1 | # Exporting Metrics and Traces with OpenCensus, Zipkin, and Prometheus |
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2 | |
3 | This tutorial provides a minimum example to verify that metrics and traces |
4 | can be exported to OpenCensus from Go tools. |
5 | |
6 | ## Setting up oragent |
7 | |
8 | 1. Ensure you have [docker](https://www.docker.com/get-started) and [docker-compose](https://docs.docker.com/compose/install/). |
9 | 2. Clone [oragent](https://github.com/orijtech/oragent). |
10 | 3. In the oragent directory, start the services: |
11 | ```bash |
12 | docker-compose up |
13 | ``` |
14 | If everything goes well, you should see output resembling the following: |
15 | ``` |
16 | Starting oragent_zipkin_1 ... done |
17 | Starting oragent_oragent_1 ... done |
18 | Starting oragent_prometheus_1 ... done |
19 | ... |
20 | ``` |
21 | * You can check the status of the OpenCensus agent using zPages at http://localhost:55679/debug/tracez. |
22 | * You can now access the Prometheus UI at http://localhost:9445. |
23 | * You can now access the Zipkin UI at http://localhost:9444. |
24 | 4. To shut down oragent, hit Ctrl+C in the terminal. |
25 | 5. You can also start oragent in detached mode by running `docker-compose up -d`. To stop oragent while detached, run `docker-compose down`. |
26 | |
27 | ## Exporting Metrics and Traces |
28 | 1. Clone the [tools](https://golang.org/x/tools) subrepository. |
29 | 1. Inside `internal`, create a file named `main.go` with the following contents: |
30 | ```go |
31 | package main |
32 | |
33 | import ( |
34 | "context" |
35 | "fmt" |
36 | "math/rand" |
37 | "net/http" |
38 | "time" |
39 | |
40 | "golang.org/x/tools/internal/event" |
41 | "golang.org/x/tools/internal/event/export" |
42 | "golang.org/x/tools/internal/event/export/metric" |
43 | "golang.org/x/tools/internal/event/export/ocagent" |
44 | ) |
45 | |
46 | type testExporter struct { |
47 | metrics metric.Exporter |
48 | ocagent *ocagent.Exporter |
49 | } |
50 | |
51 | func (e *testExporter) ProcessEvent(ctx context.Context, ev event.Event) (context.Context, event.Event) { |
52 | ctx, ev = export.Tag(ctx, ev) |
53 | ctx, ev = export.ContextSpan(ctx, ev) |
54 | ctx, ev = e.metrics.ProcessEvent(ctx, ev) |
55 | ctx, ev = e.ocagent.ProcessEvent(ctx, ev) |
56 | return ctx, ev |
57 | } |
58 | |
59 | func main() { |
60 | exporter := &testExporter{} |
61 | |
62 | exporter.ocagent = ocagent.Connect(&ocagent.Config{ |
63 | Start: time.Now(), |
64 | Address: "http://127.0.0.1:55678", |
65 | Service: "go-tools-test", |
66 | Rate: 5 * time.Second, |
67 | Client: &http.Client{}, |
68 | }) |
69 | event.SetExporter(exporter) |
70 | |
71 | ctx := context.TODO() |
72 | mLatency := event.NewFloat64Key("latency", "the latency in milliseconds") |
73 | distribution := metric.HistogramFloat64Data{ |
74 | Info: &metric.HistogramFloat64{ |
75 | Name: "latencyDistribution", |
76 | Description: "the various latencies", |
77 | Buckets: []float64{0, 10, 50, 100, 200, 400, 800, 1000, 1400, 2000, 5000, 10000, 15000}, |
78 | }, |
79 | } |
80 | |
81 | distribution.Info.Record(&exporter.metrics, mLatency) |
82 | |
83 | for { |
84 | sleep := randomSleep() |
85 | _, end := event.StartSpan(ctx, "main.randomSleep()") |
86 | time.Sleep(time.Duration(sleep) * time.Millisecond) |
87 | end() |
88 | event.Record(ctx, mLatency.Of(float64(sleep))) |
89 | |
90 | fmt.Println("Latency: ", float64(sleep)) |
91 | } |
92 | } |
93 | |
94 | func randomSleep() int64 { |
95 | var max int64 |
96 | switch modulus := time.Now().Unix() % 5; modulus { |
97 | case 0: |
98 | max = 17001 |
99 | case 1: |
100 | max = 8007 |
101 | case 2: |
102 | max = 917 |
103 | case 3: |
104 | max = 87 |
105 | case 4: |
106 | max = 1173 |
107 | } |
108 | return rand.Int63n(max) |
109 | } |
110 | |
111 | ``` |
112 | 3. Run the new file from within the tools repository: |
113 | ```bash |
114 | go run internal/main.go |
115 | ``` |
116 | 4. After about 5 seconds, OpenCensus should start receiving your new metrics, which you can see at http://localhost:8844/metrics. This page will look similar to the following: |
117 | ``` |
118 | # HELP promdemo_latencyDistribution the various latencies |
119 | # TYPE promdemo_latencyDistribution histogram |
120 | promdemo_latencyDistribution_bucket{vendor="otc",le="0"} 0 |
121 | promdemo_latencyDistribution_bucket{vendor="otc",le="10"} 2 |
122 | promdemo_latencyDistribution_bucket{vendor="otc",le="50"} 9 |
123 | promdemo_latencyDistribution_bucket{vendor="otc",le="100"} 22 |
124 | promdemo_latencyDistribution_bucket{vendor="otc",le="200"} 35 |
125 | promdemo_latencyDistribution_bucket{vendor="otc",le="400"} 49 |
126 | promdemo_latencyDistribution_bucket{vendor="otc",le="800"} 63 |
127 | promdemo_latencyDistribution_bucket{vendor="otc",le="1000"} 78 |
128 | promdemo_latencyDistribution_bucket{vendor="otc",le="1400"} 93 |
129 | promdemo_latencyDistribution_bucket{vendor="otc",le="2000"} 108 |
130 | promdemo_latencyDistribution_bucket{vendor="otc",le="5000"} 123 |
131 | promdemo_latencyDistribution_bucket{vendor="otc",le="10000"} 138 |
132 | promdemo_latencyDistribution_bucket{vendor="otc",le="15000"} 153 |
133 | promdemo_latencyDistribution_bucket{vendor="otc",le="+Inf"} 15 |
134 | promdemo_latencyDistribution_sum{vendor="otc"} 1641 |
135 | promdemo_latencyDistribution_count{vendor="otc"} 15 |
136 | ``` |
137 | 5. After a few more seconds, Prometheus should start displaying your new metrics. You can view the distribution at http://localhost:9445/graph?g0.range_input=5m&g0.stacked=1&g0.expr=rate(oragent_latencyDistribution_bucket%5B5m%5D)&g0.tab=0. |
138 | |
139 | 6. Zipkin should also start displaying traces. You can view them at http://localhost:9444/zipkin/?limit=10&lookback=300000&serviceName=go-tools-test. |
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