# Tag: Introductory

## Learning paths

- [Build a ROS 2 and Zenoh simulation environment on an Arm server](https://learn.arm.com/learning-paths/cross-platform/ros2-zenoh-arm/)
- [Explore Arm Memory Tagging Extension with an example C program](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/mte/)
- [Profile Android game performance in Godot with Arm Performance Studio](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/godot_packages/)
- [Enable hardware ray tracing on Lumen for Android devices](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/how-to-enable-hwrt-on-lumen-for-android-devices/)
- [Generate neural graphics datasets with Neural Graphics Data Capture in Unreal Engine](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/neural-graphics-data-capture-unreal/)
- [Enable Neural Super Sampling in Unreal Engine with ML Extensions](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/nss-unreal/)
- [Enable Memory Tagging Extension on Google Pixel 8](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/mte_on_pixel8/)
- [Arm Neural Technology Playbook - Evaluate](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/neural-graphics-playbook-evaluate/)
- [Query Arm GPU configuration information](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/libgpuinfo/)
- [Get started with Unity on Android](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/get-started-with-unity-on-android/)
- [Enable Neural Frame Rate Upscaling in Unreal Engine](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/nfru-unreal/)
- [Optimize a sample C++ application on an Arm-based server with Arm Performix](https://learn.arm.com/learning-paths/servers-and-cloud-computing/performix-get-started/)
- [Get started with the Raspberry Pi 4](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/rpi/)
- [Run the Zephyr RTOS on Arm Corstone-300](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/zephyr/)
- [Run Llama 3 on a Raspberry Pi 5 using ExecuTorch](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/rpi-llama3/)
- [Port Zephyr RTOS and run applications on the Arm Corstone-320 MPS4 platform](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/zephyr_cs320_mps4/)
- [Get started with Yocto Linux on Qemu](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/yocto_qemu/)
- [Build Zephyr projects with Workbench for Zephyr in VS Code](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/zephyr_vsworkbench/)
- [Visualize Ethos-U NPU performance with ExecuTorch on Arm FVPs](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/visualizing-ethos-u-performance/)
- [Run a computer vision model on a Himax microcontroller](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/yolo-on-himax/)
- [Get started with TrustZone on NXP LPCXpresso55S69](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/trustzone_nxp_lpc/)
- [Get started with Trusted Firmware-M](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/tfm/)
- [Get started with Raspberry Pi Pico](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/rpi_pico/)
- [Edge AI on Arm: PyTorch and ExecuTorch rock-paper-scissors](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/training-inference-pytorch/)
- [Create an interactive shell for Zephyr RTOS on Arm Cortex-M](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/zephyr_shell/)
- [Build a Universal Single Board Computer Rack Mount System](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/universal-sbc-chassis/)
- [Build and run the Arm Machine Learning Evaluation Kit examples](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/mlek/)
- [Build a Privacy-First LLM Smart Home on Raspberry Pi 5](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/raspberry-pi-smart-home/)
- [Deploy multi-network device meshes using Device Connect server and NATS](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/device-connect-server/)
- [Use Linux on the NXP FRDM i.MX 93 board](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/linux-nxp-board/)
- [Prepare Docker image for Arm embedded development](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/docker/)
- [Learn how to deploy Envoy](https://learn.arm.com/learning-paths/servers-and-cloud-computing/envoy/)
- [Get started with Keil Studio Cloud](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/keilstudiocloud/)
- [Deploy Envoy Proxy on Google Cloud C4A (Arm-based Axion VMs)](https://learn.arm.com/learning-paths/servers-and-cloud-computing/envoy-gcp/)
- [Debug Trusted Firmware-A and the Linux kernel on Arm FVP with Arm Development Studio](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/linux-on-fvp/)
- [Run a local LLM chatbot on a Raspberry Pi 5](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/llama-python-cpu/)
- [Learn how to run AI on Edge devices using Arduino Nano RP2040](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/edge/)
- [Introduction to TinyML on Arm using PyTorch and ExecuTorch](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/introduction-to-tinyml-on-arm/)
- [Get started with object detection using a Jetson Orin Nano](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/jetson_object_detection/)
- [Deploy ExecuTorch firmware on NXP FRDM i.MX 93 for Ethos-U65 acceleration](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/observing-ethos-u-on-nxp/)
- [Create a ChatGPT voice bot on a Raspberry Pi](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/raspberry_pi_chatgpt_bot/)
