> ## Documentation Index
> Fetch the complete documentation index at: https://odigos-core-000-verify-using-k3d-instead-of-kind.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Introduction

In this tutorial we are going to use Odigos for generating distributed traces for a microservices-based application written in Go, Java, Python, .NET and Node.js.

We are going to deploy the application in a Kubernetes cluster and use [Jaeger](https://www.jaegertracing.io/) as the backend for storing and visualizing the traces.

<Info>
  This guide is designed for:

  * IT professionals with experience in system administration or DevOps
  * Software engineers familiar with containerization and Kubernetes concepts
  * Anyone comfortable with command-line interfaces and basic cloud infrastructure

  If you're new to these concepts or prefer a more detailed, step-by-step approach, we recommend starting with our [Beginner's Guide to Odigos Installation](../quickstart/installation-guide-for-beginners).
</Info>

## Preparing the environment

### Creating a Kubernetes cluster

This first step is to create a Kubernetes cluster.
We recommend using [k3d](https://k3d.io/) or [minikube](https://minikube.sigs.k8s.io/docs/) for trying Odigos out in a local environment.

<Warning>
  **Mac users**: please avoid using Docker Desktop built-in Kubernetes cluster as it [does not](https://docs.docker.com/storage/bind-mounts/#configure-bind-propagation) support bind propagation. Use k3d (or minikube) on top of Docker Desktop / OrbStack / Colima instead — eBPF instrumentation runs inside the Linux node containers.
</Warning>

Create a new local Kubernetes cluster, by running the following command:

<Tabs>
  <Tab title="k3d">
    ```bash theme={null}
    k3d cluster create odigos
    ```
  </Tab>

  <Tab title="Minikube">
    ```bash theme={null}
    minikube start
    ```
  </Tab>
</Tabs>

### Deploying the target application

We are going to install a [demo application](https://github.com/odigos-io/simple-demo) that consists of 6 microservices written in Java, Go, Python, Node.js, .NET and PHP.

<Frame>
  <img src="https://mintcdn.com/odigos-core-000-verify-using-k3d-instead-of-kind/pzR26NsfSmc-4iDB/images/demo_architecture.png?fit=max&auto=format&n=pzR26NsfSmc-4iDB&q=85&s=66ca9356b4f91504ce74d2a76a7182ed" alt="Architecture of demo application" width="4079" height="2541" data-path="images/demo_architecture.png" />
</Frame>

Deploy the application using the following command:

```bash theme={null}
kubectl apply -f https://raw.githubusercontent.com/odigos-io/simple-demo/main/kubernetes/deployment.yaml
```

### Deploying Jaeger

Jaeger is a popular open source distributed tracing backend. We are going to use it for storing and visualizing the traces generated by Odigos.

Install Jaeger using the following command:

```bash theme={null}
kubectl apply -f https://raw.githubusercontent.com/odigos-io/simple-demo/main/kubernetes/jaeger.yaml
```

### Waiting for the applications to start

Before moving to the next step, make sure that the application pods and Jaeger pods are running, this may take a few minutes.

```bash theme={null}
kubectl wait --for=condition=available --timeout=300s deployment --all --all-namespaces
```

<Frame>
  <img src="https://mintcdn.com/odigos-core-000-verify-using-k3d-instead-of-kind/pzR26NsfSmc-4iDB/images/pods_ready.png?fit=max&auto=format&n=pzR26NsfSmc-4iDB&q=85&s=3ba436fa8cb0c903921db6a0e9c79c5d" alt="Deployments Ready" width="1890" height="728" data-path="images/pods_ready.png" />
</Frame>