I need to containerize a JanusGraph database inside Docker, i don't know what files/directories needs to reside in volume to become persistent/writable. In order to make all the things simple and fast, can i install the entire database in a volume? Not only the data, but the entire app, all the binaries etc. I think this is a fast way to containerize some of my apps.
The janusGraph subdirectories of binaries, data, log resides inside a "janusgraph-hadoop" directory
For example: i will create a volume called /janusgraph-hadoop and run the command to install all the software inside that (it will be a volume).
This can be considered a bad practice or there are no problem in doing that?
I know, we have some JanusGraph already containerized, but they are not official, and my doubt is more general in order to containerize some apps in a more direct way without the need to research what directories need to be in volume and what not.
I will not redistribute any of this, it's just to my use.
At a technical level, nothing would stop you from launching a plain container with an attached volume and installing software there.
docker run -v my_opt:/opt -it --rm ubuntu sh
I wouldn't consider this an especially effective use of Docker. If your colleague wants to use your database installation, you have no way of giving it to them; if you leave the project for six months and come back to it, you'll have no record of how you built this setup. If you were set on this approach, you might find the networking and snapshot setups for more typical virtual machines to be better matched to it.
I'm looking to start creating proper isolated environments for django web apps. My first inclination is to use Docker. Also, it's usually recommended to use virtualenv with any python project to isolate dependencies.
Is virtualenv still necessary if I'm isolating projects via Docker images?
If your Docker container is relatively long-lived or your project dependencies change, there is still value in using a Python virtual-environment. Beyond (relatively) isolating dependencies of a codebase from other projects and the underlying system (and notably, the project at a given state), it allows for a certain measure of denoting the state of requirements at a given time.
For example, say that you make a Docker image for your Django app today, and end up using it for the following three weeks. Do you see your requirements.txt file being modified between now and then? Can you imagine a scenario in which you put out a hotpatch that comes with environmental changes?
As of Python 3.3, virtual-env is stdlib, which means it's very cheap to use, so I'd continue using it, just in case the Docker container isn't as disposable as you originally planned. Stated another way, even if your Docker-image pipeline is quite mature and the version of Python and dependencies are "pre-baked", it's such low-hanging fruit that while not explicitly necessary, it's worth sticking with best-practices.
No not really if each Python / Django is going to live in it's own container.
Recently I started to practice Dockers. Basically, I am running a C application on Docker container. Now, I want to try cloud foundry, therefore, trying to understand the difference between the two.
I'll describe the application as a novice because I am.
The application I start as a service(from /etc/init.d) and it reads a config file during startup, which specifies what all modules to load and IP of other services and it's own (0.0.0.0 does not work, so I have to give actual IP).
I had to manually update the IP and some details in the config file when the container starts. So, I wrote a startup script which did all the changes when the container starts and then the service start command.
Now, moving on to Cloud Foundry, the first thing I was not able to find is 'How to deploy C application' then I found a C build pack and a binary build pack option. I still have to try those but what I am not able to understand how I can provide a startup script to a cloud foundry container or in brief how to achieve what I was doing with Dockers.
The last option I have is to use docker containers in Cloud foundry, but I want to understand if I can achieve what I described above.
I hope I was clear enough to explain my doubt.
Help appreciated.
An old question, but a lot has changed since this was posted:
Recently I started to practice Dockers. Basically, I am running a C application on Docker container. Now, I want to try cloud foundry, therefore, trying to understand the difference between the two.
...
The last option I have is to use docker containers in Cloud foundry, but I want to understand if I can achieve what I described above.
There's nothing wrong with using Docker containers on CF. If you've already got everything set up to run inside a Docker container, being able to run that on CF give you yet another place you can easily deploy your workload.
While these are pretty minor, there are a couple requirements for your Docker container, so it's worth checking those to make sure it's possible to run on CF.
https://docs.cloudfoundry.org/devguide/deploy-apps/push-docker.html#requirements
Anyways, I am not working on this now as CF is not suitable for the project. It's an SIP application and CF only accepts HTTP/S requests.
OK, the elephant in the room. This is no longer true. CF has support for TCP routes. These allow you to receive TCP traffic directly to your application. This means, it's no longer just HTTP/S apps that are suitable for running on CF.
