrics ticker.
func (s *AdminServer) recordDashboardSample() {
topology, err := s.GetClusterTopology()
if err != nil || topology == nil {
return
}
ecShards := 0
for _, vs := range topology.VolumeServers {
ecShards += vs.EcShards
}
sample := dashSample{
t: time.Now(),
volumes: float64(topology.TotalVolumes),
ecShards: float64(ecShards),
diskUsed: float64(topology.TotalSize),
files: float64(topology.TotalFiles),
}
if s.maintenanceManager != nil {
if stats := s.maintenanceManager.GetStats(); stats != nil {
active := 0
for status, n := range stats.TasksByStatus {
switch string(status) {
case "pending", "assigned", "in_progress":
active += n
}
}
sample.tasks = float64(active)
sample.workers = float64(stats.ActiveWorkers)
}
}
s.dashSamplesMu.Lock()
s.dashSamples = append(s.dashSamples, sample)
if len(s.dashSamples) > dashMaxSamples {
s.dashSamples = s.dashSamples[len(s.dashSamples)-dashMaxSamples:]
}
s.dashSamplesMu.Unlock()
}
// GetDashboardTrends builds the trend cards from the current ring buffer.
func (s *AdminServer) GetDashboardTrends() DashboardTrends {
s.dashSamplesMu.Lock()
samples := make([]dashSample, len(s.dashSamples))
copy(samples, s.dashSamples)
s.dashSamplesMu.Unlock()
series := func(pick func(dashSample) float64) []float64 {
out := make([]float64, len(samples))
for i, smp := range samples {
out[i] = pick(smp)
}
return out
}
tasks := series(func(s dashSample) float64 { return s.tasks })
workers := series(func(s dashSample) float64 { return s.workers })
// Sparkline colors match the existing cards' border colors.
return DashboardTrends{
Samples: len(samples),
Volumes: sparklineSVG(series(func(s dashSample) float64 { return s.volumes }), "#1cc88a"), // success
Files: sparklineSVG(series(func(s dashSample) float64 { return s.files }), "#36b9cc"), // info
DiskUsed: sparklineSVG(series(func(s dashSample) float64 { return s.diskUsed }), "#f6c23e"), // warning
EcShards: sparklineSVG(series(func(s dashSample) float64 { return s.ecShards }), "#5a5c69"), // dark
Tasks: sparklineSVG(tasks, "#36b9cc"),
TasksValue: trendCount(last(tasks)),
Workers: sparklineSVG(workers, "#4e73df"),
WorkersValue: trendCount(last(workers)),
}
}
func last(v []float64) float64 {
if len(v) == 0 {
return 0
}
return v[len(v)-1]
}
// sparklineSVG renders a fixed-viewBox, width-responsive inline SVG line of the
// given points. Self-contained (no JS/chart lib); safe to inline in the page.
func sparklineSVG(pts []float64, color string) string {
const w, h = 240.0, 48.0
if len(pts) < 2 {
// Not enough history yet — draw a flat baseline so the card isn't empty.
return fmt.Sprintf(`<svg viewBox="0 0 %g %g" preserveAspectRatio="none" style="width:100%%;height:48px"><line x1="0" y1="%g" x2="%g" y2="%g" stroke="%s" stroke-width="2" opacity="0.4"/></svg>`, w, h, h/2, w, h/2, color)
}
minV, maxV := pts[0], pts[0]
for _, v := range pts {
if v < minV {
minV = v
}
if v > maxV {
maxV = v
}
}
span := maxV - minV
if span == 0 {
span = 1
}
dx := w / float64(len(pts)-1)
var line strings.Builder
for i, v := range pts {
x := float64(i) * dx
y := h - 3 - (v-minV)/span*(h-6) // 3px padding top/bottom; SVG y grows down
if i == 0 {
fmt.Fprintf(&line, "M%.1f %.1f", x, y)
} else {
fmt.Fprintf(&line, " L%.1f %.1f", x, y)
}
}
// Area path closes back along the baseline for a subtle fill.
area := fmt.Sprintf("%s L%.1f %.1f L0 %.1f Z", line.String(), w, h, h)
return fmt.Sprintf(`<svg viewBox="0 0 %g %g" preserveAspectRatio="none" style="width:100%%;height:48px"><path d="%s" fill="%s" opacity="0.12"/><path d="%s" fill="none" stroke="%s" stroke-width="2"/></svg>`,
w, h, area, color, line.String(), color)
}
// trendCount formats a count with thousands separators.
func trendCount(v float64) string {
n := int64(v)
s := fmt.Sprintf("%d", n)
if n < 0 {
return s
}
var out []byte
for i, c := range []byte(s) {
if i > 0 && (len(s)-i)%3 == 0 {
out = append(out, ',')
}
out = append(out, c)
}
return string(out)
}