- [Add new debug targets to Arm Development Studio](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/new_debug_targets_armds/)
- [Get started with Microcontrollers](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/intro/)
- [Deploy Elasticsearch on Azure Cobalt 100 Arm virtual machines](https://learn.arm.com/learning-paths/servers-and-cloud-computing/elasticsearch-on-azure/)
- [Analyze a frame from an Android application with Frame Advisor](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/analyze_a_frame_with_frame_advisor/)
- [Sampling CPython with WindowsPerf](https://learn.arm.com/learning-paths/laptops-and-desktops/windowsperf_sampling_cpython/)
- [Implement CI/CD with Windows on Arm host](https://learn.arm.com/learning-paths/laptops-and-desktops/windows_cicd_github/)
- [Get started with the Windows Performance Analyzer plugin for WindowsPerf](https://learn.arm.com/learning-paths/laptops-and-desktops/windowsperf_wpa_plugin/)
- [Develop desktop applications with Windows Forms on Windows on Arm](https://learn.arm.com/learning-paths/laptops-and-desktops/win_forms/)
- [Automate Windows on Arm virtual machine deployment with QEMU and KVM on Arm Linux](https://learn.arm.com/learning-paths/laptops-and-desktops/win11-vm-automation/)
- [Port the Win32 library to Arm64](https://learn.arm.com/learning-paths/laptops-and-desktops/win_win32_dll_porting/)
- [Measure application resource and power usage on Windows on Arm with FFmpeg and PowerShell](https://learn.arm.com/learning-paths/laptops-and-desktops/win-resource-ps1/)
- [Develop Windows applications with WinUI3 on Windows on Arm](https://learn.arm.com/learning-paths/laptops-and-desktops/win_winui3/)
- [Deploy GitHub Actions workflows using Windows Sandbox](https://learn.arm.com/learning-paths/laptops-and-desktops/win_sandbox_dot_net_cicd/)
- [Create OpenCV applications on Windows on Arm](https://learn.arm.com/learning-paths/laptops-and-desktops/win-opencv/)
- [Analyze performance data with the Visual Studio extension for WindowsPerf](https://learn.arm.com/learning-paths/laptops-and-desktops/windowsperf-vs-extension/)
- [Port Code to Arm Scalable Vector Extension (SVE)](https://learn.arm.com/learning-paths/servers-and-cloud-computing/sve/)
- [Optimize C++ performance with Profile-Guided Optimization and Google Benchmark](https://learn.arm.com/learning-paths/servers-and-cloud-computing/cpp-profile-guided-optimisation/)
- [Optimize application performance using Arm Performix CPU microarchitecture analysis](https://learn.arm.com/learning-paths/servers-and-cloud-computing/performix-microarchitecture/)
- [Optimize AArch64 binaries with LLVM BOLT](https://learn.arm.com/learning-paths/servers-and-cloud-computing/bolt/)
- [Learn about optimization techniques using the g++ compiler](https://learn.arm.com/learning-paths/servers-and-cloud-computing/cplusplus_compilers_flags/)
- [Learn about Large System Extensions (LSE)](https://learn.arm.com/learning-paths/servers-and-cloud-computing/lse/)
- [Enable Arm SPE for Performix memory access analysis](https://learn.arm.com/learning-paths/servers-and-cloud-computing/spe-on-performix/)
- [Develop desktop applications with Chromium Embedded Framework on Windows on Arm](https://learn.arm.com/learning-paths/laptops-and-desktops/win_cef/)
- [Build a Windows on Arm native application with .NET](https://learn.arm.com/learning-paths/laptops-and-desktops/win_net/)
- [Build .NET MAUI Applications on Arm64](https://learn.arm.com/learning-paths/laptops-and-desktops/win_net_maui/)
- [Optimize Windows applications using Arm Performance Libraries](https://learn.arm.com/learning-paths/laptops-and-desktops/windows_armpl/)
- [Optimize C++ applications on Windows on Arm using profile-guided optimization](https://learn.arm.com/learning-paths/laptops-and-desktops/win_profile_guided_optimisation/)
- [Get started with WindowsPerf](https://learn.arm.com/learning-paths/laptops-and-desktops/windowsperf/)
- [Develop cross-platform applications with Xamarin Forms on Windows on Arm](https://learn.arm.com/learning-paths/laptops-and-desktops/win_xamarin_forms/)
- [Develop applications with Windows Presentation Foundation (WPF) on Windows on Arm](https://learn.arm.com/learning-paths/laptops-and-desktops/win_wpf/)
- [Build native Windows on Arm applications with Python](https://learn.arm.com/learning-paths/laptops-and-desktops/win_python/)
- [Benchmarking .NET 8 applications on Windows on Arm](https://learn.arm.com/learning-paths/laptops-and-desktops/win_net8/)
- [Get started with Laptops and Desktops](https://learn.arm.com/learning-paths/laptops-and-desktops/intro/)
- [Optimize AArch64 code with LLVM link-time optimization and profile-guided optimization](https://learn.arm.com/learning-paths/servers-and-cloud-computing/pgo/)
- [Run MNIST on an Alif E8 Ensemble DevKit using ExecuTorch and Ethos-U85](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/observing-ethos-u-on-alif/)
- [Accelerate Denoising, Background Blur and Low-Light Camera Effects with SME2](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/ai-camera-pipelines/)
- [Sample Instructions with WindowsPerf and Arm SPE](https://learn.arm.com/learning-paths/cross-platform/windowsperf_sampling_cpython_spe/)
- [Deploy a Windows on Arm virtual machine on Microsoft Azure](https://learn.arm.com/learning-paths/cross-platform/woa_azure/)