Instructions to set up your CF environment with TCP routing: https://docs.cloudfoundry.org/adminguide/enabling-tcp-routing.html
Instructions to use TCP routes as a developer: https://docs.cloudfoundry.org/devguide/deploy-apps/routes-domains.html#create-route-with-port
Now, moving on to Cloud Foundry, the first thing I was not able to find is 'How to deploy C application' then I found a C build pack and a binary build pack option.
Picking a buildpack is an important step. The buildpack takes your app and prepares it to run on CF. A C buildpack might sound nice as it would take your source code, build and run it, but it's going to get tricky because your C app likely depends on libraries. Libraries that may or may not be installed.
If you're going to go this route, you'll probably need to use CF's multi-buildpack support. This lets you run multiple buildpacks. If you pair this with the Apt buildpack, you can install the packages that you need so that any required libraries are available for your app as it's compiled.
https://docs.cloudfoundry.org/buildpacks/use-multiple-buildpacks.html
https://github.com/cloudfoundry/apt-buildpack
Using the binary buildpack is another option. In this case, you'd build your app locally. Perhaps in a docker container or on an Ubuntu VM (it needs to match the stack being used by your CF provider, i.e. cf stacks, currently Ubuntu Trusty or Ubuntu Bionic). Once you have a binary or binary + set of libraries, you can simply cf push the compiled artifacts. The binary buildpack will "run" (it actually does nothing) and then your app will be started with the command you specify.
My $0.02 only, but the binary buildpack is probably the easier of the two options.
what I am not able to understand how I can provide a startup script to a cloud foundry container or in brief how to achieve what I was doing with Dockers.
There's a few ways you can do this. The first is to specify a custom start command. You do this with cf push -c 'command'. This would normally be used to just start your app, like './my-app', but you could also use this to do other things.
Ex: cf push -c './prep-my-app.sh && ./my-app'
Or even just call your start script:
Ex: cf push -c './start-my-app.sh'.
CF also has support for a .profile script. This can be pushed with your app (at the root of the files you push), and it will be executed by the platform prior to your application starting up.
https://docs.cloudfoundry.org/devguide/deploy-apps/deploy-app.html#profile
Normally, you'd want to use a .profile script as you'd want to let the buildpack decide how to start your app (setting -c will override the buildpack), but in your case with the C or binary buildpack's, it's unlikely the buildpack will be able to do that, so you'll end up having to set a custom start command anyway.
For this specific case, I'd suggest using cf push -c as it's slightly easier, but for all other cases and apps deployed with other buildpacks, I'd suggest a .profile script.
Hope that helps!
I am trying to understand how docker can be used to dockerize multilayered application.
My tomcat application needs mongodb, mysql, redis, solr and rabbitmq. I am playing with Docker for couple of weeks now. I am able to install and use mongo/mysql containers. But I am not getting how can I completely ship application using Docker. I have few questions.
How should the images be. Should I have one image that has all the components installed or have separate images (like one for tomcat, one for mongo, one for mysql etc) and start those containers using a bash script outside of docker.
What is the docker way of maintaining multiple containers at once. Meaning say I have multiple containers (like mongo, mysql, tomcat etc...) that needs to be worked together to run my application, Is there any inbuilt way of dealing this so that one command/script does this?
Suppose I dockerize my application, how can i manage various routine tasks that need to be performed like incremental code deployment, database patches etc. Currently we are using vagrant, we also use fabric along with vagrant for various tasks.Like after vagrant up we use fab tasks for all kind of routine things like code deployment, db refresh, adding volumes, start/stop services etc. What would be the docker's way of doing this?
With Vagrant if VM crashes due to High CPU etc. host system is not affected. But I see docker is eating up lot of host resources. Can we put limits for that say not more than one cpu core for that container etc..?
Because we use vagrant, most of the questions above are in that context. When started with docker I thought docker as a kind of visualization technology that can be a replacement for our huge Vagrant based infra. Please correct me if I am wrong?
I advise you to look at docker-compose:
you'll be able to define an architecture of your application
you can then easily build it and run it (with one command)
pretty much same setup for dev and prod
For microservices, composition etc I won't repost on this.
For containet resource allocation:
Docker run has various resource control options (using google cgroups) see my gist here
https://gist.github.com/afolarin/15d12a476e40c173bf5f
I've heard about Docker some days ago and wanted to go across.
But in fact, I don't know what is the purpose of this "container"?
What is a container?
Can it replace a virtual machine dedicated to development?
What is the purpose, in simple words, of using Docker in companies? The main advantage?
