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Azure powers rapid deployment of private 4G and 5G networks

As the cloud continues to expand into a ubiquitous and highly distributed fabric, a new breed of application is emerging: Modern Connected Applications. We define these new offerings as network-intelligent applications at the edge, powered by 5G, and enabled by programmable interfaces that give developer access to network resources. Along with internet of things (IoT) and real-time AI, 5G is enabling this new app paradigm, unlocking new services and business models for enterprises, while accelerating their network and IT transformation.

At Mobile World Congress this year, Microsoft announced a significant step towards helping enterprises in this journey: Azure Private 5G Core, available as a part of the Azure private multi-access edge compute (MEC) solution. Azure Private 5G Core enables operators and system integrators (SIs) to provide a simple, scalable, and secure deployment of private 4G and 5G networks on small footprint infrastructure, at the enterprise edge.

This blog dives a little deeper into the fundamentals of the service and highlights some extensions that enterprises can leverage to gain more visibility and control over their private network. It also includes a use case of an early deployment of Azure Kubernetes Services (AKS) on an edge platform, leveraged by the Azure Private 5G Core to rapidly deploy such networks.

Building simple, scalable, and secure private networks

Azure Private 5G Core dramatically simplifies the deployment and operation of private networks. With just a few clicks, organizations can deploy a customized set of selectable 5G core functions, radio access network (RAN), and applications on a small edge-compute platform, at thousands of locations. Built-in automation delivers security patches, assures compliance, and performs audits and reporting. Enterprises benefit from a consistent management experience and improved service assurance experience, with all logs and metrics from cloud to edge available for viewing within Azure dashboards.

Enterprises need the highest level of security to connect their mission critical operations. Azure Private 5G Core makes this possible by natively integrating into a broad range of Azure capabilities. With Azure Arc, we provide seamless and secure connectivity from an on-premises edge platform into the Azure cloud. With Azure role-based access control (RBAC), administrators can author policies and define privileges that will allow an application to access all necessary resources. Likewise, users can be given appropriate access to manage all resources in a resource group, such as virtual machines, websites, and subnets. Our Zero Trust security frameworks are integrated from devices to the cloud to keep users and data secure. And our complete, “full-stack” solution (hardware, host and guest operating system, hypervisor, AKS, packet core, IoT Edge Runtime for applications, and more) meets standard Azure privacy and compliance benchmarks in the cloud and on the enterprise edge, meaning that data privacy requirements are adhered to in each geographic region.

Deploying private 5G networks in minutes

Microsoft partner Inventec is a leading design manufacturer of enterprise-class technology solutions like laptops, servers, and wireless communication products. The company has been quick to see the potential benefit in transforming its own world-class manufacturing sites into 5G smart factories to fully utilize the power of AI and IoT.

In a compelling example of rapid private 5G network deployment, Inventec recently installed our Azure private MEC solution in their Taiwan smart factory. It took only 56 minutes to fully deploy the Azure Private 5G Core and connect it to 5G access points that served multiple 5G endpoints—a significant reduction from the months that enterprises have come to expect. Azure Private 5G Core leverages Azure Arc and Azure Kubernetes Service on-prem to provide security and manageability for the entire core network stack. Figures 1 and 2 below show snapshots from the trial.

Figure 1: Screenshot of logs with time stamps showing start and completion of the core network deployment.

Figure 2: Screenshot from the trial showing one access point successfully connected to seven endpoints.

Inventec is developing applications for manufacturing use-cases that leverage private 5G networks and Microsoft’s Azure Private 5G Core. Examples of these high-value MEC use cases include Automatic Optical Inspection (AOI), facial recognition, and security surveillance systems.

Extending enterprise control and visibility from the 5G core

Through close integration with other elements of the Azure private MEC solution, our Azure Private 5G Core essentially acts as an enterprise “control point” for private wireless networks. Through comprehensive APIs, the Azure Private 5G Core can extend visibility into the performance of connected network elements, simplify the provisioning of subscriber identity modules (SIMs) for end devices, secure private wireless deployments, and offer 5G connectivity between cloud services (like IoT Hub) and associated on-premises devices.

Figure 3: Azure Private 5G Core is a central control point for private wireless networks.

