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Add directions to enable Java profiling. (#171)
Signed-off-by: Hannah Troisi <htroisi@pixielabs.ai>
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content/en/04-tutorials/01-pixie-101/06-profiler.md

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This tutorial will demonstrate how to use Pixie's Always-On Profiling feature to investigate a spike in CPU utilization, using a flamegraph to identify a performance issue within the application code.
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Pixie's profiling feature currently supports Go, C++, and Rust. Other language support coming soon.
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Pixie's continuous profiler currently supports Go, C++, and Rust. Java support is a beta feature and must be [manually enabled](#prerequisites-enabling-java-support). Other language support coming soon.
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<YouTube youTubeId="Zr-s3EvAey8"/>
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## Prerequisites
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You will need a Kubernetes cluster with Pixie installed. If you do not have a cluster, you can create a minikube cluster and install Pixie using one of our [install guides](/installing-pixie/install-guides/).
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### Enabling Java Support
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Java support is a beta feature and must be manually enabled during the deployment of Pixie.
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To enable Java support when deploying Pixie with the [Pixie CLI](/installing-pixie/install-schemes/cli/), run:
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```
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px deploy --pem_flags=PL_PROFILER_JAVA_SYMBOLS=1
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```
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To enable Java support when deploying Pixie with [Helm](/installing-pixie/install-schemes/helm/), run:
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```
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helm install pixie pixie-operator/pixie-operator-chart --set deployKey=<deploy-key-goes-here> --set clusterName=<cluster-name> --namespace pl --create-namespace --set dataCollectorParams.customPEMFlags.PL_PROFILER_JAVA_SYMBOLS=true
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```
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## Setup
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We are going to be working with GCP's [Online Boutique](https://github.com/GoogleCloudPlatform/microservices-demo), a microservices demo application for a web-based e-commerce app where users can browse and purchase items.

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