VM: Using virtual machine (VM) software, for example, Ubuntu can be installed inside a Windows. And they would both run at the same time. It is like building a PC, with its core components like CPU, RAM, Disks, Network Cards etc, within an operating system and assemble them to work as if it was a real PC. This way, the virtual PC becomes a "guest" inside an actual PC which with its operating system, which is called a host.
Container: It's same as above but instead of using an entire operating system, it cut down the "unnecessary" components of the virtual OS to create a minimal version of it. This lead to the creation of LXC (Linux Containers). It therefore should be faster and more efficient than VMs.
Docker: A docker container, unlike a virtual machine and container, does not require or include a separate operating system. Instead, it relies on the Linux kernel's functionality and uses resource isolation.
Purpose of Docker: Its primary focus is to automate the deployment of applications inside software containers and the automation of operating system level virtualization on Linux. It's more lightweight than standard Containers and boots up in seconds.
(Notice that there's no Guest OS required in case of Docker)
[ Note, this answer focuses on Linux containers and may not fully apply to other operating systems. ]
What is a container ?
It's an App: A container is a way to run applications that are isolated from each other. Rather than virtualizing the hardware to run multiple operating systems, containers rely on virtualizing the operating system to run multiple applications. This means you can run more containers on the same hardware than VMs because you only have one copy of the OS running, and you do not need to preallocate the memory and CPU cores for each instance of your app. Just like any other app, when a container needs the CPU or Memory, it allocates them, and then frees them up when done, allowing other apps to use those same limited resources later.
They leverage kernel namespaces: Each container by default will receive an environment where the following are namespaced:
Mount: filesystems, / in the container will be different from / on the host.
PID: process id's, pid 1 in the container is your launched application, this pid will be different when viewed from the host.
Network: containers run with their own loopback interface (127.0.0.1) and a private IP by default. Docker uses technologies like Linux bridge networks to connect multiple containers together in their own private lan.
IPC: interprocess communication
UTS: this includes the hostname
User: you can optionally shift all the user id's to be offset from that of the host
Each of these namespaces also prevent a container from seeing things like the filesystem or processes on the host, or in other containers, unless you explicitly remove that isolation.
And other linux security tools: Containers also utilize other security features like SELinux, AppArmor, Capabilities, and Seccomp to limit users inside the container, including the root user, from being able to escape the container or negatively impact the host.
Package your apps with their dependencies for portability: Packaging an application into a container involves assembling not only the application itself, but all dependencies needed to run that application, into a portable image. This image is the base filesystem used to create a container. Because we are only isolating the application, this filesystem does not include the kernel and other OS utilities needed to virtualize an entire operating system. Therefore, an image for a container should be significantly smaller than an image for an equivalent virtual machine, making it faster to deploy to nodes across the network. As a result, containers have become a popular option for deploying applications into the cloud and remote data centers.
Can it replace a virtual machine dedicated to development ?
It depends: If your development environment is running Linux, and you either do not need access to hardware devices, or it is acceptable to have direct access to the physical hardware, then you'll find a migration to a Linux container fairly straight forward. The ideal target for a docker container are applications like web based API's (e.g. a REST app), which you access via the network.
What is the purpose, in simple words, of using Docker in companies ? The main advantage ?
Dev or Ops: Docker is typically brought into an environment in one of two paths. Developers looking for a way to more rapidly develop and locally test their application, and operations looking to run more workload on less hardware than would be possible with virtual machines.
Or Devops: One of the ideal targets is to leverage Docker immediately from the CI/CD deployment tool, compiling the application and immediately building an image that is deployed to development, CI, prod, etc. Containers often reduce the time to move the application from the code check-in until it's available for testing, making developers more efficient. And when designed properly, the same image that was tested and approved by the developers and CI tools can be deployed in production. Since that image includes all the application dependencies, the risk of something breaking in production that worked in development are significantly reduced.
Scalability: One last key benefit of containers that I'll mention is that they are designed for horizontal scalability in mind. When you have stateless apps under heavy load, containers are much easier and faster to scale out due to their smaller image size and reduced overhead. For this reason you see containers being used by many of the larger web based companies, like Google and Netflix.
Same questions were hitting my head some days ago and what i found after getting into it, let's understand in very simple words.
Why one would think about docker and containers when everything seems fine with current process of application architecture and development !!