- [Profile an Android application with Arm Performance Studio](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/ams/)
- [Optimize hardware ray tracing with Lumen on Android devices](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/best-practices-for-hwrt-lumen-performance/)
- [Get started with Scalable Vector Extension 2 on Android](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/android_sve2/)
- [Detect faces with OpenCV on Android Devices](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/android_opencv_facedetection/)
- [Build a customer support chatbot on Android with Llama and ExecuTorch](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/customer-support-chatbot-with-llama-and-executorch-on-arm-based-mobile-devices/)
- [Add an LLM to your Android app with Arm's AI Chat library](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/android-ai-chat-lib/)
- [Optimize image processing on Android using Halide](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/android_halide/)
- [Create Computer Vision Applications with OpenCV on Android Devices](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/android_opencv_camera/)
- [Build an Android chat app with Llama, KleidiAI, ExecuTorch, and XNNPACK](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/build-llama3-chat-android-app-using-executorch-and-xnnpack/)
- [Accelerate an OpenCV-based Android Application with KleidiCV](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/android_opencv_kleidicv/)
- [Build and deploy multi-node Zenoh systems on Raspberry Pi](https://learn.arm.com/learning-paths/cross-platform/zenoh-multinode-ros2/)
- [Run Java applications on Google Axion processors](https://learn.arm.com/learning-paths/servers-and-cloud-computing/java-on-axion/)
- [Profile Unity application performance on Android devices](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/profiling-unity-apps-on-android/)
- [Install a Unity Game on a single board computer (Orange Pi 5)](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/unity_on_orange_pi/)
- [Build an on-device AI fitness tutor app on Android](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/ai-plank-tutor/)
- [Deploy an MCP Server on Raspberry Pi 5 for AI agent interaction using OpenAI SDK](https://learn.arm.com/learning-paths/cross-platform/mcp-ai-agent/)
- [Build an embedded application with Rust and debug with Arm Development Studio](https://learn.arm.com/learning-paths/cross-platform/rust_armds/)
- [Optimize an Adler-32 checksum function with SVE intrinsics using the Arm MCP server](https://learn.arm.com/learning-paths/servers-and-cloud-computing/adler32-kiro/)
- [Deploy containerized workloads to Arm-based Linux targets with Topo](https://learn.arm.com/learning-paths/cross-platform/deploy-containerized-workloads-with-topo/)
- [Use LLVM Machine Code Analyzer to analyze assembly performance on Arm](https://learn.arm.com/learning-paths/cross-platform/mca-godbolt/)
- [Run custom software for simulation with Arm IP Explorer](https://learn.arm.com/learning-paths/cross-platform/ipexplorer/)
- [Access remote devices with Remote.It](https://learn.arm.com/learning-paths/cross-platform/remoteit/)
- [Accelerate Generative AI workloads using KleidiAI](https://learn.arm.com/learning-paths/cross-platform/kleidiai-explainer/)
- [Run and benchmark BitNet-2B inference on Arm CPUs with Litespark-Inference](https://learn.arm.com/learning-paths/cross-platform/litespark-inference/)
- [Validate PAC/BTI security features in OpenJDK on Google Cloud C4A](https://learn.arm.com/learning-paths/servers-and-cloud-computing/openjdk-pacbti-gcp/)
- [Use OpenEBS for Kubernetes-native persistent storage on Azure Cobalt 100-based Arm64 virtual machines](https://learn.arm.com/learning-paths/servers-and-cloud-computing/openebs-cobalt/)
- [Use Longhorn to deploy persistent storage for Kubernetes workloads on Arm-based Azure virtual machines](https://learn.arm.com/learning-paths/servers-and-cloud-computing/longhorn-cobalt/)
- [Use Keras Core with TensorFlow, PyTorch, and JAX backends](https://learn.arm.com/learning-paths/servers-and-cloud-computing/keras-core/)
- [Use Infrastructure as Code and Pulumi to provision Azure resources](https://learn.arm.com/learning-paths/servers-and-cloud-computing/from-iot-to-the-cloud-part4/)
- [Tune the Performance of the Java Garbage Collector](https://learn.arm.com/learning-paths/servers-and-cloud-computing/java-gc-tuning/)
- [Train and deploy XGBoost models on Google Cloud C4A Axion VM](https://learn.arm.com/learning-paths/servers-and-cloud-computing/xgboost-on-axion/)
- [Train and benchmark AI workloads with DeepSpeed on Google Cloud C4A Axion VMs](https://learn.arm.com/learning-paths/servers-and-cloud-computing/deepspeed-on-axion/)
- [Scan multi-architecture containers with Trivy on Azure Cobalt 100](https://learn.arm.com/learning-paths/servers-and-cloud-computing/trivy-on-gcpp/)
- [Scale AI workloads with Ray on Google Cloud C4A Axion VM](https://learn.arm.com/learning-paths/servers-and-cloud-computing/ray-on-axion/)
- [Run x265 (H.265 codec) on Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/codec/)
- [Run vLLM inference with INT4 quantization on Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/vllm-acceleration/)
- [Run the vvenc H.266 encoder on Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/vvenc/)
- [Run Text Classification with ThirdAI on Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/thirdai-sentiment-analysis/)
