Files
jarl/internal/stats/query.go
T
abrown38andClaude Opus 5.5 3b7bee67f8 Add optional query statistics
Off by default (stats in jarl.yaml). When enabled, Jarl adds a loopback
statistics channel and a response log to named's configuration (merged
into existing logging/statistics-channels statements) and switches
response logging with rndc responselog, because the responselog option
only counts when named starts. jarld polls named's counters every minute
and tails the response log (resuming after restarts and across
rotation). It stores aggregates, never individual queries, in a separate
SQLite database: per-minute, hourly and daily counters (queries, result
codes, record types, views, zones, cache hits, upstream latency, DNSSEC)
and hourly/daily top lists (names, clients, NXDOMAIN and SERVFAIL names,
refused clients), each with its own retention. Clients can be anonymized
or excluded.

- Web UI: Statistics page with KPI tiles, queries and failed answers over
  time, a weekday x hour heatmap, top lists and breakdowns; SVG charts
  with hover/keyboard readouts, a table view and light/dark palettes
  validated for colour-vision deficiency.
- CLI: jarl stats status|summary|top|timeline|heatmap|breakdown.
- API: /api/v1/stats/*, behind a new "stats" permission resource.
- jarld brings named's configuration up to date with jarl.yaml at
  startup (engine.SyncConfig), never overwriting hand-edited files.
- resync now refuses to overwrite drifted files without force, as
  documented.
- tmpfiles.d creates /var/log/named (allowed by named's AppArmor profile
  on Debian 13 and Ubuntu).
- The e2e harness runs named with -f like the Debian unit.
- docs/stats.md, plus API, CLI, configuration, permissions and README
  updates.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-07 20:21:34 +00:00

423 lines
12 KiB
Go

package stats
import (
"cmp"
"context"
"fmt"
"slices"
"strings"
"time"
)
// Querier answers questions about stored statistics.
type Querier struct {
Store *Store
Opts Options
Now func() time.Time
}
// NewQuerier returns a querier for a collector's data.
func NewQuerier(c *Collector) *Querier {
return &Querier{Store: c.store, Opts: c.opts, Now: time.Now}
}
func (q *Querier) loc() *time.Location {
if q.Opts.Location != nil {
return q.Opts.Location
}
return time.Local
}
// Resolution picks the finest stored resolution that covers a time range
// starting since ago.
func (q *Querier) Resolution(since time.Duration) string {
switch {
case since <= 48*time.Hour && since <= q.Opts.RetainMinute:
return ResMinute
case since <= q.Opts.RetainHour:
return ResHour
}
return ResDay
}
// topsResolution picks the resolution for top lists, which exist per hour
// and per day.
func (q *Querier) topsResolution(since time.Duration) string {
if since <= 7*24*time.Hour && since <= q.Opts.RetainHour {
return ResHour
}
return ResDay
}
// bucketStart returns the start of the bucket containing t at a resolution.
func (q *Querier) bucketStart(res string, t time.Time) int64 {
switch res {
case ResMinute:
return t.Unix() - t.Unix()%60
case ResHour:
return t.Unix() - t.Unix()%3600
}
l := t.In(q.loc())
return time.Date(l.Year(), l.Month(), l.Day(), 0, 0, 0, 0, q.loc()).Unix()
}
// sums returns the totals of counters (optionally with a key prefix) in
// [from, to).
func (s *Store) sums(ctx context.Context, res string, from, to int64, prefix string) (map[string]int64, error) {
rows, err := s.db.QueryContext(ctx, `SELECT key, SUM(value) FROM counters WHERE res = ? AND ts >= ? AND ts < ? AND key LIKE ? ESCAPE '\' GROUP BY key`,
res, from, to, likePrefix(prefix))
if err != nil {
return nil, err
}
defer rows.Close()
out := map[string]int64{}
for rows.Next() {
var k string
var v int64
if err := rows.Scan(&k, &v); err != nil {
return nil, err
}
out[k] = v
}
return out, rows.Err()
}
func likePrefix(p string) string {
r := strings.NewReplacer(`\`, `\\`, `%`, `\%`, `_`, `\_`)
return r.Replace(p) + "%"
}
// series returns the values of a counter per bucket in [from, to).
