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230 lines
9.3 KiB
Markdown
230 lines
9.3 KiB
Markdown
# OpenTelemetry
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Requirements:
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- docker-compose
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## Prepare setup
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Create a `docker-compose.yaml` and `otel-collector-config.yml` file as seen below in a folder.
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```yaml title="docker-compose.yaml"
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version: '3'
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services:
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# Jaeger
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jaeger:
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image: jaegertracing/all-in-one:1.61.0
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ports:
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- '16686:16686'
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- '4317'
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otel-collector:
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image: otel/opentelemetry-collector-contrib:0.109.0
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command: ['--config=/etc/otel-collector-config.yml']
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volumes:
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- ./otel-collector-config.yml:/etc/otel-collector-config.yml
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ports:
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- '1888:1888' # pprof extension
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- '13133:13133' # health_check extension
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- '55679:55679' # zpages extension
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- '4318:4318' # OTLP HTTP
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- '4317:4317' # OTLP GRPC
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- '9123:9123' # Prometheus exporter
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depends_on:
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- jaeger
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```
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```yaml title="otel-collector-config.yml"
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receivers:
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otlp:
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protocols:
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grpc:
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http:
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exporters:
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otlp/jaeger:
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endpoint: jaeger:4317
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tls:
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insecure: true
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logging:
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prometheus:
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endpoint: '0.0.0.0:9123'
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processors:
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batch:
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spanmetrics:
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metrics_exporter: prometheus
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latency_histogram_buckets: [10ms, 100ms, 250ms, 1s, 30s, 1m, 5m]
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dimensions:
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- name: http.method
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- name: http.status_code
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- name: http.host
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dimensions_cache_size: 1000
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aggregation_temporality: 'AGGREGATION_TEMPORALITY_CUMULATIVE'
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extensions:
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health_check:
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pprof:
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zpages:
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service:
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extensions: [pprof, zpages, health_check]
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pipelines:
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traces:
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receivers: [otlp]
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exporters: [otlp/jaeger, logging]
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processors: [spanmetrics, batch]
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metrics:
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receivers: [otlp]
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exporters: [prometheus]
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```
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Start setup using this command inside the folder containing the files created in the earlier steps:
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```
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docker-compose up
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```
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This command will start an [OpenTelemetry Collector](https://github.com/open-telemetry/opentelemetry-collector-contrib) and an instance of [Jaeger](https://www.jaegertracing.io/).
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Jaeger will be now reachable under [http://localhost:16686](http://localhost:16686).
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## Run Renovate with OpenTelemetry
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To start Renovate with OpenTelemetry enabled run following command, after pointing to your `config.js` config file:
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```
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docker run \
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--rm \
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-e OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4318 \
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-v "/path/to/your/config.js:/usr/src/app/config.js" \
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renovate/renovate:latest
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```
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You should now see `trace_id` and `span_id` fields in the logs.
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```
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INFO: Repository finished (repository=org/example)
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"durationMs": 5574,
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"trace_id": "f9a4c33852333fc2a0fbdc163100c987",
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"span_id": "4ac1323eeaee
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```
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### Traces
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Open now Jaeger under [http://localhost:16686](http://localhost:16686).
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You should now be able to pick `renovate` under in the field `service` field.
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Select `Find Traces` to search for all Renovate traces and then select one of the found traces to open the trace view.
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You should be able to see now the full trace view which shows each HTTP request and internal spans.
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### Metrics
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Additional to the received traces some metrics are calculated.
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This is achieved using the [spanmetricsprocessor](https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/processor/spanmetricsprocessor).
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The previous implemented setup will produce following metrics, which are exposed under [http://localhost:9123/metrics](http://localhost:9123/metrics):
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```
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# HELP calls_total
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# TYPE calls_total counter
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### Example of internal spans
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calls_total{operation="renovate repository",service_name="renovate",span_kind="SPAN_KIND_INTERNAL",status_code="STATUS_CODE_UNSET"} 3
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calls_total{operation="run",service_name="renovate",span_kind="SPAN_KIND_INTERNAL",status_code="STATUS_CODE_UNSET"} 1
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### Example of http calls from Renovate to external services
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calls_total{http_host="api.github.com:443",http_method="POST",http_status_code="200",operation="HTTPS POST",service_name="renovate",span_kind="SPAN_KIND_CLIENT",status_code="STATUS_CODE_UNSET"} 9
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...
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# HELP latency
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# TYPE latency histogram
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### Example of internal spans
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latency_bucket{operation="renovate repository",service_name="renovate",span_kind="SPAN_KIND_INTERNAL",status_code="STATUS_CODE_UNSET",le="0.1"} 0
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...
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latency_bucket{operation="renovate repository",service_name="renovate",span_kind="SPAN_KIND_INTERNAL",status_code="STATUS_CODE_UNSET",le="9.223372036854775e+12"} 3
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latency_bucket{operation="renovate repository",service_name="renovate",span_kind="SPAN_KIND_INTERNAL",status_code="STATUS_CODE_UNSET",le="+Inf"} 3
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latency_sum{operation="renovate repository",service_name="renovate",span_kind="SPAN_KIND_INTERNAL",status_code="STATUS_CODE_UNSET"} 30947.4689
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latency_count{operation="renovate repository",service_name="renovate",span_kind="SPAN_KIND_INTERNAL",status_code="STATUS_CODE_UNSET"} 3
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...