- [Run MongoDB on Arm-based Azure Cobalt 100 instances](https://learn.arm.com/learning-paths/servers-and-cloud-computing/mongodb-on-azure/)
- [Run memcached on Arm servers and measure its performance](https://learn.arm.com/learning-paths/servers-and-cloud-computing/memcached/)
- [Run distributed inference with llama.cpp on Arm-based AWS Graviton4 instances](https://learn.arm.com/learning-paths/servers-and-cloud-computing/distributed-inference-with-llama-cpp/)
- [Run CircleCI Arm Native Workflows on a SUSE Arm GCP VM](https://learn.arm.com/learning-paths/servers-and-cloud-computing/circleci-gcp/)
- [Run an LLM chatbot with rtp-llm on Arm-based servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/rtp-llm/)
- [Run a Natural Language Processing (NLP) model from Hugging Face on Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/nlp-hugging-face/)
- [Run a Large Language Model (LLM) chatbot with PyTorch using KleidiAI on Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/pytorch-llama/)
- [Run a .NET Aspire application on Arm-based VMs on AWS and GCP](https://learn.arm.com/learning-paths/servers-and-cloud-computing/net-aspire/)
- [Optimize the performance of Snort 3 using multithreading](https://learn.arm.com/learning-paths/servers-and-cloud-computing/snort3-multithreading/)
- [Optimize exponential functions with FEXPA](https://learn.arm.com/learning-paths/servers-and-cloud-computing/fexpa/)
- [Monitor Azure Cobalt 100 Arm64 virtual machines using Dynatrace OneAgent](https://learn.arm.com/learning-paths/servers-and-cloud-computing/dynatrace-azure/)
- [Migrating applications to Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/migration/)
- [Migrate MySQL from on-premises x64 to Azure Cobalt 100 Arm VMs](https://learn.arm.com/learning-paths/servers-and-cloud-computing/mysql-lns-azure/)
- [Migrate containers to Arm using KubeArchInspect](https://learn.arm.com/learning-paths/servers-and-cloud-computing/kubearchinspect/)
- [Migrate applications that leverage performance libraries](https://learn.arm.com/learning-paths/servers-and-cloud-computing/using-and-porting-performance-libs/)
- [Microbenchmark storage performance with fio on Arm](https://learn.arm.com/learning-paths/servers-and-cloud-computing/disk-io-benchmark/)
- [Microbenchmark and tune network performance with iPerf3 and Linux traffic control](https://learn.arm.com/learning-paths/servers-and-cloud-computing/microbenchmark-network-iperf3/)
- [Measure performance of compression libraries on Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/snappy/)
- [Measure performance of ClickHouse on Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/clickhouse/)
- [Measure Machine Learning Inference Performance on Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/ml-perf/)
- [Measure and modify Go garbage collection behavior on AWS Graviton-based compute](https://learn.arm.com/learning-paths/servers-and-cloud-computing/go-gc-default-settings/)
- [Measure and accelerate PyTorch Inference on Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/torchbench/)
- [Managed, self-hosted Arm runners for GitHub Actions](https://learn.arm.com/learning-paths/servers-and-cloud-computing/github-actions-runner/)
- [Manage the ML lifecycle with MLflow on Google Cloud C4A Axion VM](https://learn.arm.com/learning-paths/servers-and-cloud-computing/mlflow-axion/)
- [Learn how to deploy Spark on AWS Graviton2](https://learn.arm.com/learning-paths/servers-and-cloud-computing/spark/)
- [Learn how to deploy PostgreSQL](https://learn.arm.com/learning-paths/servers-and-cloud-computing/postgresql/)
- [Learn how to deploy Nginx](https://learn.arm.com/learning-paths/servers-and-cloud-computing/nginx/)
- [Learn how to deploy MySQL](https://learn.arm.com/learning-paths/servers-and-cloud-computing/mysql/)
- [Learn how to deploy AWS Lambda functions](https://learn.arm.com/learning-paths/servers-and-cloud-computing/lambda_functions/)
- [Learn how to deploy a Django application](https://learn.arm.com/learning-paths/servers-and-cloud-computing/django/)
- [Install Vectorscan (Hyperscan on Arm) and use it with Snort 3](https://learn.arm.com/learning-paths/servers-and-cloud-computing/vectorscan/)
- [Install and validate Helm on Google Cloud C4A Arm-based VMs](https://learn.arm.com/learning-paths/servers-and-cloud-computing/helm-on-gcp/)
- [How to use AWS Graviton processors on AWS Fargate with Copilot](https://learn.arm.com/learning-paths/servers-and-cloud-computing/aws-copilot/)
- [Get started with Arm-based cloud instances](https://learn.arm.com/learning-paths/servers-and-cloud-computing/csp/)
- [Get ready for performance analysis with Sysreport](https://learn.arm.com/learning-paths/servers-and-cloud-computing/sysreport/)
- [Deploy WordPress with MySQL on Arm-based instances using Amazon EKS](https://learn.arm.com/learning-paths/servers-and-cloud-computing/eks/)
- [Deploy TypeScript on Google Cloud C4A virtual machines](https://learn.arm.com/learning-paths/servers-and-cloud-computing/typescript-on-gcp/)
- [Deploy TensorFlow on Google Cloud C4A (Arm-based Axion VMs)](https://learn.arm.com/learning-paths/servers-and-cloud-computing/tensorflow-gcp/)
- [Deploy SqueezeNet 1.0 INT8 model with ONNX Runtime on Azure Cobalt 100](https://learn.arm.com/learning-paths/servers-and-cloud-computing/onnx-on-azure/)
- [Deploy Rust on Google Cloud C4A (Arm-based Axion VMs)](https://learn.arm.com/learning-paths/servers-and-cloud-computing/rust-on-gcp/)
