I don't understand what is the reason of buildroot of a card such as beaglebone black where as it has a Linux system when we bought.What is the utility of the buildroot?
Build a completely custom, lightweight, and fast-booting embedded Linux system?
Buildroot is a set of Makefiles and patches that makes it easy to generate a complete embedded Linux system.
Buildroot can generate any or all of a cross-compilation toolchain, a root filesystem, a kernel image and a bootloader image.
It is useful mainly for people working with small or embedded systems, using various CPU architectures (x86, ARM, MIPS, PowerPC, etc.) : it automates the building process of your embedded system and eases the cross-compilation process.
The resulting root filesystem is mounted read-only, but other filesystems can be mounted read/write for persistence.
Although user accounts can be created, in practice almost everything is done as root. Buildroot uses no package manager.
Instead, package selection is managed through make menuconfig.
source http://elinux.org/BeagleBone_Operating_Systems
Related
Are containers specific to a particular host OS? For instance, if a container is created on Windows with particular dependencies (e.g., DLL files), can it run in a setup in which the host OS is Linux? I initially assumed that a container must be specific to a particular host OS.
But the following two excerpts seem to suggest that I may not have understood the mechanics correctly. So my question is: are containers built over the docker engine so when the dependencies are included, they are relative to the docker engine and the underlying host OS does not matter?
(1) From IBM:
Containerization allows developers to create and deploy applications faster and more securely. With traditional methods, code is developed in a specific computing environment which, when transferred to a new location, often results in bugs and errors. For example, when a developer transfers code from a desktop computer to a virtual machine (VM) or from a Linux to a Windows operating system. Containerization eliminates this problem by bundling the application code together with the related configuration files, libraries, and dependencies required for it to run. This single package of software or “container” is abstracted away from the host operating system, and hence, it stands alone and becomes portable—able to run across any platform or cloud, free of issues. [https://www.ibm.com/cloud/learn/containerization]
(2) From Docker:
Does Docker run on Linux, macOS, and Windows?
You can run both Linux and Windows programs and executables in Docker containers. The Docker platform runs natively on Linux (on x86-64, ARM and many other CPU architectures) and on Windows (x86-64).
Docker Inc. builds products that let you build and run containers on Linux, Windows and macOS.
What does Docker technology add to just plain LXC?🔗
Docker technology is not a replacement for LXC. “LXC” refers to capabilities of the Linux kernel (specifically namespaces and control groups) which allow sandboxing processes from one another, and controlling their resource allocations. On top of this low-level foundation of kernel features, Docker offers a high-level tool with several powerful functionalities:
Portable deployment across machines. Docker defines a format for bundling an application and all its dependencies into a single object called a container. This container can be transferred to any Docker-enabled machine. The container can be executed there with the guarantee that the execution environment exposed to the application is the same in development, testing, and production. LXC implements process sandboxing, which is an important pre-requisite for portable deployment, but is not sufficient for portable deployment. If you sent me a copy of your application installed in a custom LXC configuration, it would almost certainly not run on my machine the way it does on yours. The app you sent me is tied to your machine’s specific configuration: networking, storage, logging, etc. Docker defines an abstraction for these machine-specific settings. The exact same Docker container can run - unchanged - on many different machines, with many different configurations.
The host OS, or precisely, the kernel provided still matters. That's why you can't run Windows containers on Linux. You can run Linux container on Windows due to Hyper-V and WSL2, and on macOS with Hypervisor, but that's it. If the provided kernel is compatible (doesn't have to be identical), usually similar version and the same architecture (remember, there are x64, ARM64, etc) or at least supported virtualization (x64 containers can run on M1, which is ARM64) then you can just run the container, no need to worry about DLLs because they're supposed to be included either in one of the base image you start with or the image you generate.
Our requirement is to create a container for legacy apps over docker.
We don't have the operating system support/application server support available, nor do we have knowledge to build them from scratch.
But we have a physical instance of the legacy app running in our farm.
We could get an ISO image from our server team if required, our question is if we get this ISO image can we export this as a docker image?
if yes, please let me know if there is any specific procedure or steps associated with it.
if no, please tell me why? and the possible workarounds for the same.
if we get this ISO image can we export this as a docker image?
I don't think there is an easy way (like push-the-export-button) to do this. Explanation follows...
You are describing a procedure taking place in the Virtual Machine world. You take a snapshot of a server, move the .iso file somewhere else and create a new VM that will run on a Hypervisor.
Containers are not VMs. They "contain" all the bytes that a service needs to run but not a whole operating system. They are supposed to run as processes on the host.
Workarounds:
You will have to get your hands dirty. This means that you will have to find out what the legacy app uses (for example Apache + PHP + MySql + app code) and build it from scratch with Docker.
Some thoughts:
containers are supposed to be lightweight. For example one might use one container for the database, another one for the Apache etc... Your case looks like you are moving towards a fat container that has everything inside.
Depending on what the legacy technology is, you might hit a wall... For example, if we are talking about something working with old php, mysql you might find ready-to-use images on hub.docker.com. But if the legacy app is a financial system written in cobol, I don't know what your starting point might be...
You will need to reverse engineer the application dependencies from the artifacts that you have in access to. This means recovering the language specific dependencies (whether python, java, php, node, etc). And any operating system level packages/dependencies that are required.
Essentially you are rebuilding the contents of that ISO image inside your docker file using OS package installation tools like apt, language level tools like pip, PECL, PEAR, composer, or maven, and finally the files that make up the app code.
So, for example: a PHP application might be dependent on having build-essential and php-mysql installed in the OS. Then the app may be dependent on packages like twig and monolog loaded through composer. If you are using SASS you may need to install ruby as well.
