// List of target relabel configurations.
RelabelConfigs []*relabel.Config `yaml:"relabel_configs,omitempty"`
// List of metric relabel configurations.
MetricRelabelConfigs []*relabel.Config `yaml:"metric_relabel_configs,omitempty"`
从下面代码看到，targetsFromGroup方法接收targetGroups对象，然后遍历targetGroup.Targets的每个target元素，把target和targetGroup的label都拿出来，传给populateLabels处理。populateLabels方法最终调用relabel.Process对label进行处理。因此relabel是对target本身的元数据进行处理的，没有对最终采集到的指标作处理。
// targetsFromGroup builds targets based on the given TargetGroup and config.
func targetsFromGroup(tg *targetgroup.Group, cfg *config.ScrapeConfig) ([]*Target, error) {
targets := make([]*Target, 0, len(tg.Targets))
for i, tlset := range tg.Targets {
lbls := make([]labels.Label, 0, len(tlset)+len(tg.Labels))
for ln, lv := range tlset {
lbls = append(lbls, labels.Label{Name: string(ln), Value: string(lv)})
}
for ln, lv := range tg.Labels {
if _, ok := tlset[ln]; !ok {
lbls = append(lbls, labels.Label{Name: string(ln), Value: string(lv)})
}
}
lset := labels.New(lbls...)
lbls, origLabels, err := populateLabels(lset, cfg)
}
...
}
// populateLabels builds a label set from the given label set and scrape configuration.
// It returns a label set before relabeling was applied as the second return value.
// Returns the original discovered label set found before relabelling was applied if the target is dropped during relabeling.
func populateLabels(lset labels.Labels, cfg *config.ScrapeConfig) (res, orig labels.Labels, err error) {
// Copy labels into the labelset for the target if they are not set already.
scrapeLabels := []labels.Label{
{Name: model.JobLabel, Value: cfg.JobName},
{Name: model.MetricsPathLabel, Value: cfg.MetricsPath},
{Name: model.SchemeLabel, Value: cfg.Scheme},
}
lb := labels.NewBuilder(lset)
...
preRelabelLabels := lb.Labels()
lset = relabel.Process(preRelabelLabels, cfg.RelabelConfigs...)
...
}
// Labels returns the labels from the builder. If no modifications
// were made, the original labels are returned.
func (b *Builder) Labels() Labels {
if len(b.del) == 0 && len(b.add) == 0 {
return b.base
}
// In the general case, labels are removed, modified or moved
// rather than added.
res := make(Labels, 0, len(b.base))
Outer:
for _, l := range b.base {
for _, n := range b.del {
if l.Name == n {
continue Outer
}
}
for _, la := range b.add {
if l.Name == la.Name {
continue Outer
}
}
res = append(res, l)
}
res = append(res, b.add...)
sort.Sort(res)
return res
}
metricRelabel的代码可以看到，这个配置被用于处理具体采集到的指标中含有的label。
具体流程是：reload方法读取了metricRelabelConfig配置（后买你简称为mrc），并通过newLoop创建loop，loop会创建scrapeLoop，scrapeLoop在append方法中接收到指标，并调用mrc配置处理label。
// reload the scrape pool with the given scrape configuration. The target state is preserved
// but all scrape loops are restarted with the new scrape configuration.
// This method returns after all scrape loops that were stopped have stopped scraping.
func (sp *scrapePool) reload(cfg *config.ScrapeConfig) error {
...
mrc = sp.config.MetricRelabelConfigs
...
for fp, oldLoop := range sp.loops {
var cache *scrapeCache
if oc := oldLoop.getCache(); reuseCache && oc != nil {
oldLoop.disableEndOfRunStalenessMarkers()
cache = oc
} else {
cache = newScrapeCache()
}
var (
newLoop = sp.newLoop(scrapeLoopOptions{
target: t,
scraper: s,
limit: limit,
honorLabels: honorLabels,
honorTimestamps: honorTimestamps,
mrc: mrc,
cache: cache,
})
)
...
}
func newScrapePool(cfg *config.ScrapeConfig, app storage.Appendable, jitterSeed uint64, logger log.Logger) (*scrapePool, error) {
sp.newLoop = func(opts scrapeLoopOptions) loop {
return newScrapeLoop(
ctx,
opts.scraper,
log.With(logger, "target", opts.target),
buffers,
func(l labels.Labels) labels.Labels {
return mutateSampleLabels(l, opts.target, opts.honorLabels, opts.mrc)
},
func(l labels.Labels) labels.Labels { return mutateReportSampleLabels(l, opts.target) },
func(ctx context.Context) storage.Appender { return appender(app.Appender(ctx), opts.limit) },
cache,
jitterSeed,
opts.honorTimestamps,
)
}
...
}
func newScrapeLoop(ctx context.Context,
sc scraper,
l log.Logger,
buffers *pool.Pool,
sampleMutator labelsMutator,
reportSampleMutator labelsMutator,
appender func(ctx context.Context) storage.Appender,
cache *scrapeCache,
jitterSeed uint64,
honorTimestamps bool,
) *scrapeLoop {
...
sl := &scrapeLoop{
scraper: sc,
buffers: buffers,
cache: cache,
appender: appender,
sampleMutator: sampleMutator,
reportSampleMutator: reportSampleMutator,
stopped: make(chan struct{}),
jitterSeed: jitterSeed,
l: l,
parentCtx: ctx,
honorTimestamps: honorTimestamps,
}
...
}
func (sl *scrapeLoop) append(app storage.Appender, b []byte, contentType string, ts time.Time) (total, added, seriesAdded int, err error) {
...
loop:
for {
var (
et textparse.Entry
sampleAdded bool
)
if et, err = p.Next(); err != nil {
if err == io.EOF {
err = nil
}
break
}
ce, ok := sl.cache.get(yoloString(met))
...
if !ok {
var lset labels.Labels
mets := p.Metric(&lset)
hash := lset.Hash()
// Hash label set as it is seen local to the target. Then add target labels
// and relabeling and store the final label set.
lset = sl.sampleMutator(lset)
}
...
}
...
}
小结：
通过以上分析可以确定，relabelConfig处理的是target本身的元数据，metricRelabelConfig处理的是采集到的指标中带有的label。