- [Deploy Ruby on Rails on Arm-based Google Cloud C4A virtual machines](https://learn.arm.com/learning-paths/servers-and-cloud-computing/ruby-on-rails/)
- [Deploy Redis on Azure Cobalt 100 Arm64 virtual machines for real-time messaging and event processing](https://learn.arm.com/learning-paths/servers-and-cloud-computing/redis-cobalt/)
- [Deploy Redis on Arm](https://learn.arm.com/learning-paths/servers-and-cloud-computing/redis/)
- [Deploy Redis for data searching on Google Cloud C4A](https://learn.arm.com/learning-paths/servers-and-cloud-computing/redis-data-searching/)
- [Deploy RabbitMQ on Arm64 Cloud Platforms (Azure and GCP)](https://learn.arm.com/learning-paths/servers-and-cloud-computing/rabbitmq-gcp/)
- [Deploy Puppet on Google Cloud C4A](https://learn.arm.com/learning-paths/servers-and-cloud-computing/puppet-on-gcp/)
- [Deploy PostgreSQL on Azure Cobalt 100 Arm64 virtual machines](https://learn.arm.com/learning-paths/servers-and-cloud-computing/postgresql-cobalt/)
- [Deploy PHP on Google Cloud C4A Arm-based Axion VMs](https://learn.arm.com/learning-paths/servers-and-cloud-computing/php-on-gcp/)
- [Deploy OpenTelemetry on Google Cloud C4A Axion processors](https://learn.arm.com/learning-paths/servers-and-cloud-computing/opentelemetry/)
- [Deploy OpenStack on Azure Cobalt 100 Arm64 Virtual Machine](https://learn.arm.com/learning-paths/servers-and-cloud-computing/openstack-on-azure/)
- [Deploy Node.js on Google Cloud C4A Arm-based Axion VMs](https://learn.arm.com/learning-paths/servers-and-cloud-computing/node-js-gcp/)
- [Deploy NGINX on Azure Cobalt 100 Arm-based virtual machines](https://learn.arm.com/learning-paths/servers-and-cloud-computing/nginx-on-azure/)
- [Deploy MySQL on Microsoft Azure Cobalt 100 processors](https://learn.arm.com/learning-paths/servers-and-cloud-computing/mysql-azure/)
- [Deploy MySQL and WordPress on an always free tier Arm shape](https://learn.arm.com/learning-paths/servers-and-cloud-computing/wordpress/)
- [Deploy MongoDB on an Arm-based Google Axion C4A VM](https://learn.arm.com/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/)
- [Deploy ModelScope FunASR Model on Arm Servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/funasr/)
- [Deploy MinIO on Azure Cobalt 100](https://learn.arm.com/learning-paths/servers-and-cloud-computing/minio-cobalt/)
- [Deploy MariaDB on Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/mariadb/)
- [Deploy Keycloak on Azure Cobalt 100-based Arm64 virtual machines for identity and access management](https://learn.arm.com/learning-paths/servers-and-cloud-computing/keycloak-cobalt/)
- [Deploy Java applications on Azure Cobalt 100 processors](https://learn.arm.com/learning-paths/servers-and-cloud-computing/java-on-azure/)
- [Deploy High-Performance Analytics with Apache Arrow and Arrow Flight on Google Cloud C4A Axion processors](https://learn.arm.com/learning-paths/servers-and-cloud-computing/apache_arrow_and_flight/)
- [Deploy Golang on Azure Cobalt 100 on Arm](https://learn.arm.com/learning-paths/servers-and-cloud-computing/golang-on-azure/)
- [Deploy GitHub Actions Self-Hosted Runner on Google Axion C4A virtual machine](https://learn.arm.com/learning-paths/servers-and-cloud-computing/github-on-arm/)
- [Deploy Gerrit on a Google Cloud C4A instance](https://learn.arm.com/learning-paths/servers-and-cloud-computing/gerrit-on-gcp/)
- [Deploy Gardener on Google Cloud C4A (Arm-based Axion VMs)](https://learn.arm.com/learning-paths/servers-and-cloud-computing/gardener-gcp/)
- [Deploy Django on Arm-based Google Cloud C4A](https://learn.arm.com/learning-paths/servers-and-cloud-computing/django-on-gcp/)
- [Deploy DeepSeek-R1 on Arm Servers with llama.cpp](https://learn.arm.com/learning-paths/servers-and-cloud-computing/deepseek-cpu/)
- [Deploy Couchbase on Google Cloud C4A](https://learn.arm.com/learning-paths/servers-and-cloud-computing/couchbase-on-gcp/)
- [Deploy containers on Arm-based compute using Amazon ECS and the AWS CDK](https://learn.arm.com/learning-paths/servers-and-cloud-computing/aws-cdk/)
- [Deploy containers on Amazon ECS with AWS Graviton processors](https://learn.arm.com/learning-paths/servers-and-cloud-computing/ecs/)
- [Deploy CircleCI Arm Native Workflows on AWS EC2 Graviton](https://learn.arm.com/learning-paths/servers-and-cloud-computing/circleci-on-aws/)
- [Deploy Cassandra on a Google Axion C4A virtual machine](https://learn.arm.com/learning-paths/servers-and-cloud-computing/cassandra-on-gcp/)
- [Deploy AWS services using the Serverless Framework](https://learn.arm.com/learning-paths/servers-and-cloud-computing/serverless-framework-aws-intro/)
- [Deploy Arm-based Cobalt 100 VMs using Azure Resource Manager templates](https://learn.arm.com/learning-paths/servers-and-cloud-computing/azure-arm-template/)
- [Deploy Arm virtual machines on Google Cloud Platform (GCP) using Terraform](https://learn.arm.com/learning-paths/servers-and-cloud-computing/gcp/)
- [Deploy Arcee AFM-4.5B on Arm-based Google Cloud Axion with Llama.cpp](https://learn.arm.com/learning-paths/servers-and-cloud-computing/arcee-foundation-model-on-gcp/)
- [Deploy Arcee AFM-4.5B on Arm-based AWS Graviton4 with Llama.cpp](https://learn.arm.com/learning-paths/servers-and-cloud-computing/arcee-foundation-model-on-aws/)
- [Deploy applications on Arm-based GKE using GitOps with Argo CD](https://learn.arm.com/learning-paths/servers-and-cloud-computing/argo-cd-gcp/)
