Deploying on Hosts¶

Installing DataKit Agent¶

Before performing system and application link analysis, you need to deploy the TrueWatch DataKit collector on each target host to collect the necessary link data.

Enabling the DDTrace Collector¶

DDTrace is used to receive, process, and analyze Tracing protocol data. Execute the following command to enable the DDTrace collector. For other third-party Tracing collector configurations, refer to Integrations.

cp /usr/local/datakit/conf.d/ddtrace/ddtrace.conf.sample /usr/local/datakit/conf.d/ddtrace/ddtrace.conf

After configuration, restart DataKit:

datakit service -R

Selecting a Language¶

Java¶

Install dependencies:

wget -O dd-java-agent.jar 'https://static.truewatch.com/dd-image/dd-java-agent.jar'

Run the application:

You can run your Java Code through various methods such as IDE, Maven, Gradle, or directly via the java -jar command. Below is an example using the java command to start the application:

java \ 
    -javaagent:/path/to/dd-java-agent.jar \ 
    -Ddd.logs.injection=true \ 
    -Ddd.agent.host=<YOUR-DATAKIT-HOST> \ 
    -Ddd.trace.agent.port=9529 \ 
    -jar path/to/your/app.jar

Parameter Configuration:

1. service.name: Service name;
2. env: Environment information of the application service;
3. version: Version number;
4. Set sampling rate: Enabling this can reduce the actual data volume generated; the range is from 0.0 (0%) to 1.0 (100%);
5. Collect Profiling data: Enabling this allows you to see more runtime information of the application;
6. Enable JVM metrics collection: Requires simultaneous enabling of the statsd collector.

For more parameter configurations, refer to here.

Python¶

Install dependencies:

pip install ddtrace

Run the application:

You can run your Java Code through various methods such as IDE, Maven, Gradle, or directly via the java -jar command. Below is an example using the java command to start the application:

DD_LOGS_INJECTION=true \ 
DD_AGENT_HOST=localhost \ 
DD_AGENT_PORT=9529 \ 
ddtrace-run python my_app.py

Parameter Configuration:

1. service.name: Service name;
2. env: Environment information of the application service;
3. version: Version number;
4. Set sampling rate: Enabling this can reduce the actual data volume generated; the range is from 0.0 (0%) to 1.0 (100%);
5. Collect Profiling data: Enabling this allows you to see more runtime information of the application;
6. Enable Python metrics collection: Requires simultaneous enabling of the statsd collector.

For more parameter configurations, refer to here.

Golang¶

Install dependencies:

go get gopkg.in/DataDog/dd-trace-go.v1/ddtrace/tracer

Run the application:

You can run your Java Code through various methods such as IDE, Maven, Gradle, or directly via the java -jar command. Below is an example using the java command to start the application:

package main 

import ( 
   "io/ioutil" 
   "os" 
   "time" 
   httptrace "gopkg.in/DataDog/dd-trace-go.v1/contrib/net/http" 
   "gopkg.in/DataDog/dd-trace-go.v1/ddtrace/tracer" 
) 

func main() { 
  tracer.Start( 
  ) 
  defer tracer.Stop() 
  // Create a traced mux router
  mux := httptrace.NewServeMux()
  // Continue using the router as you normally would.
  mux.HandleFunc("/", func(w http.ResponseWriter, r *http.Request) {
    time.Sleep(time.Second)
    w.Write([]byte("Hello World!"))
  })
  if err := http.ListenAndServe(":18080", mux); err != nil {
    log.Fatal(err)
  }
}

Parameter Configuration:

1. service.name: Service name;
2. env: Environment information of the application service;
3. version: Version number;
4. Set sampling rate: Enabling this can reduce the actual data volume generated; the range is from 0.0 (0%) to 1.0 (100%);
5. Collect Profiling data: Enabling this allows you to see more runtime information of the application.

For more parameter configurations, refer to here.

Node.JS¶

C++¶

PHP¶