Your job is to track all these down and create a docker file that reproduces the iso image. If you are using a common stack like a J2EE app in tomcat, or a php app fronted by apache or ngnix, there will be base docker images that will get you most of the way to where you need to go.
It does look like there are some tools that can do this for you automatically: Dependency Walker equivalent for Linux?. I can't vouch for any of them. But you can also use command line tools. For example this will give you a list of all the user installed packages on a fedora system:
sudo dnf history userinstalled
When an app is using a dependency manager like composer or pip, there is usually a file that lists all the language specific dependencies.
At the end of the process you'll have a portable legacy app that can be easily deployed anywhere with a minimal footprint.
As one of the comments rightly points out, creating a VM from the ISO image is another way forward that will be much easier to accomplish. The application dependencies won't be explicit, but maybe that's ok for your use case.
I need to write a Bazel repository rule which downloads mysql binaries according to the required version, to the operating system and the architecture.
I'll get the required version from the user, the operating system from repository_os.name but I'm not sure how I can access the architecture?
The current non-hermetic code uses os.arch as a good enough heuristic (yes I know it's not precise).
There is no way to access the architecture, except asking for uname -m using repository_ctx.execute. You can also make it work on Windows by executing a different command depending on repository_ctx.os.name (which is the same as os.name from the JVM so if it contains win you can execute the Windows command). If you think this is needed, please file a feature request on https://github.com/bazelbuild/bazel/issues/new
The host platform's CPU architecture and operating system name are accessible via repository_ctx.os. The attribute is a repository_os struct with arch and name.
There was a project thrown my way recently that involves the orchestration of several (Linux capable) embedded devices, deploying software to them, and allowing for the applications to be updated when the code base updates in a git repo.
The initial thought was to make a standard image for each device, and I set out, attempting to install docker on an UDOO Quad and an Intel Edison to start, but without any success up to this point.
My thinking is that it seems to be a good idea to install Docker on embedded devices--but if that's the case, surely it would have been ported by now. The only group out there that seems to be making these efforts is Resin.io.
Is there something I'm missing, or is there a clear reason why Docker doesn't make sense on embedded devices? If there isn't a reason, and it does make sense to run Docker on embedded systems, is there something I've overlooked out there: are there any sources of discussion on porting, or how-to's that cover this?
I have considered running docker on embedded devices (a mips system), but didn't go that way. There are some problems with it, in my humble view:
Docker is implemented in Golang. There is currently no available tool chain for mips to compile go. You will need to create the tool chain yourself using gcc-go.
The size of docker is larger than lxc. In a desktop computer this is not a problem, but the embedded device has limited flash storage.
Docker uses some quite up-to-date feature of linux kernel. Sometimes the kernel version on embedded devices are not so new and back-port is needed to make it work.
The docker image has to be built on the same architecture as the run time environment. It means that if you want to run a docker container on Raspberry Pi, the docker image has to be built on an ARM-architecture system. QEMU can be used to build docker image in the cloud, but it doesn't support all CPU architectures used in embedded system. (for example, it currently doesn't support MIPS)
In the end, lxc was chosen for the specific task of running a container on embedded device. It has limited features compared to docker, but currently it suits the requirement of the project.
As of year 2019, I would like to update this answer since I did port docker to embedded system with ARM cpu. With the price of flash usage, memory usage, by using docker you will have container management, image management, and many ready to run images from docker hub. So the decision is a balance between cost and features.
Here is an update for 2018:
You can work with Docker on embedded devices such as Raspberry Pi and Orange Pi quite easily now because of advancements in the development of Raspbian and Armbian operating system images. Specifically, both types of devices and their respective OS images now support kernels that are of sufficiently high enough versions to install Docker without any problems (at least version 3.10, though both now offer 4.x+ versions).
Your desire for faster rates of change can definitely be realized by using embedded Docker. I can say from experience that I have tested and regularly run the approach you describe. Basically, you start with a base operating system image such as Raspbian or Armbian, tweak that operating system enough that it's secure and has Docker installed, and then you use Docker for handling development iteration and application updates.
As an aside, if you are interested in running Docker on embedded Linux devices, then I recommend you check out a free, open-source, MIT-licensed command line tool I wrote to help developers work with embedded Docker on multiple devices at once: https://github.com/ForwardLoopLLC/floopcli .
Even if you are not interested in the tool itself, the documentation for the tool describes several patterns for working with Dockerized applications across multiple devices in multiple languages: https://docs.forward-loop.com/floopcli/master/index.html . The materials there should serve as a starting point for porting applications to Docker and then deploying them on embedded devices. The documentation also addresses some embedded device subtleties, such as differences between ARMv6 and ARMv7. Hopefully this helps you get started!
There is a great article on LinkedIn describing his experience with that
https://www.linkedin.com/pulse/whale-jar-when-running-docker-embedded-linux-good-thing-fletcher#pulse-comments-urn:li:article:7736487387895237975
Often embedded systems have a very slow rate of change. Docker works well on a minimum build then layering on top. If you want to sacrifice the overhead of running docker on a minimum embedded system for docker's ability to have a build system and steady rate of change then you could explorer it.
The Neo4j manual shows that windows is supported, but the minimum filesystem is Ext4, what are the compromises for NTFS.
Neo4J is written on java and uses JDK abstraction of file system. So developers can recommend you some operation system, but theoretically it will work on FAT or even on proprietary OS of your cooler (if it is run with Java control).
Just provide your own measurement of performance at possible target OS and select best one.