Customers, developers, and partners are finding value today with a number of early integrations with both Azure and third-party services that include:

Plug and play RAN: Azure private MEC offers a choice of 4G or 5G Standalone radio access network (RAN) partners that integrate directly with the Azure Private 5G Core. By integrating RAN monitoring with the Azure Private 5G Core, RAN performance can be made visible through the Azure management portal. Our RAN partners are also onboarding their Element Management System (EMS) and Service Management and Orchestrator (SMO) products to Azure, simplifying the deployment processes and have a framework for closed-loop radio performance automation.
Azure Arc managed edge: The Azure Private 5G Core takes advantage of the security and reliability capabilities of Azure Arc-enabled Azure Kubernetes Service running on Azure Stack Edge Pro. These include policy definitions with Azure Policy for Kubernetes, simplified access to AKS clusters for High Availability with Cluster Connect and fine-grained identity and access management with Azure RBAC. 
Device and Profile Management: Azure Private 5G Core APIs integrate with SIM management services to securely provision the 5G devices with appropriate profiles. In addition, integration with Azure IoT Hub enables unified management of all connected IoT devices across an enterprise and provides a message hub for IoT telemetry data. 
Localized ISV MEC applications: Low-latency MEC applications benefit from running side-by-side with core network functions on the common (Azure private MEC) edge-compute platform. By integrating tightly with the Azure Private 5G Core using Azure Resource Manager APIs, third-party applications can configure network resources and devices. Applications offered by partners are available in, and deployable from the Azure Marketplace.

It’s easy to get started with Azure private MEC

As innovative use cases for private wireless networks continue to develop and industry 4.0 transformation accelerates, we welcome ISVs, platform partners, operators, and SIs to learn more about Azure private MEC.

Application ISVs interested in deploying their industry or horizontal solutions on Azure should begin by onboarding their applications to Azure Marketplace.
Platform partners, operators, and SIs interested in partnering with Microsoft to deploy or integrate with private MEC can get started by reaching out to the Azure private MEC Team.

Microsoft is committed to helping organizations innovate from the cloud, to the edge, and to space—offering the platform and ecosystem strong enough to support the vision and vast potential of 5G. As the cloud continues to expand and a new breed of modern connected apps at the edge emerges, the growth and transformation opportunities for enterprises will be profound. Learn more about how Microsoft is helping developers embrace 5G.
Quelle: Azure

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Cross Compiling Rust Code for Multiple Architectures

Getting an idea, planning it out, implementing your Rust code, and releasing the final build is a long process full of unexpected issues. Cross compilation of your code will allow you to reach more users, but it requires knowledge of building executables for different runtime environments. Luckily, this post will help in getting your Rust application running on multiple architectures, including x86 for Windows.
Overview
You want to vet your idea with as many users as possible, so you need to be able to compile your code for multiple architectures. Your users have their own preferences on what machines and OS to use, so we should do our best to meet them in their preferred set-up. This is why it’s critical to pick a language or framework that lends itself to support multiple ways to export your code for multiple target environments with minimal developer effort. Also, it’d be better to have tooling in place to help automate this export process.
If we invest some time in the beginning to pick the right coding language and automation tooling, then we’ll avoid the headaches of not being able to reach a wider audience without the use of cumbersome manual steps. Basically, we need to remove as many barriers as possible between our code and our audience.
This post will cover building a custom Docker image, instantiating a container from that image, and finally using that container to cross compile your Rust code. Your code will be compiled, and an executable will be created for your target environment within your working directory.
What You’ll Need

Your Rust code (to help you get started, you can use the source code from this git repo)
The latest version of Docker Desktop

Getting Started
My Rust directory has the following structure:

.
├── Cargo.lock
├── Cargo.toml
└── src
└── main.rs

 
The lock file and toml file both share the same format. The lock file lists packages and their properties. The Cargo program maintains the lock file, and this file should not be manually edited. The toml file is a manifest file that specifies the metadata of your project. Unlike the lock file, you can edit the toml file. The actual Rust code is in main.rs. In my example, the main.rs file contains a version of the game Snake that uses ASCII art graphics. These files run on Linux machines, and our goal is to cross compile them into a Windows executable.
The cross compilation of your Rust code will be done via Docker. Download and install the latest version of Docker Desktop. Choose the version matching your workstation OS — and remember to choose either the Intel or Apple (M-series) processor variant if you’re running macOS.
 

