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Beginning of rewrite Petclinic
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‎content/en/other/wip/pet-clinic/2-zero-configuration.md‎ renamed to ‎content/en/other/wip/pet-clinic/10-preparation.md‎

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---
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title: Zero Configuration Auto Instrumentation for Java
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linkTitle: 2. Zero Configuration
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weight: 2
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title: Preparation of the Pet Clinic application.
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linkTitle: 1. Preparation
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weight: 10
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---
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## 1. Spring PetClinic Application
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## 1. Spring PetClinic Application build
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The first thing we need to set up APM is... well, an application. For this exercise, we will use the Spring PetClinic Microservices Application. This is a very popular sample Java application built with Spring framework (Springboot), using a Microservices Architecture.
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The first thing we need to set up is... well, an application. For this exercise, we will use the Spring PetClinic application. This is a very popular sample Java application built with the Spring framework (Springboot). We are using the Micro services version of it.
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First, clone the PetClinic GitHub repository, and then we will compile, build, package and test the application:
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First, clone the PetClinic GitHub repository, and then we will compile, build, package and containerize the application:
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```bash
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git clone https://github.com/hagen-p/spring-petclinic-microservices.git
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```
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<!--```bash
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git clone https://github.com/spring-projects/spring-petclinic
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```-->
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Change into the `spring-petclinic` directory <!--(and checkout a specific commit): -->
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Change into the `spring-petclinic` directory (and checkout a specific commit):
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```bash
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cd spring-petclinic
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cd spring-petclinic-microservices
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```
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<!--
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Start a MySQL database for PetClinic to use:
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```bash
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Next, we will start a Docker container running Locust that will generate some simple traffic to the PetClinic application. Locust is a simple load-testing tool that can be used to generate traffic to a web application.
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```bash
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docker run --network="host" -d -p 8090:8090 -v /home/ubuntu/workshop/petclinic:/mnt/locust docker.io/locustio/locust -f /mnt/locust/locustfile.py --headless -u 1 -r 1 -H http://127.0.0.1:8083
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docker run --network="host" -d -p 8090:8090 -v ~/workshop/petclinic:/mnt/locust docker.io/locustio/locust -f /mnt/locust/locustfile.py --headless -u 1 -r 1 -H http://127.0.0.1:8083
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```
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Next, run the `maven` command to compile/build/package PetClinic:
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-->
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Next, run the script that will use the `maven` command to compile/build/package the PetClinic Micro services into Docker containers:
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```bash
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./mvnw package -Dmaven.test.skip=true
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. ./scripts/build.sh
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```
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{{% notice style="info" %}}
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This will take a few minutes the first time you run, `maven` will download a lot of dependencies before it compiles the application. Future executions will be a lot quicker.
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This will take a few minutes the first time you run, `maven` will download a lot of dependencies before it compiles the application. Future builds will be a lot quicker.
