916ec63af6
This is a new revision of the discovery server. Relevant changes and non-changes: - Protocol towards clients is unchanged. - Recommended large scale design is still to be deployed nehind nginx (I tested, and it's still a lot faster at terminating TLS). - Database backend is leveldb again, only. It scales enough, is easy to setup, and we don't need any backend to take care of. - Server supports replication. This is a simple TCP channel - protect it with a firewall when deploying over the internet. (We deploy this within the same datacenter, and with firewall.) Any incoming client announces are sent over the replication channel(s) to other peer discosrvs. Incoming replication changes are applied to the database as if they came from clients, but without the TLS/certificate overhead. - Metrics are exposed using the prometheus library, when enabled. - The database values and replication protocol is protobuf, because JSON was quite CPU intensive when I tried that and benchmarked it. - The "Retry-After" value for failed lookups gets slowly increased from a default of 120 seconds, by 5 seconds for each failed lookup, independently by each discosrv. This lowers the query load over time for clients that are never seen. The Retry-After maxes out at 3600 after a couple of weeks of this increase. The number of failed lookups is stored in the database, now and then (avoiding making each lookup a database put). All in all this means clients can be pointed towards a cluster using just multiple A / AAAA records to gain both load sharing and redundancy (if one is down, clients will talk to the remaining ones). GitHub-Pull-Request: https://github.com/syncthing/syncthing/pull/4648
104 lines
2.8 KiB
Go
104 lines
2.8 KiB
Go
// Copyright 2013 The Prometheus Authors
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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package model
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import (
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"fmt"
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"regexp"
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"sort"
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"strings"
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)
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var (
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separator = []byte{0}
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// MetricNameRE is a regular expression matching valid metric
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// names. Note that the IsValidMetricName function performs the same
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// check but faster than a match with this regular expression.
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MetricNameRE = regexp.MustCompile(`^[a-zA-Z_:][a-zA-Z0-9_:]*$`)
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)
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// A Metric is similar to a LabelSet, but the key difference is that a Metric is
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// a singleton and refers to one and only one stream of samples.
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type Metric LabelSet
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// Equal compares the metrics.
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func (m Metric) Equal(o Metric) bool {
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return LabelSet(m).Equal(LabelSet(o))
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}
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// Before compares the metrics' underlying label sets.
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func (m Metric) Before(o Metric) bool {
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return LabelSet(m).Before(LabelSet(o))
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}
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// Clone returns a copy of the Metric.
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func (m Metric) Clone() Metric {
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clone := make(Metric, len(m))
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for k, v := range m {
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clone[k] = v
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}
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return clone
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}
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func (m Metric) String() string {
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metricName, hasName := m[MetricNameLabel]
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numLabels := len(m) - 1
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if !hasName {
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numLabels = len(m)
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}
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labelStrings := make([]string, 0, numLabels)
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for label, value := range m {
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if label != MetricNameLabel {
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labelStrings = append(labelStrings, fmt.Sprintf("%s=%q", label, value))
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}
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}
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switch numLabels {
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case 0:
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if hasName {
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return string(metricName)
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}
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return "{}"
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default:
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sort.Strings(labelStrings)
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return fmt.Sprintf("%s{%s}", metricName, strings.Join(labelStrings, ", "))
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}
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}
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// Fingerprint returns a Metric's Fingerprint.
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func (m Metric) Fingerprint() Fingerprint {
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return LabelSet(m).Fingerprint()
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}
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// FastFingerprint returns a Metric's Fingerprint calculated by a faster hashing
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// algorithm, which is, however, more susceptible to hash collisions.
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func (m Metric) FastFingerprint() Fingerprint {
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return LabelSet(m).FastFingerprint()
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}
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// IsValidMetricName returns true iff name matches the pattern of MetricNameRE.
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// This function, however, does not use MetricNameRE for the check but a much
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// faster hardcoded implementation.
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func IsValidMetricName(n LabelValue) bool {
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if len(n) == 0 {
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return false
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}
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for i, b := range n {
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if !((b >= 'a' && b <= 'z') || (b >= 'A' && b <= 'Z') || b == '_' || b == ':' || (b >= '0' && b <= '9' && i > 0)) {
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return false
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}
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}
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return true
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}
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