prometheus 中 remote-write 和 remote-read 的配置:
# store data to influxdb
remote_write:
- url: "http://10.21.1.74:8086/api/v1/prom/write?db=prometheus"
# read data from influxdb
remote_read:
- url: "http://10.21.1.74:8086/api/v1/prom/read?db=prometheus"
remote-read 能够让 prometheus 读取近程存储上的时序数据,扩大了本地存储。
prometheus 在应答 /query 查问申请时,由 fanoutStorage 解决;
- fanoutStorage 蕴含 localStorage(本地 TSDB) 和 remoteStorage(近程存储),它们均实现了查问接口;
- localStorage 执行本地查问;
- remoteStorage 通过 HTTP 执行近程查问;
- 将上述 2 个查问后果进行合并,返回给 client;
demo 演示
- prometheus 配置 remote-write 和 remote-read;
- 运行一段时间后:
进行 prometheus: stop prometheus;
删除本地数据:delete prometheus/data 目录;
启动 prometheus: start promethesu;
上述操作模仿:本地存储宕机,应用近程存储的场景。
- 在 prometheus UI 上执行查问,能够失去历史数据 (近程存储);
remote-read 的代码
执行近程查问的入口代码:生成 query,而后发送 HTTP 近程查问
// storage/remote/read.go
func (q *querier) Select(sortSeries bool, hints *storage.SelectHints, matchers ...*labels.Matcher) storage.SeriesSet {if len(q.requiredMatchers) > 0 {requiredMatchers := append([]*labels.Matcher{}, q.requiredMatchers...)
for _, m := range matchers {
for i, r := range requiredMatchers {
if m.Type == labels.MatchEqual && m.Name == r.Name && m.Value == r.Value {
// Requirement matched.
requiredMatchers = append(requiredMatchers[:i], requiredMatchers[i+1:]...)
break
}
}
}
}
// 加 label
m, added := q.addExternalLabels(matchers)
// 生成查问
query, err := ToQuery(q.mint, q.maxt, m, hints)
// HTTP client 发动近程查问
res, err := q.client.Read(q.ctx, query)
return newSeriesSetFilter(FromQueryResult(sortSeries, res), added)
}
client 对象的结构:每个 remote 有一个 client,应用其配置的 URL/HttpConfig 结构
//storage/remote/storage.go
func (s *Storage) ApplyConfig(conf *config.Config) error {
for _, rrConf := range conf.RemoteReadConfigs {
c, err := newReadClient(name, &ClientConfig{
URL: rrConf.URL,
Timeout: rrConf.RemoteTimeout,
HTTPClientConfig: rrConf.HTTPClientConfig,
})
queryables = append(queryables, NewSampleAndChunkQueryableClient(
c,
conf.GlobalConfig.ExternalLabels,
labelsToEqualityMatchers(rrConf.RequiredMatchers),
rrConf.ReadRecent,
s.localStartTimeCallback,
))
......
}
......
}
发动 HTTP 近程查问申请:
- HTTP request:先用 protobuf 序列化,再用 snappy 压缩;
- HTTP response: 先用 snappy 解压缩,而后再用 protobuf 反序列化;
//storage/remote/client.go
// Read reads from a remote endpoint.
func (c *client) Read(ctx context.Context, query *prompb.Query) (*prompb.QueryResult, error) {
req := &prompb.ReadRequest{Queries: []*prompb.Query{query,},
}
// protobuf 序列化
data, err := proto.Marshal(req)
// snappy 压缩
compressed := snappy.Encode(nil, data)
// 发送 HTTP POST
httpReq, err := http.NewRequest("POST", c.url.String(), bytes.NewReader(compressed))
httpReq.Header.Add("Content-Encoding", "snappy")
httpReq.Header.Add("Accept-Encoding", "snappy")
httpReq.Header.Set("Content-Type", "application/x-protobuf")
httpReq.Header.Set("User-Agent", userAgent)
httpReq.Header.Set("X-Prometheus-Remote-Read-Version", "0.1.0")
ctx, cancel := context.WithTimeout(ctx, c.timeout)
defer cancel()
httpReq = httpReq.WithContext(ctx)
// 发送 request
httpResp, err := c.client.Do(httpReq)
compressed, err = ioutil.ReadAll(httpResp.Body)
// 返回的后果,先 snappy 解压缩
uncompressed, err := snappy.Decode(nil, compressed)
var resp prompb.ReadResponse
// 再 protobuf 反序列化
err = proto.Unmarshal(uncompressed, &resp)
return resp.Results[0], nil
}
参考:
1.https://yunlzheng.gitbook.io/…