- [Deploy Apache Flink on Google Cloud C4A (Arm-based Axion VMs)](https://learn.arm.com/learning-paths/servers-and-cloud-computing/flink-on-gcp/)
- [Deploy and integrate AWS Lambda with DynamoDB using the Serverless Framework](https://learn.arm.com/learning-paths/servers-and-cloud-computing/serverless-framework-aws-lambda-dynamodb/)
- [Deploy an AWS IoT Greengrass custom component to Arm devices and verify PAC/BTI support](https://learn.arm.com/learning-paths/cross-platform/aws-greengrass-pacbti-test/)
- [Deploy an application to Azure Kubernetes Service](https://learn.arm.com/learning-paths/servers-and-cloud-computing/from-iot-to-the-cloud-part3/)
- [Deploy an AI Agent on Arm with llama.cpp and llama-cpp-agent using KleidiAI](https://learn.arm.com/learning-paths/servers-and-cloud-computing/ai-agent-on-cpu/)
- [Deploy Alluxio on Azure Cobalt 100 Arm64 virtual machines for data orchestration and caching](https://learn.arm.com/learning-paths/servers-and-cloud-computing/alluxio-cobalt/)
- [Deploy a static website to Amazon S3 and integrate with AWS Lambda and DynamoDB using the Serverless Framework](https://learn.arm.com/learning-paths/servers-and-cloud-computing/serverless-framework-aws-s3/)
- [Deploy a live sensor dashboard with TimescaleDB and Grafana on Google Cloud C4A](https://learn.arm.com/learning-paths/servers-and-cloud-computing/timescaledb-on-gcp/)
- [Deploy a Large Language Model (LLM) chatbot with llama.cpp using KleidiAI on Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/llama-cpu/)
- [Deploy a containerized application using Azure Container Instances](https://learn.arm.com/learning-paths/servers-and-cloud-computing/from-iot-to-the-cloud-part2/)
- [Deploy a Cobalt 100 Virtual Machine on Azure](https://learn.arm.com/learning-paths/servers-and-cloud-computing/cobalt/)
- [Deploy .NET applications to Arm Virtual Machines and Container Registry in Microsoft Azure](https://learn.arm.com/learning-paths/servers-and-cloud-computing/from-iot-to-the-cloud-part1/)
- [Create multi-architecture Docker images with Buildkite on Google Axion](https://learn.arm.com/learning-paths/servers-and-cloud-computing/buildkite-gcp/)
- [Building and Benchmarking DLRM on Arm Neoverse V2 with MLPerf](https://learn.arm.com/learning-paths/servers-and-cloud-computing/dlrm/)
- [Build Semantic Search and Chatbot Retrieval Systems with Qdrant on Google Cloud C4A Axion processors](https://learn.arm.com/learning-paths/servers-and-cloud-computing/qdrant-on-axion/)
- [Build RAG applications with LlamaIndex on a Google Cloud C4A virtual machine](https://learn.arm.com/learning-paths/servers-and-cloud-computing/llamaindex-rag-axion/)
- [Build ML Workflow Pipelines with Flyte and gRPC on Google Cloud C4A Axion processors](https://learn.arm.com/learning-paths/servers-and-cloud-computing/flyte-with-grpc/)
- [Build computer vision pipelines with OpenCV on a Google Cloud C4A Axion VM](https://learn.arm.com/learning-paths/servers-and-cloud-computing/opencv-on-axion/)
- [Build and run vLLM on Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/vllm/)
- [Build a real-time analytics pipeline with ClickHouse on Google Cloud Axion](https://learn.arm.com/learning-paths/servers-and-cloud-computing/clickhouse-gcp/)
- [Build a RAG application using Zilliz Cloud on Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/milvus-rag/)
- [Build a multi-architecture Kubernetes cluster running nginx on Azure AKS](https://learn.arm.com/learning-paths/servers-and-cloud-computing/multiarch_nginx_on_aks/)
- [Build a CI/CD pipeline using GitLab-hosted Arm runners](https://learn.arm.com/learning-paths/cross-platform/gitlab-managed-runners/)
- [Benchmarking MySQL with Sysbench](https://learn.arm.com/learning-paths/servers-and-cloud-computing/mysql_benchmark/)
- [Benchmark the performance of Flink on Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/flink/)
- [Benchmark Go performance with Sweet and Benchstat](https://learn.arm.com/learning-paths/servers-and-cloud-computing/go-benchmarking-with-sweet/)
- [Autoscale HTTP applications on Kubernetes with KEDA and Kedify](https://learn.arm.com/learning-paths/servers-and-cloud-computing/kedify-http-autoscaling/)
- [Analyze the performance of MongoDB on Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/mongodb/)
- [Analyze cache behavior with Perf C2C on Arm](https://learn.arm.com/learning-paths/servers-and-cloud-computing/false-sharing-arm-spe/)
- [Add Arm nodes to your GKE cluster using a multi-architecture Ollama container image](https://learn.arm.com/learning-paths/servers-and-cloud-computing/multiarch_ollama_on_gke/)
- [Access running containers using Supervisor, SSH, and Remote.It](https://learn.arm.com/learning-paths/servers-and-cloud-computing/supervisord/)
- [Accelerate Whisper on Arm with Hugging Face Transformers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/whisper/)
- [Accelerate search performance with SVE2 MATCH on Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/sve2-match/)
- [Accelerate Natural Language Processing (NLP) models from Hugging Face on Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/benchmark-nlp/)
- [Accelerate Bitmap Scanning with Neon and SVE Instructions on Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/bitmap_scan_sve2/)
- [Use self-hosted Arm64-based runners in GitHub Actions for CI/CD](https://learn.arm.com/learning-paths/laptops-and-desktops/self_hosted_cicd_github/)