func (s *Store) series(ctx context.Context, res string, from, to int64, key string) (map[int64]int64, error) {
rows, err := s.db.QueryContext(ctx, `SELECT ts, value FROM counters WHERE res = ? AND key = ? AND ts >= ? AND ts < ?`, res, key, from, to)
if err != nil {
return nil, err
}
defer rows.Close()
out := map[int64]int64{}
for rows.Next() {
var ts, v int64
if err := rows.Scan(&ts, &v); err != nil {
return nil, err
}
out[ts] = v
}
return out, rows.Err()
}
// tops sums top lists in [from, to).
func (s *Store) tops(ctx context.Context, res, kind string, from, to int64, limit int) ([]Entry, error) {
rows, err := s.db.QueryContext(ctx, `SELECT key, SUM(count) AS n FROM tops WHERE res = ? AND kind = ? AND ts >= ? AND ts < ?
GROUP BY key ORDER BY n DESC, key LIMIT ?`, res, kind, from, to, limit)
if err != nil {
return nil, err
}
defer rows.Close()
out := []Entry{}
for rows.Next() {
var e Entry
if err := rows.Scan(&e.Key, &e.Count); err != nil {
return nil, err
}
out = append(out, e)
}
return out, rows.Err()
}
func sorted(m map[string]int64, prefix string) []Entry {
out := []Entry{}
for k, v := range m {
if strings.HasPrefix(k, prefix) && v != 0 {
out = append(out, Entry{strings.TrimPrefix(k, prefix), v})
}
}
slices.SortFunc(out, func(a, b Entry) int {
if a.Count != b.Count {
return cmp.Compare(b.Count, a.Count)
}
return cmp.Compare(a.Key, b.Key)
})
return out
}
// Summary is an overview of a time range.
type Summary struct {
From time.Time `json:"from"`
To time.Time `json:"to"`
Resolution string `json:"resolution"`
Queries int64 `json:"queries"`
// AvgQPS is queries per second over the part of the range with data.
AvgQPS float64 `json:"avg_qps"`
Peak *struct {
Time time.Time `json:"time"`
Queries int64 `json:"queries"`
Per string `json:"per"` // minute, hour or day
} `json:"peak,omitempty"`
RCodes []Entry `json:"rcodes"`
QTypes []Entry `json:"qtypes"`
Views []Entry `json:"views"`
Zones []Entry `json:"zones"`
Answers []Entry `json:"answers"` // authoritative, recursive
Transport []Entry `json:"transport"` // udp, tcp
CacheHitRatio *float64 `json:"cache_hit_ratio,omitempty"`
NXDomainRatio *float64 `json:"nxdomain_ratio,omitempty"`
Tops map[string][]Entry `json:"tops,omitempty"`
}
// Summary summarizes the last since.
func (q *Querier) Summary(ctx context.Context, since time.Duration, topLimit int) (*Summary, error) {
now := q.Now()
res := q.Resolution(since)
from := q.bucketStart(res, now.Add(-since))
to := now.Unix() + 1
all, err := q.Store.sums(ctx, res, from, to, "")
if err != nil {
return nil, err
}
s := &Summary{From: time.Unix(from, 0), To: now, Resolution: res, Queries: all["queries"],
RCodes: sorted(all, "rcode:"), QTypes: sorted(all, "qtype:"), Views: sorted(all, "view:"), Zones: sorted(all, "zone:"),
Answers: sorted(all, "answer:"), Transport: sorted(all, "transport:")}
if h, m := all["cache:hits"], all["cache:misses"]; h+m > 0 {
r := float64(h) / float64(h+m)
s.CacheHitRatio = &r
}
if s.Queries > 0 {
r := float64(all["rcode:NXDOMAIN"]) / float64(s.Queries)
s.NXDomainRatio = &r
}
per, err := q.Store.series(ctx, res, from, to, "queries")
if err != nil {
return nil, err
}
if len(per) > 0 {
first, peakTS := int64(1<<62), int64(0)
var peak int64 = -1
for ts, v := range per {
first = min(first, ts)
if v > peak || v == peak && ts < peakTS {
peak, peakTS = v, ts
}
}
if secs := float64(to - first); secs > 0 {
s.AvgQPS = float64(s.Queries) / secs
}
s.Peak = &struct {
Time time.Time `json:"time"`
Queries int64 `json:"queries"`
Per string `json:"per"`
}{time.Unix(peakTS, 0), peak, map[string]string{ResMinute: "minute", ResHour: "hour", ResDay: "day"}[res]}
}
if topLimit > 0 {
s.Tops = map[string][]Entry{}
for _, k := range []string{KindName, KindClient, KindNXDomain} {
es, err := q.Top(ctx, k, since, topLimit)
if err != nil {
return nil, err
}
s.Tops[k] = es
}
}
return s, nil
}
// Top returns the largest entries of a top list over the last since.
