https://github.com/francoposa/echo-server-rust-logging-metrics-tracing
Echo Server Demonstrating a Fully Instrumented Rust Backend Application
https://github.com/francoposa/echo-server-rust-logging-metrics-tracing
Last synced: 4 months ago
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Echo Server Demonstrating a Fully Instrumented Rust Backend Application
- Host: GitHub
- URL: https://github.com/francoposa/echo-server-rust-logging-metrics-tracing
- Owner: francoposa
- License: mit
- Created: 2022-07-19T16:42:06.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2024-12-01T18:48:02.000Z (7 months ago)
- Last Synced: 2025-03-19T05:33:38.860Z (4 months ago)
- Language: Rust
- Homepage:
- Size: 76.2 KB
- Stars: 5
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# echo-server-rust-logging-tracing-metrics
## Configuration
### Server Configuration
* `SERVER_ADDR` - server bind address in `host:port` format; defaults to `0.0.0.0:8080`.
* `BASE_URL_PATH` - URL path prefix to be applied to all public API endpoints; defaults to `/api/v0`
### OTEL Instrumentation Official Configuration
OpenTelemetry library configuration is done with the standardized environment variables listed here
[here](https://opentelemetry.io/docs/concepts/sdk-configuration/) and
[here] (https://opentelemetry.io/docs/specs/otel/configuration/sdk-environment-variables/).
Of particular interest are:
* `OTEL_EXPORTER_OTLP_ENDPOINT` - this server currently only exports via gRPC.
The RPC exporter endpoint defaults to `http://localhost:4317`.
Endpoints can also be configured separately for metrics and (logs + traces) via
`OTEL_EXPORTER_OTLP_METRICS_ENDPOINT` and `OTEL_EXPORTER_OTLP_TRACES_ENDPOINT`.
* `OTEL_METRIC_EXPORT_INTERVAL` - this defaults to 60000 (60 seconds), but I set it to 10000 or 15000 (10 or 15
seconds).
I primarily export metrics to Mimir/Prometheus/Grafana where I want to evaluate or graph the metrics rate on
one-minute intervals.
The rule of thumb for Prometheus-compatible tooling seems to be an
[evaluation range >= 4x the scrape interval](https://www.robustperception.io/what-range-should-i-use-with-rate/).
### Additional Configuration
I have also added the options to enable or disable stdout and OTLP exporting for each of logs, metrics, and traces.
* `STD_STREAM_LOGS_EXPORTER_ENABLED`: default `false`
* `STD_STREAM_METRICS_EXPORTER_ENABLED`: default `false`
* `STD_STREAM_TRACES_EXPORTER_ENABLED`: default `false`
* `OTEL_COLLECTOR_LOGS_EXPORTER_ENABLED`: default `true`
* `OTEL_COLLECTOR_TRACES_EXPORTER_ENABLED`: default `true`
* `OTEL_COLLECTOR_METRICS_EXPORTER_ENABLED`: default `true`
Environment variable names and defaults subject to change.
The stdout exporter prints the telemetry signals to the console
in the same human-readable format as the OTEL Collector's debug exporter
It is intended only for debugging and development purposes only.
## Usage
### Docker Compose
#### Echo Server
In the `development` directory, bring up the echo server with:
```shell
docker-compose up -d echo-server # add the --build option to include any local changes
```
The Docker Compose configuration binds the container port to the host network's port 8080.
Hit either the vanilla echo endpoint at `localhost:8080` or the json echo endpoint at `localhost:8080/json`:
```shell
curl -i -X GET localhost:8080/api/v0/echo -d 'hello world'
curl -i -X GET --header "content-type: application/json" localhost:8080/api/v0/echo/json -d '{"hello": "world"}'
```
#### Telemetry Collectors
Only use one of the two collectors for the telemetry data, either the OTEL Collector or Grafana Agent:
```shell
docker-compose up -d otel-collector
# or
docker-compose up -d grafana-agent
```
For now, the pre-set-up configuration options are more limited for the Grafana Agent.
#### Ingesting And Visualizing Metrics:
The Docker Compose setup uses Grafana's Mimir metrics database in monolithic mode to ingest metrics,
and Grafana (the visualization application itself) to query and graph the data.
Querying may also be done via HTTP calls to Mimir's Prometheus query endpoints.
```shell
docker compose up -d mimir grafana
```
Access the Grafana UI at `localhost:3000/explore` and view the metrics with a PromQL query:
```PromQL
rate(http_server_request_duration_count[1m])
```
#### Ingesting and Visualizing Traces
The easiest way to view traces is with the Jaeger all-in-one docker image.
Jaeger added support for OpenTelemetry-formatted traces in v1.35
```shell
docker run -d --name jaeger \
-e COLLECTOR_OTLP_ENABLED=true \
-p 16686:16686 \
-p 4317:4317 \
-p 4318:4318 \
jaegertracing/all-in-one:1.35
```
Then access the Jaeger UI at http://localhost:16686.
The echo server service will appear once traces have been produced.
Make individual requests to the server or use the load gen scripts and container to create activity on the server.
Trace spans do not link together much at this point - I believe this is due to the lack of tracing support thus far in
Hyper.
## Development
Compiling outside of Docker requires protobuf compiler packages to be installed on the operating system.
The packages are generally called `protobuf`, `protobuf-devel`, or similar in Linux repos
---
Created by Franco Posa (franco @ [francoposa.io](https://francoposa.io))