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{{% /notice %}}
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Once the compilation is complete, you can run the application with the following command. Notice that we are passing the `mysql` profile to the application, this will tell the application to use the MySQL database we started earlier. We are also setting the `otel.service.name` to a logical service name that will also be used in the UI for filtering:
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## 2. Check Docker Images
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Once the build completes, you need to verify if the containers are indeed build:
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{{< tabs >}}
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{{% tab title="Check Docker Containers" %}}
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```bash
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docker images
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```
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{{% /tab %}}
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{{% tab title="Docker Output" %}}
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``` text
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splunk@show-no-config-i-027057abec7c0c6d3:~/spring-petclinic-microservices$ docker images
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REPOSITORY TAG IMAGE ID CREATED SIZE
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quay.io/phagen/spring-petclinic-api-gateway latest f954254824ed 7 seconds ago 510MB
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<none> <none> 5dbbb7d1fbb2 9 seconds ago 563MB
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quay.io/phagen/spring-petclinic-discovery-server latest 0761e73d679d 26 seconds ago 500MB
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<none> <none> d71dc0ff96f4 28 seconds ago 544MB
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quay.io/phagen/spring-petclinic-config-server latest 81a0ab6495c2 39 seconds ago 488MB
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<none> <none> 69d60a035bb9 40 seconds ago 519MB
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quay.io/phagen/spring-petclinic-visits-service latest ca306495bf11 50 seconds ago 526MB
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<none> <none> b60155eb8ab4 52 seconds ago 596MB
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quay.io/phagen/spring-petclinic-vets-service latest 29f1b1909b8b About a minute ago 527MB
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<none> <none> b07e8de54c99 About a minute ago 598MB
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quay.io/phagen/spring-petclinic-customers-service latest 5b21e448c91e About a minute ago 526MB
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<none> <none> 722fa001614c About a minute ago 596MB
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quay.io/phagen/spring-petclinic-admin-server latest 4a1906a91210 About a minute ago 498MB
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<none> <none> 96f61c7bb66a About a minute ago 540MB
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eclipse-temurin 17 807dd649ff14 13 days ago 407MB
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```
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{{% /tab %}}
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{{< /tabs >}}
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To test the application you need to obtain the public IP address of the instance you are running on. You can do this by running the following command:
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```bash
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curl ifconfig.me
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```
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You will see an IP address returned, make a note of this as we will need it to validate that the application is running.
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We also need to obtain the `INSTANCE` environment variable value, as this is what is being used as the `otel.service.name` attribute. You can do this by running the following command:
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```bash
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echo $INSTANCE
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```
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Also, make a note of this value as we will need it to filter the data in the UI.
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You can now run the application with the following command. Notice that we are passing the `mysql` profile to the application, this will tell the application to use the MySQL database we started earlier. We are also setting the `otel.service.name` to a logical service name that will also be used in the UI for filtering:
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```bash
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java \
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-jar target/spring-petclinic-*.jar --spring.profiles.active=mysql
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```
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You can validate if the application is running by visiting `http://<VM_IP_ADDRESS>:8083`.
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You can validate if the application is running by visiting `http://<IP_ADDRESS>:8083` (replace `<IP_ADDRESS>` with the IP address you obtained earlier). You should see the PetClinic application running.
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## 2. AlwaysOn Profiling and Metrics
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When we installed the collector we configured it to enable AlwaysOn Profiling and Metrics. This means that the collector will automatically generate CPU and Memory profiles for the application and send them to Splunk Observability Cloud.
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When we installed the collector we configured it to enable **AlwaysOn Profiling** and **Metrics**. This means that the collector will automatically generate CPU and Memory profiles for the application and send them to Splunk Observability Cloud.
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When you start the PetClinic application you will see the collector automatically detect the application and instrument it for traces and profiling.
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## 3. Review Profiling Data Collection
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You can now visit the Splunk APM UI and examine the application components, traces, profiling, DB Query performance and metrics. From the left-hand menu **APM** → Explore**, click the environment dropdown and select your environment (which is prefixed with the hostname of your instance).
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You can now visit the Splunk APM UI and examine the application components, traces, profiling, DB Query performance and metrics. From the left-hand menu **APM** → **Explore**, click the environment dropdown and select your environment e.g. `<INSTANCE>-petclinic` (where`<INSTANCE>` is replaced with the value you noted down earlier).
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![APM Environment](../images/apm-environment.png)
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Resource attributes can be added to every reported span. For example `version=0.314`. A comma-separated list of resource attributes can also be defined e.g. `key1=val1,key2=val2`.