func (q *Querier) Top(ctx context.Context, kind string, since time.Duration, limit int) ([]Entry, error) {
if !slices.Contains(Kinds, kind) {
return nil, fmt.Errorf("unknown list %q (use %s)", kind, strings.Join(Kinds, ", "))
}
now := q.Now()
res := q.topsResolution(since)
return q.Store.tops(ctx, res, kind, q.bucketStart(res, now.Add(-since)), now.Unix()+1, limit)
}
// Breakdown returns the totals of a counter group (qtype, rcode, view,
// zone, answer, transport, rtt, dnssec, cache, ratelimit) over the last since.
func (q *Querier) Breakdown(ctx context.Context, group string, since time.Duration) ([]Entry, error) {
if !slices.Contains(Groups, group) {
return nil, fmt.Errorf("unknown group %q (use %s)", group, strings.Join(Groups, ", "))
}
now := q.Now()
res := q.Resolution(since)
m, err := q.Store.sums(ctx, res, q.bucketStart(res, now.Add(-since)), now.Unix()+1, group+":")
if err != nil {
return nil, err
}
return sorted(m, group+":"), nil
}
// Groups are the counter groups Breakdown accepts.
var Groups = []string{"qtype", "rcode", "view", "zone", "answer", "transport", "rtt", "dnssec", "cache", "ratelimit"}
// Timeline is a set of series over time.
type Timeline struct {
Step string `json:"step"`
Times []int64 `json:"times"` // bucket starts (Unix seconds)
Series []*Series `json:"series"`
}
// Series is one counter over time.
type Series struct {
Key string `json:"key"`
Values []int64 `json:"values"`
}
var steps = []struct {
name string
d time.Duration
res string
}{
{"1m", time.Minute, ResMinute}, {"5m", 5 * time.Minute, ResMinute}, {"15m", 15 * time.Minute, ResMinute},
{"1h", time.Hour, ResHour}, {"6h", 6 * time.Hour, ResHour}, {"1d", 24 * time.Hour, ResDay},
}
// Timeline returns counters over the last since. keys are counter names;
// a key ending in ":*" means every counter of that group. step is "auto"
// or one of 1m, 5m, 15m, 1h, 6h, 1d.
func (q *Querier) Timeline(ctx context.Context, since time.Duration, step string, keys []string) (*Timeline, error) {
idx := -1
for i, st := range steps {
ok := st.res == ResMinute && since <= q.Opts.RetainMinute || st.res == ResHour && since <= q.Opts.RetainHour || st.res == ResDay
if step == st.name {
if !ok {
return nil, fmt.Errorf("step %s needs %s data, which is only kept for %s", st.name, map[string]string{ResMinute: "per-minute", ResHour: "hourly"}[st.res], humanDuration(map[string]time.Duration{ResMinute: q.Opts.RetainMinute, ResHour: q.Opts.RetainHour}[st.res]))
}
idx = i
break
}
if step == "auto" || step == "" {
if ok && since/st.d <= 300 {
idx = i
break
}
}
}
if idx < 0 {
if step != "auto" && step != "" {
return nil, fmt.Errorf("unknown step %q (use auto, 1m, 5m, 15m, 1h, 6h or 1d)", step)
}
idx = len(steps) - 1
}
st := steps[idx]
now := q.Now()
// Buckets aligned to the step (days to local midnight).