 
 
 
 
 
 
 
Creating Your Docker Image
Once you’ve installed Docker Desktop, navigate to your Rust directory. Then, create an empty file called Dockerfile within that directory. The Dockerfile will contain the instructions needed to create your Docker image. Paste the following code into your Dockerfile:

FROM rust:latest

RUN apt update && apt upgrade -y
RUN apt install -y g++-mingw-w64-x86-64

RUN rustup target add x86_64-pc-windows-gnu
RUN rustup toolchain install stable-x86_64-pc-windows-gnu

WORKDIR /app

CMD ["cargo", "build", "–target", "x86_64-pc-windows-gnu"]

 
Setting Up Your Image
The first line creates your image from the Rust base image. The next command upgrades the contents of your image’s packages to the latest version and installs mingw, an open source program that builds Windows applications.
Compiling for Windows
The next two lines are key to getting cross compilation working. The rustup program is a command line toolchain manager for Rust that allows Rust to support compilation for different target platforms. We need to specify which target platform to add for Rust (a target specifies an architecture which can be compiled into by Rust). We then install that toolchain into Rust. A toolchain is a set of programs needed to compile our application to our desired target architecture.
Building Your Code
Next, we’ll set the working directory of our image to the app folder. The final line utilizes the CMD instruction in our running container. Our command instructs Cargo, the Rust build system, to build our Rust code to the designated target architecture.
Building Your Image
Let’s save our Dockerfile, and then navigate to that directory in our terminal. In the terminal, run the following command:
docker build . -t rust_cross_compile/windows
 
Docker will build the image by using the current directory’s Dockerfile. The command will also tag this image as rust_cross_compile/windows.
Running Your Container
Once you’ve created the image, then you can run the container by executing the following command:
docker run –rm -v ‘your-pwd’:/app rust_cross_compile/windows
 
The -rm option will remove the container when the command completes. The -v command allows you to persist data after a container has existed by linking your container storage with your local machine. Replace ‘your-pwd’ with the absolute path to your Rust directory. Once you run the above command, then you will see the following directory structure within your Rust directory:

.
├── Cargo.lock
├── Cargo.toml
└── src
└── main.rs
└── target
└── debug
└── x86_64-pc-windows-gnu
└── debug
termsnake.exe

 
Running Your Rust Code
You should now see a newly created directory called target. This directory will contain a subdirectory that will be named after the architecture you are targeting. Inside this directory, you will see a debug directory that contains the executable file. Clicking the executable allows you to run the application on a Windows machine. In my case, I was able to start playing the game Snake:
 

 
Running Rust on armv7
We have compiled our application into a Windows executable, but we can modify the Dockerfile like the below in order for our application to run on the armv7 architecture:

FROM rust:latest

RUN apt update && apt upgrade -y
RUN apt install -y g++-arm-linux-gnueabihf libc6-dev-armhf-cross

RUN rustup target add armv7-unknown-linux-gnueabihf
RUN rustup toolchain install stable-armv7-unknown-linux-gnueabihf

WORKDIR /app

ENV CARGO_TARGET_ARMV7_UNKNOWN_LINUX_GNUEABIHF_LINKER=arm-linux-gnueabihf-gcc CC_armv7_unknown_Linux_gnueabihf=arm-linux-gnueabihf-gcc CXX_armv7_unknown_linux_gnueabihf=arm-linux-gnueabihf-g++

CMD ["cargo", "build", "–target", "armv7-unknown-linux-gnueabihf"]

 
Running Rust on aarch64
Alternatively, we could edit the Dockerfile with the below to support aarch64:

FROM rust:latest

RUN apt update && apt upgrade -y
RUN apt install -y g++-aarch64-linux-gnu libc6-dev-arm64-cross

RUN rustup target add aarch64-unknown-linux-gnu
RUN rustup toolchain install stable-aarch64-unknown-linux-gnu

WORKDIR /app

ENV CARGO_TARGET_AARCH64_UNKNOWN_LINUX_GNU_LINKER=aarch64-linux-gnu-gcc CC_aarch64_unknown_linux_gnu=aarch64-linux-gnu-gcc CXX_aarch64_unknown_linux_gnu=aarch64-linux-gnu-g++

CMD ["cargo", "build", "–target", "aarch64-unknown-linux-gnu"]

 
Another way to compile for different architectures without going through the creation of a Dockerfile would be to install the cross project, using the cargo install -f cross command. From there, simply run the following command to start the build:
cross build –target x86_64-pc-windows-gnu
Conclusion
Docker Desktop allows you to quickly build a development environment that can support different languages and frameworks. We can build and compile our code for many target architectures. In this post, we got Rust code written on Linux to run on Windows, but we don’t have to limit ourselves to just that example. We can pick many other languages and architectures. Alternatively, Docker Buildx is a tool that was designed to help solve these same problems. Checkout more documentation of Buildx here.
Quelle: https://blog.docker.com/feed/