- [Optimize memory access behavior using Arm Performix and the Arm MCP Server](https://learn.arm.com/learning-paths/servers-and-cloud-computing/performix-memory-access/)
- [Find Code Hotspots with Arm Performix](https://learn.arm.com/learning-paths/servers-and-cloud-computing/cpu_hotspot_performix/)
- [Accelerate random number generation with OpenRNG and Performix](https://learn.arm.com/learning-paths/servers-and-cloud-computing/openrng-with-performix/)
- [Use Arm64EC with Windows 11 on Arm](https://learn.arm.com/learning-paths/laptops-and-desktops/win_arm64ec/)
- [Unlock quantized LLM performance on Arm-based NVIDIA DGX Spark](https://learn.arm.com/learning-paths/laptops-and-desktops/dgx_spark_llamacpp/)
- [Run AI models with Docker Model Runner](https://learn.arm.com/learning-paths/laptops-and-desktops/docker-models/)
- [Create Linux virtual machines with Hyper-V](https://learn.arm.com/learning-paths/laptops-and-desktops/hyper-v/)
- [Automate Windows on Arm builds with GitHub Arm-hosted runners](https://learn.arm.com/learning-paths/laptops-and-desktops/gh-arm-runners-win/)
- [Port applications to Arm64 using Arm64EC](https://learn.arm.com/learning-paths/laptops-and-desktops/win_arm64ec_porting/)
- [Install Ubuntu on ChromeOS Crostini as an LXC container](https://learn.arm.com/learning-paths/laptops-and-desktops/chrome-os-lxc/)
- [Develop cross-platform desktop applications with Electron on Windows on Arm](https://learn.arm.com/learning-paths/laptops-and-desktops/electron/)
- [Build and run a native Windows on Arm Qt application](https://learn.arm.com/learning-paths/laptops-and-desktops/win_arm_qt/)
- [Build and test KleidiCV on macOS](https://learn.arm.com/learning-paths/laptops-and-desktops/kleidicv-on-mac/)
- [Build a Windows on Arm native application with clang](https://learn.arm.com/learning-paths/laptops-and-desktops/llvm_putty/)
- [Run the AV1 and VP9 codecs on Arm Linux](https://learn.arm.com/learning-paths/servers-and-cloud-computing/codec1/)
- [Generate Arm Performix AI insights in Visual Studio Code with Codex](https://learn.arm.com/learning-paths/servers-and-cloud-computing/performix-agentic-dynamic-insights-codex/)
- [Get started with the arm-performix agent skill for profiling and improving Arm workloads](https://learn.arm.com/learning-paths/servers-and-cloud-computing/performix-llm-agent-skill/)
- [Profiling for Neoverse with Streamline CLI Tools](https://learn.arm.com/learning-paths/servers-and-cloud-computing/profiling-for-neoverse/)
- [Benchmark Arm CPU performance with Geekbench](https://learn.arm.com/learning-paths/servers-and-cloud-computing/geekbench/)
- [Inspect model artifacts and runtime profiles with Google Model Explorer and Arm extensions](https://learn.arm.com/learning-paths/cross-platform/explore-model-artifacts-with-model-explorer/)
- [Profile GPT-2 inference with the Arm Performix Instruction Mix recipe](https://learn.arm.com/learning-paths/servers-and-cloud-computing/performix-instruction-mix/)
- [Deploy a machine learning application to the Arm Ethos-U65 NPU on NXP FRDM i.MX 93 with Topo](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/deploy-ml-model-to-npu-with-topo/)
- [Create and deploy a custom Topo Project](https://learn.arm.com/learning-paths/cross-platform/create-your-own-topo-project/)
- [Run a local AI agent with Ollama to visualize CPU orchestration on Arm](https://learn.arm.com/learning-paths/cross-platform/ai-agent-cpu-orchestration/)
- [Analyze Java performance on Arm servers using flame graphs](https://learn.arm.com/learning-paths/servers-and-cloud-computing/java-perf-flamegraph/)
- [Run a Minecraft server on an Arm-based Oracle Cloud Infrastructure instance](https://learn.arm.com/learning-paths/servers-and-cloud-computing/minecraft-on-oci/)
- [Create an Armv8-A embedded application](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/bare-metal/)
- [Deploy IoT applications with Balena Cloud and Arm Virtual Hardware](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/avh_balena/)
- [Device-to-Device communication with Device Connect](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/device-connect-d2d/)
- [Design an AXI-Lite peripheral to control GPIOs](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/advanced_soc/)
- [Deploy IoT applications with AWS IoT Greengrass and Arm Virtual Hardware](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/avh_greengrass/)
- [Deploy firmware on hybrid edge systems using containers](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/cloud-native-deployment-on-hybrid-edge-systems/)
- [Build an RTX5 RTOS application with Keil μVision](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/cmsis_rtx/)
- [Build an RTX5 RTOS application with Keil Studio (VS Code)](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/cmsis_rtx_vs/)
- [Write Arm Assembler functions](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/asm/)
- [Learn about context switching on Arm Cortex-M processors](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/context-switch-cortex-m/)
- [Get started with Keil MDK Code Coverage](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/coverage_mdk/)
- [Get started with Arm Development Studio](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/armds/)
- [Embedded programming with Arduino on the Raspberry Pi Pico](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/arduino-pico/)
- [Accelerate multimodal Voice Assistant performance with KleidiAI and SME2](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/voice-assistant/)