var starts []int64
if st.res == ResDay {
for t := time.Unix(q.bucketStart(ResDay, now.Add(-since)), 0).In(q.loc()); !t.After(now); t = t.AddDate(0, 0, 1) {
starts = append(starts, t.Unix())
}
} else {
sd := int64(st.d.Seconds())
first := now.Add(-since).Unix()
first -= first % sd
for t := first; t <= now.Unix(); t += sd {
starts = append(starts, t)
}
}
from, to := starts[0], now.Unix()+1
// Expand group keys.
var expanded []string
for _, k := range keys {
if g, ok := strings.CutSuffix(k, ":*"); ok {
m, err := q.Store.sums(ctx, st.res, from, to, g+":")
if err != nil {
return nil, err
}
for _, e := range sorted(m, "") {
expanded = append(expanded, e.Key)
}
continue
}
expanded = append(expanded, k)
}
tl := &Timeline{Step: st.name, Times: starts, Series: []*Series{}}
for _, k := range expanded {
raw, err := q.Store.series(ctx, st.res, from, to, k)
if err != nil {
return nil, err
}
vals := make([]int64, len(starts))
for ts, v := range raw {
// The bucket is the last start <= ts.
i, found := slices.BinarySearch(starts, ts)
if !found {
i--
}
if i >= 0 && i < len(vals) {
vals[i] += v
}
}
tl.Series = append(tl.Series, &Series{Key: k, Values: vals})
}
return tl, nil
}
// Heatmap is average activity per weekday and hour of day (local time).
type Heatmap struct {
Key string `json:"key"`
// Avg[d][h] is the average per hour on weekday d (0 = Monday) at
// hour h; -1 where there is no data.
Avg [7][24]float64 `json:"avg"`
// Samples[d][h] is how many hours the average is based on.
Samples [7][24]int `json:"samples"`
From time.Time `json:"from"`
}
// Heatmap averages a counter (default "queries") by weekday and hour over
// the last since (at most the hourly retention).
func (q *Querier) Heatmap(ctx context.Context, key string, since time.Duration) (*Heatmap, error) {
if key == "" {
key = "queries"
}
since = min(since, q.Opts.RetainHour)
now := q.Now()
from := q.bucketStart(ResHour, now.Add(-since))
raw, err := q.Store.series(ctx, ResHour, from, now.Unix()+1, key)
if err != nil {
return nil, err
}
hm := &Heatmap{Key: key, From: time.Unix(from, 0)}
var sum [7][24]int64
for ts, v := range raw {
t := time.Unix(ts, 0).In(q.loc())
d := (int(t.Weekday()) + 6) % 7
sum[d][t.Hour()] += v
hm.Samples[d][t.Hour()]++
}
for d := range 7 {
for h := range 24 {
if n := hm.Samples[d][h]; n > 0 {
hm.Avg[d][h] = float64(sum[d][h]) / float64(n)
} else {
hm.Avg[d][h] = -1
}
}
}
return hm, nil
}
// ParseSince parses a range such as 90m, 24h, 7d or 2w.
func ParseSince(s string) (time.Duration, error) {
if s == "" {
return 24 * time.Hour, nil
}
mult := time.Duration(0)
switch {
case strings.HasSuffix(s, "d"):
mult = 24 * time.Hour
case strings.HasSuffix(s, "w"):
mult = 7 * 24 * time.Hour
}
if mult > 0 {
var n int
if _, err := fmt.Sscanf(s[:len(s)-1], "%d", &n); err != nil || n <= 0 || fmt.Sprint(n) != s[:len(s)-1] {
return 0, fmt.Errorf("invalid range %q (use e.g. 90m, 24h, 7d, 2w)", s)
}
return time.Duration(n) * mult, nil
}
d, err := time.ParseDuration(s)
if err != nil || d <= 0 {
return 0, fmt.Errorf("invalid range %q (use e.g. 90m, 24h, 7d, 2w)", s)
}
return d, nil
}