Let's take an example that we are developing an application using nodeJs , MongoDB, Redis, RabbitMQ etc services [you can think of any other services].
Now we face these following things as problems in application development and shipping process if we forget about existence of docker or other alternatives of containerizing applications.
Compatibility of services(nodeJs, mongoDB, Redis, RabbitMQ etc.) with OS(even after finding compatible versions with OS, if something unexpected happens related to versions then we need to relook the compatibility again and fix that).
If two system components requires a library/dependency with different versions in application in OS(That need a relook every time in case of an unexpected behaviour of application due to library and dependency version issue).
Most importantly , If new person joins the team, we find it very difficult to setup the new environment, person has to follow large set of instructions and run hundreds of commands to finally setup the environment And it takes time and effort.
People have to make sure that they are using right version of OS and check compatibilities of services with OS.And each developer has to follow this each time while setting up.
We also have different environment like dev, test and production.If One developer is comfortable using one OS and other is comfortable with other OS And in this case, we can't guarantee that our application will behave in same way in these two different situations.
All of these make our life difficult in process of developing , testing and shipping the applications.
So we need something which handles compatibility issue and allows us to make changes and modifications in any system component without affecting other components.
Now we think about docker because it's purpose is to
containerise the applications and automate the deployment of applications and ship them very easily.
How docker solves above issues-
We can run each service component(nodeJs, MongoDB, Redis, RabbitMQ) in different containers with its own dependencies and libraries in the same OS but with different environments.
We have to just run docker configuration once then all our team developers can get started with simple docker run command, we have saved lot of time and efforts here:).
So containers are isolated environments with all dependencies and
libraries bundled together with their own process and networking
interfaces and mounts.
All containers use the same OS resources
therefore they take less time to boot up and utilise the CPU
efficiently with less hardware costs.
I hope this would be helpful.
Why use docker:
Docker makes it really easy to install and running software without worrying about setup or dependencies. Docker is really made it easy and really straight forward for you to install and run software on any given computer not just your computer but on web servers as well or any cloud based computing platform. For example when I went to install redis in my computer by using bellow command
wget http://download.redis.io/redis-stable.tar.gz
I got error,
Now I could definitely go and troubleshoot this install that program and then try installing redis again, and I kind of get into endless cycle of trying to do all bellow troubleshooting as you I am installing and running software.
Now let me show you how easy it is to run read as if you are making use of Docker instead. just run the command docker run -it redis, this command will install docker without any error.
What docker is:
To understand what is docker you have to know about docker Ecosystem.
Docker client, server, Machine, Images, Hub, Composes are all projects tools pieces of software that come together to form a platform where ecosystem around creating and running something called containers, now if you run the command docker run redis something called docker CLI reached out to something called the Docker Hub and it downloaded a single file called an image.
An image is a single file containing all the dependencies and all the configuration required to run a very specific program, for example redis this which is what the image that you just downloaded was supposed to run.
This is a single file that gets stored on your hard drive and at some point time you can use this image to create something called a container.
A container is an instance of an image and you can kind of think it as being like a running program with it's own isolated set of hardware resources so it kind of has its own little set or its own little space of memory has its own little space of networking technology and its own little space of hard drive space as well.
Now lets examine when you give bellow command:
sudo docker run hello-world
Above command will starts up the docker client or docker CLI, Docker CLI is in charge of taking commands from you kind of doing a little bit of processing on them and then communicating the commands over to something called the docker server, and docker server is in charge of the heavy lifting when we ran the command Docker run hello-world,
That meant that we wanted to start up a new container using the image with the name of hello world, the hello world image has a tiny tittle program inside of it whose sole purpose or sole job is to print out the message that you see in the terminal.
Now when we ran that command and it was issued over to the docker server a series of actions very quickly occurred in background. The Docker server saw that we were trying to start up a new container using an image called hello world.
The first thing that the docker server did was check to see if it already had a local copy like a copy on your personal machine of the hello world image or that hello world file.So the docker server looked into something called the image cache.
Now because you and I just installed Docker on our personal computers that image cache is currently empty, We have no images that have already been downloaded before.
So because the image cache was empty the docker server decided to reach out to a free service called Docker hub. The Docker Hub is a repository of free public images that you can freely download and run on your personal computer. So Docker server reached out to Docker Hub and and downloaded the hello world file and stored it on your computer in the image-cache, where it can now be re-run at some point the future very quickly without having to re-downloading it from the docker hub.