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### Example of http calls from Renovate to external services
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latency_bucket{http_host="api.github.com:443",http_method="POST",http_status_code="200",operation="HTTPS POST",service_name="renovate",span_kind="SPAN_KIND_CLIENT",status_code="STATUS_CODE_UNSET",le="0.1"} 0
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...
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latency_bucket{http_host="api.github.com:443",http_method="POST",http_status_code="200",operation="HTTPS POST",service_name="renovate",span_kind="SPAN_KIND_CLIENT",status_code="STATUS_CODE_UNSET",le="250"} 3
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latency_bucket{http_host="api.github.com:443",http_method="POST",http_status_code="200",operation="HTTPS POST",service_name="renovate",span_kind="SPAN_KIND_CLIENT",status_code="STATUS_CODE_UNSET",le="9.223372036854775e+12"} 9
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latency_bucket{http_host="api.github.com:443",http_method="POST",http_status_code="200",operation="HTTPS POST",service_name="renovate",span_kind="SPAN_KIND_CLIENT",status_code="STATUS_CODE_UNSET",le="+Inf"} 9
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latency_sum{http_host="api.github.com:443",http_method="POST",http_status_code="200",operation="HTTPS POST",service_name="renovate",span_kind="SPAN_KIND_CLIENT",status_code="STATUS_CODE_UNSET"} 2306.1385999999998
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latency_count{http_host="api.github.com:443",http_method="POST",http_status_code="200",operation="HTTPS POST",service_name="renovate",span_kind="SPAN_KIND_CLIENT",status_code="STATUS_CODE_UNSET"} 9
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```
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The [spanmetricsprocessor](https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/processor/spanmetricsprocessor) creates two sets of metrics.
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#### Calls metric
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At first there are the `calls_total` metrics which display how often specific trace spans have been observed.
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For example:
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`calls_total{operation="renovate repository",service_name="renovate",span_kind="SPAN_KIND_INTERNAL",status_code="STATUS_CODE_UNSET"} 3` signals that 3 repositories have been renovated.
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`calls_total{operation="run",service_name="renovate",span_kind="SPAN_KIND_INTERNAL",status_code="STATUS_CODE_UNSET"} 1` represents how often Renovate has been run.
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If we combine this using the PrometheusQueryLanguage ( PromQL ), we can calculate the average count of repositories each Renovate run handles.
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```
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calls_total{operation="renovate repository",service_name="renovate"} / calls_total{operation="run",service_name="renovate"}
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```
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This metrics is also for spans generated by http calls:
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```yaml
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calls_total{http_host="registry.terraform.io:443",http_method="GET",http_status_code="200",operation="HTTPS GET",service_name="renovate",span_kind="SPAN_KIND_CLIENT",status_code="STATUS_CODE_UNSET"} 5
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```
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#### Latency buckets
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The second class of metrics exposed are the latency focused latency buckets which allow to create [heatmaps](https://grafana.com/docs/grafana/latest/basics/intro-histograms/#heatmaps).
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A request is added to a backed if the latency is bigger than the bucket value (`le`). `request_duration => le`
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As an example if we receive a request which need `1.533s` to complete get following metrics:
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```
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latency_bucket{http_host="api.github.com:443",le="0.1"} 0
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latency_bucket{http_host="api.github.com:443",le="1"} 0
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latency_bucket{http_host="api.github.com:443",le="2"} 1
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latency_bucket{http_host="api.github.com:443",le="6"} 1
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latency_bucket{http_host="api.github.com:443",le="10"} 1
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latency_bucket{http_host="api.github.com:443",le="100"} 1
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latency_bucket{http_host="api.github.com:443",le="250"} 1
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latency_bucket{http_host="api.github.com:443",le="9.223372036854775e+12"} 1
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latency_bucket{http_host="api.github.com:443",le="+Inf"} 1
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latency_sum{http_host="api.github.com:443"} 1.533
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latency_count{http_host="api.github.com:443"} 1
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```
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Now we have another request which this time takes 10s to complete:
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```
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latency_bucket{http_host="api.github.com:443",le="0.1"} 0
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latency_bucket{http_host="api.github.com:443",le="1"} 0
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latency_bucket{http_host="api.github.com:443",le="2"} 1
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latency_bucket{http_host="api.github.com:443",le="6"} 1
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latency_bucket{http_host="api.github.com:443",le="10"} 2
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latency_bucket{http_host="api.github.com:443",le="100"} 2
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latency_bucket{http_host="api.github.com:443",le="250"} 2
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latency_bucket{http_host="api.github.com:443",le="9.223372036854775e+12"} 2
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latency_bucket{http_host="api.github.com:443",le="+Inf"} 2
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latency_sum{http_host="api.github.com:443"} 11.533
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latency_count{http_host="api.github.com:443"} 2
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```
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More about the functionality can be found on the Prometheus page for [metric types](https://prometheus.io/docs/concepts/metric_types/#histogram).
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