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Let's launch the PetClinic again using a new resource attribute. Note, that adding resource attributes to the run command will override what was defined when we installed the collector. Let's add a new resource attribute `version=0.314`:
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Let's launch the PetClinic again using new resource attributes. Note, that adding resource attributes to the run command will override what was defined when we installed the collector. Let's add two new resource attributes `deployment.environment=$INSTANCE-petclinic-env,version=0.314`:
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```bash
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java \
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-Dserver.port=8083 \
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-Dotel.service.name=$INSTANCE-petclinic-service \
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-Dotel.resource.attributes=version=0.314 \
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-Dotel.resource.attributes=deployment.environment=$INSTANCE-petclinic-env,version=0.314 \
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-jar target/spring-petclinic-*.jar --spring.profiles.active=mysql
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```
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‎content/en/other/wip/pet-clinic/1-otel-collector.md‎ renamed to ‎content/en/other/wip/pet-clinic/20-otel-collector.md‎

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---
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title: Installing the OpenTelemetry Collector
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linkTitle: 1. OpenTelemetry Collector
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weight: 1
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linkTitle: 2. OpenTelemetry Collector
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weight: 20
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---
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## 1. Introduction
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The OpenTelemetry Collector is the core component of instrumenting infrastructure and applications. Its role is to collect and send:
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The Splunk OpenTelemetry Collector is the core component of instrumenting infrastructure and applications. Its role is to collect and send:
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* Infrastructure metrics (disk, cpu, memory, etc)
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* Infrastructure metrics (disk, CPU, memory, etc)
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* Application Performance Monitoring (APM) traces
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* Profiling data
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* Host and application logs
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Splunk Observability Cloud offers a wizard to walk you through the setup of the Collector on both your infrastructure and applications.
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{{% notice title="Delete any existing OpenTelemetry Collectors" style="warning" %}}
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If you have completed the Splunk IM workshop, please ensure you have deleted the collector running in Kubernetes before continuing. This can be done by running the following command:
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If you have completed a Splunk Observability workshop using this EC2 instance, please ensure you have deleted the collector running in Kubernetes before continuing. This can be done by running the following command:
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``` bash
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helm delete splunk-otel-collector
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ACCESS_TOKEN
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REALM
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RUM_TOKEN
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HEC_TOKEN
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HEC_URL
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```
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For this workshop, **all** of the above are required. If any are missing, please contact your instructor.
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* `--enable-profiler` - Enables the profiler for the Java application. This will generate CPU profiles for the application.
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* `--enable-profiler-memory` - Enables the profiler for the Java application. This will generate memory profiles for the application.
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* `--enable-metrics` - Enables the exporting of Micrometer metrics
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* `--hec-token` - Sets the HEC token for the collector to use
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* `--hec-url` - Sets the HEC URL for the collector to use
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``` bash
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curl -sSL https://dl.signalfx.com/splunk-otel-collector.sh > /tmp/splunk-otel-collector.sh && \
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sudo sh /tmp/splunk-otel-collector.sh --realm $REALM -- $ACCESS_TOKEN --mode agent --without-fluentd --with-instrumentation --deployment-environment $INSTANCE-petclinic --enable-profiler --enable-profiler-memory --enable-metrics
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sudo sh /tmp/splunk-otel-collector.sh --realm $REALM -- $ACCESS_TOKEN --mode agent --without-fluentd --with-instrumentation --deployment-environment $INSTANCE-petclinic --enable-profiler --enable-profiler-memory --enable-metrics --hec-token $HEC_TOKEN --hec-url $HEC_URL
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{{% notice style="info" title="AWS/EC2 instances" %}}
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If you are attempting this workshop on an AWS/EC2 instance you will have to patch the collector to expose the hostname of the instance:
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When prompted to restart services, select 'OK' and press enter.
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Next, we will patch the collector to expose the hostname of the instance and not the AWS instance ID. This will make it easier to filter data in the UI. Run the following command to patch the collector:
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``` bash
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{{% /notice %}}
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Once the installation is completed, you can navigate to the **Hosts with agent installed** dashboard to see the data from your host, **Dashboards → Hosts with agent installed**.
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Use the dashboard filter and select `host.name` and type or select the hostname of your virtual machine. Once you see data flowing for your host, we are then ready to get started with the APM component.