After that the docker server will use it to create an instance of a container, and we know that a container is an instance of an image, its sole purpose is to run one very specific program. So the docker server then essentially took that image file from image cache and loaded it up into memory to created a container out of it and then ran a single program inside of it. And that single programs purpose was to print out the message that you see.
What a container is:
A container is a process or a set of processes that have a grouping of resource specifically assigned to it, in the bellow is a diagram that anytime that we think about a container we've got some running process that sends a system call to a kernel, the kernel is going to look at that incoming system call and direct it to a very specific portion of the hard drive, the RAM, CPU or what ever else it might need and a portion of each of these resources is made available to that singular process.
Let me try to provide as simple answers as possible:
But in fact, I don't know what is the purpose of this "container"?
What is a container?
Simply put: a package containing software. More specifically, an application and all its dependencies bundled together. A regular, non-dockerised application environment is hooked directly to the OS, whereas a Docker container is an OS abstraction layer.
And a container differs from an image in that a container is a runtime instance of an image - similar to how objects are runtime instances of classes in case you're familiar with OOP.
Can it replace a virtual machine dedicated to development?
Both VMs and Docker containers are virtualisation techniques, in that they provide abstraction on top of system infrastructure.
A VM runs a full “guest” operating system with virtual access to host resources through a hypervisor. This means that the VM often provides the environment with more resources than it actually needs In general, VMs provide an environment with more resources than most applications need. Therefore, containers are a lighter-weight technique. The two solve different problems.
What is the purpose, in simple words, of using Docker in companies?
The main advantage?
Containerisation goes hand-in-hand with microservices. The smaller services that make up the larger application are often tested and run in Docker containers. This makes continuous testing easier.
Also, because Docker containers are read-only they enforce a key DevOps principle: production services should remain unaltered
Some general benefits of using them:
Great isolation of services
Great manageability as containers contain everything the app needs
Encapsulation of implementation technology (in the containers)
Efficient resource utilisation (due to light-weight os virtualisation) in comparison to VMs
Fast deployment
If you don't have any prior experience with Docker this answer will cover the basics needed as a developer.
Docker has become a standard tool for DevOps as it is an effective application to improve operational efficiencies. When you look at why Docker was created and why it is very popular, it is mostly for its ability to reduce the amount of time it takes to set up the environments where applications run and are developed.
Just look at how long it takes to set up an environment where you have React as the frontend, a node and express API for backend, which also needs Mongo. And that's just to start. Then when your team grows and you have multiple developers working on the same front and backend and therefore they need to set up the same resources in their local environment for testing purposes, how can you guarantee every developer will run the same environment resources, let alone the same versions? All of these scenarios play well into Docker's strengths where it's value comes from setting containers with specific settings, environments and even versions of resources. Simply type a few commands to have Docker set up, install, and run your resources automatically.
Let's briefly go over the main components. A container is basically where your application or specific resource is located. For example, you could have the Mongo database in one container, then the frontend React application, and finally your node express server in the third container.
Then you have an image, which is from what the container is built. The images contains all the information that a container needs to build a container exactly the same way across any systems. It's like a recipe.
Then you have volumes, which holds the data of your containers. So if your applications are on containers, which are static and unchanging, the data that change is on the volumes.
And finally, the pieces that allow all these items to speak is networking. Yes, that sounds simple, but understand that each container in Docker have no idea of the existence of each container. They're fully isolated. So unless we set up networking in Docker, they won't have any idea how to connect to one and another.
There are really good answers above which I found really helpful.
Below I had drafted a simpler answer:
Reasons to dockerize my web application?
a. One OS for multiple applications ( Resources are shared )
b. Resource manangement ( CPU / RAM) is efficient.
c. Serverless Implementation made easier -Yes, AWS ECS with Fargate, But serverless can be achieved with Lamdba
d. Infra As Code - Agree, but IaC can be achieved via Terraforms
e. "It works in my machine" Issue
Still, below questions are open when choosing dockerization
A simple spring boot application
a. Jar file with size ~50MB
b. creates a Docker Image ~500MB
c. Cant I simply choose a small ec2 instance for my microservices.
Financial Benefits (reducing the individual instance cost) ?
a. No need to pay for individual OS subscription
b. Is there any monetary benefit like the below implementation?
c. let say select t3.2xlarge ( 8 core / 32 GB) and start 4-5 docker images ?