f5cc502874
1) Breaking changes! Updated collection code for proper Prometheus support - Now metrics names of all subcollectors have prefixes: nsq_topic_, nsq_channel_, nsq_client_ As a result metrics registration code now passing Prometheus' client validation, also it fixes scrape warnings - "type" label in exported metrics removed as obsolete 2) Add reset of gauges before scrape (like in haproxy-exporter) 3) Refactor: subcollectors logic is simplified, multiple collectors support removed We always use 'stats' collector so it removes unnecessary flexibility and complexity.
101 lines
2.4 KiB
Go
101 lines
2.4 KiB
Go
package collector
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import (
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"strconv"
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"github.com/prometheus/client_golang/prometheus"
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)
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type topicStats []struct {
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val func(*topic) float64
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vec *prometheus.GaugeVec
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}
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// TopicStats creates a new stats collector which is able to
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// expose the topic metrics of a nsqd node to Prometheus.
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func TopicStats(namespace string) StatsCollector {
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labels := []string{"topic", "paused"}
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namespace += "_topic"
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return topicStats{
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{
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val: func(t *topic) float64 { return float64(len(t.Channels)) },
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vec: prometheus.NewGaugeVec(prometheus.GaugeOpts{
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Namespace: namespace,
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Name: "channel_count",
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Help: "Number of channels",
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}, labels),
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},
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{
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val: func(t *topic) float64 { return float64(t.Depth) },
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vec: prometheus.NewGaugeVec(prometheus.GaugeOpts{
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Namespace: namespace,
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Name: "depth",
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Help: "Queue depth",
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}, labels),
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},
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{
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val: func(t *topic) float64 { return float64(t.BackendDepth) },
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vec: prometheus.NewGaugeVec(prometheus.GaugeOpts{
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Namespace: namespace,
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Name: "backend_depth",
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Help: "Queue backend depth",
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}, labels),
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},
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{
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val: func(t *topic) float64 { return getPercentile(t, 99) },
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vec: prometheus.NewGaugeVec(prometheus.GaugeOpts{
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Namespace: namespace,
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Name: "e2e_latency_99_percentile",
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Help: "Queue e2e latency 99th percentile",
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}, labels),
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},
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{
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val: func(t *topic) float64 { return getPercentile(t, 95) },
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vec: prometheus.NewGaugeVec(prometheus.GaugeOpts{
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Namespace: namespace,
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Name: "e2e_latency_95_percentile",
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Help: "Queue e2e latency 95th percentile",
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}, labels),
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},
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{
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val: func(t *topic) float64 { return float64(t.MessageCount) },
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vec: prometheus.NewGaugeVec(prometheus.GaugeOpts{
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Namespace: namespace,
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Name: "message_count",
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Help: "Queue message count",
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}, labels),
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},
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}
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}
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func (ts topicStats) set(s *stats) {
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for _, topic := range s.Topics {
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labels := prometheus.Labels{
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"topic": topic.Name,
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"paused": strconv.FormatBool(topic.Paused),
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}
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for _, c := range ts {
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c.vec.With(labels).Set(c.val(topic))
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}
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}
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}
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func (ts topicStats) collect(out chan<- prometheus.Metric) {
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for _, c := range ts {
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c.vec.Collect(out)
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}
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}
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func (ts topicStats) describe(ch chan<- *prometheus.Desc) {
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for _, c := range ts {
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c.vec.Describe(ch)
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}
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}
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func (ts topicStats) reset() {
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for _, c := range ts {
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c.vec.Reset()
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}
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}
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