- [Learn how to use Docker](https://learn.arm.com/learning-paths/cross-platform/docker/)
- [Build multi-architecture container images with Docker Build Cloud](https://learn.arm.com/learning-paths/cross-platform/docker-build-cloud/)
- [Build an edge AI Reachy Mini app with Raspberry Pi, MediaPipe, and MuJoCo](https://learn.arm.com/learning-paths/cross-platform/build-a-reachy-robot-app-on-pi/)
- [Boost C++ performance by optimizing loops with boundary information](https://learn.arm.com/learning-paths/cross-platform/cpp-loop-size-context/)
- [Migrate applications to Arm servers using migrate-ease](https://learn.arm.com/learning-paths/servers-and-cloud-computing/migrate-ease/)
- [Write Neon intrinsics using GitHub Copilot to improve Adler32 performance](https://learn.arm.com/learning-paths/cross-platform/adler32/)
- [Write a Dynamic Memory Allocator](https://learn.arm.com/learning-paths/cross-platform/dynamic-memory-allocator/)
- [Get started with Realm Management Extension (RME)](https://learn.arm.com/learning-paths/cross-platform/cca_rme/)
- [Build multi-architecture container images with GitHub Arm-hosted runners](https://learn.arm.com/learning-paths/cross-platform/github-arm-runners/)
- [Automate MCP server testing using Pytest and Testcontainers](https://learn.arm.com/learning-paths/cross-platform/automate-mcp-with-testcontainers/)
- [Create a new Learning Path](https://learn.arm.com/learning-paths/cross-platform/_example-learning-path/)
- [Get started with CCA Attestation and Veraison](https://learn.arm.com/learning-paths/servers-and-cloud-computing/cca-veraison/)
- [Run an application in a Realm using the Arm Confidential Compute Architecture (CCA)](https://learn.arm.com/learning-paths/servers-and-cloud-computing/cca-container/)
- [Explore performance gains by increasing the Linux kernel page size on Arm](https://learn.arm.com/learning-paths/servers-and-cloud-computing/arm_linux_page_size/)
- [Deploy Open AD Kit containerized autonomous driving simulation on Arm Neoverse](https://learn.arm.com/learning-paths/automotive/openadkit1_container/)
- [Develop Arm automotive software on the System76 Thelio Astra](https://learn.arm.com/learning-paths/automotive/system76-auto/)
- [Debug Arm Zena CSS Reference Software Stack with Arm Development Studio](https://learn.arm.com/learning-paths/automotive/zenacssdebug/)
- [Generate audio with Stable Audio Open Small on LiteRT](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/run-stable-audio-open-small-with-lite-rt/)
- [Run vLLM inference with quantized models and benchmark on Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/vllm-benchmark-quantisation/)
- [Run Vision LLM inference on Android with KleidiAI and MNN](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/vision-llm-inference-on-android-with-kleidiai-and-mnn/)
- [Run Process watch on your Arm machine](https://learn.arm.com/learning-paths/servers-and-cloud-computing/processwatch/)
- [Profile the Performance of AI and ML Mobile Applications on Arm](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/profiling-ml-on-arm/)
- [Optimize performance using Link-Time Optimization with GCC](https://learn.arm.com/learning-paths/servers-and-cloud-computing/gcc-lto/)
- [Optimize network interrupt handling on Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/irq-tuning-guide/)
- [Optimize MLOps with Arm-hosted GitHub Runners](https://learn.arm.com/learning-paths/servers-and-cloud-computing/gh-runners/)
- [Optimize graphics performance using Frame Advisor render graphs](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/render-graph-optimization/)
- [Learn the Arm Neoverse N1 performance analysis methodology](https://learn.arm.com/learning-paths/servers-and-cloud-computing/top-down-n1/)
- [Learn how to create a virtual machine in a Realm using Arm Confidential Compute Architecture (CCA)](https://learn.arm.com/learning-paths/servers-and-cloud-computing/rme-cca-basics/)
- [Install and Use Arm integration packages for Unity](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/unity_packages/)
- [Improve data compression performance on Arm servers with zlib-ng](https://learn.arm.com/learning-paths/servers-and-cloud-computing/zlib/)
- [Get started with the Neoverse Reference Design software stack](https://learn.arm.com/learning-paths/servers-and-cloud-computing/refinfra-quick-start/)
- [Get started with the Arm 5G RAN Acceleration Library (ArmRAL)](https://learn.arm.com/learning-paths/servers-and-cloud-computing/ran/)
- [Get started with Servers and Cloud Computing](https://learn.arm.com/learning-paths/servers-and-cloud-computing/intro/)
- [Get started with Arm hardware](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/intro/)
- [Generate audio with Stable Audio Open Small using ExecuTorch](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/run-stable-audio-with-executorch/)
- [Enable reproducible math functions across vector extensions with Arm Performance Libraries](https://learn.arm.com/learning-paths/servers-and-cloud-computing/reproducible-libamath/)
- [Control floating-point accuracy modes in Arm Performance Libraries](https://learn.arm.com/learning-paths/servers-and-cloud-computing/multi-accuracy-libamath/)
- [Characterize system performance with Arm Performix](https://learn.arm.com/learning-paths/servers-and-cloud-computing/performix-system-characterization/)