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Use the dashboard filter and select `host.name` and type or select the hostname of your workshop instance (you can get this from the command prompt in your terminal session). Once you see data flowing for your host, we are then ready to get started with the APM component.

‎content/en/other/wip/pet-clinic/3-rum.md‎

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‎content/en/other/wip/pet-clinic/30-rum.md‎

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---
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title: Real User Monitoring
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linkTitle: 4. Real User Monitoring
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weight: 40
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---
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## 1. Enable RUM
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For the Real User Monitoring (RUM) instrumentation, we will add the Open Telemetry Javascript [**https://github.com/signalfx/splunk-otel-js-web**](https://github.com/signalfx/splunk-otel-js-web) snippet in the pages, we will use the wizard again **Data Management → Add Integration → RUM Instrumentation → Browser Instrumentation**.
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Your instructor will inform you which token to use from the dropdown, click **Next**. Enter **App name** and **Environment** using the following syntax:
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- `<INSTANCE>-petclinic-service` - replacing `<INSTANCE>` with the value you noted down earlier.
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- `<INSTANCE>-petclinic-env` - replacing `<INSTANCE>` with the value you noted down earlier.
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The wizard will then show a snippet of HTML code that needs to be placed at the top of the pages in the `<head>` section. The following is an example of the (do not use this snippet, use the one generated by the wizard):
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``` html
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/*
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IMPORTANT: Replace the <version> placeholder in the src URL with a
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version from https://github.com/signalfx/splunk-otel-js-web/releases
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*/
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<script src="https://cdn.signalfx.com/o11y-gdi-rum/latest/splunk-otel-web.js" crossorigin="anonymous"></script>
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<script>
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SplunkRum.init({
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realm: "eu0",
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rumAccessToken: "<redacted>",
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applicationName: "petclinic-1be0-petclinic-service",
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deploymentEnvironment: "petclinic-1be0-petclinic-env"
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});
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</script>
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```
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The Spring PetClinic application uses a single HTML page as the "layout" page, that is reused across all pages of the application. This is the perfect location to insert the Splunk RUM Instrumentation Library as it will be loaded in all pages automatically.
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Let's then edit the layout page:
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```bash
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vi src/main/resources/templates/fragments/layout.html
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```
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Next, insert the snippet we generated above in the `<head>` section of the page. Make sure you don't include the comment and replace `<version>` in the source URL to `latest` e.g.
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```html
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<!doctype html>
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<html th:fragment="layout (template, menu)">
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<head>
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<script src="https://cdn.signalfx.com/o11y-gdi-rum/latest/splunk-otel-web.js" crossorigin="anonymous"></script>
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<script>
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SplunkRum.init({
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realm: "eu0",
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rumAccessToken: "<redacted>",
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applicationName: "petclinic-1be0-petclinic-service",
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deploymentEnvironment: "petclinic-1be0-petclinic-env"
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});
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</script>
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...
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```
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## 2. Rebuild PetClinic
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With the code changes complete, we need to rebuild the application and run it again. Run the `maven` command to compile/build/package PetClinic:
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```bash
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./mvnw package -Dmaven.test.skip=true
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```
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```bash
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java \
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-Dserver.port=8083 \
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-Dotel.service.name=$INSTANCE-petclinic-service \
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-Dotel.resource.attributes=deployment.environment=$INSTANCE-petclinic-env,version=0.314 \
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-jar target/spring-petclinic-*.jar --spring.profiles.active=mysql
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```
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Then let's visit the application using a browser to generate real-user traffic `http://<IP_ADDRESS>:8083`.
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In RUM, filter down into the environment as defined in the RUM snippet above and click through to the dashboard.
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When you drill down into a RUM trace you will see a link to APM in the spans. Clicking on the trace ID will take you to the corresponding APM trace for the current RUM trace.

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