This repository has an application example to demonstrate 3 different ways of instrumenting a service, all 3 services are instrumented to produce Traces, Metrics and Logs:
- Temperature Simulator is instrumented using manual instrumentation.
- Data Processing is instrumented using instrumentation libraries.
- Temperature Calculator is instrumented using auto-instrumentation (OTel Java agent) and manual instrumentation.
graph LR
TempSimulator(Temperature<br/>Simulator):::java
DataProcessing(Data<br/>Processing):::rust
TempCalculator(Temperature<br/>Calculator):::java
Internet --HTTP--> TempSimulator
TempSimulator --HTTP--> DataProcessing
DataProcessing --HTTP--> TempCalculator
classDef java fill:#f34b7d,color:white;
classDef rust fill:#535454,color:white;
-
Navigate to the
.envfile and add your Datadog credentials:- eg:
DD_SITE=datadoghq.eu DD_API_KEY=1abc2def3ghi4xxx567
-
From the root folder, run:
docker compose up -d
-
Send some requests to the application. This can be done in 2 different ways:
-
curlthesimulateTemperatureendpoint:curl "localhost:8080/simulateTemperature?measurements=5&location=New%20York" -
Call the
traffic.shscript, which simulates a traffic of 1-10 requests per minute../traffic.sh
-
You can check the full Collector configuration in the
otelcol-config.yml file.
graph TD
TempSimulator(Temperature<br/>Simulator):::java
DataProcessing(Data<br/>Processing):::rust
TempCalculator(Temperature<br/>Calculator):::java
otelcol(OpenTelemetry<br/>Collector):::otelcol
datadog(Datadog):::datadog
TempCalculator --OTLP/gRPC--> otelcol
TempSimulator --OTLP/gRPC--> otelcol
DataProcessing --OTLP/gRPC--> otelcol
otelcol --> datadog
classDef java fill:#f34b7d,color:white;
classDef rust fill:#535454,color:white;
classDef otelcol fill:#426feb,color:white;
classDef datadog fill:#632CA6,color:white;
