A small introduction to history. I am building a small service (website) where the user is provided with all sorts of tools that work according to the parameters specified by the user himself. In my implementation, it turns out that the tools are one big script that runs in the docker. It turns out that my service should launch a new docker container for each user.
I was thinking about using "aws fargate" or "gcloud run", or any other resource that makes it possible to run a docker container.
But I'm interested. What if there are 1000 or 10000 users, each one will have its own docker container, is that good? Do the services (aws, gcloud) have any restrictions, or is it a bad implementation?
Based upon my understanding you have suggested that you instantiate a Docker container for each of your users, I think there are a couple of issues with this:
Depending on how many users you have you get into the realms of too many containers. (each container will consume resources, not just Memory and CPU but also TCP/IP pool exhaustion.)
Isolation -> Read containers are not VMs
I have an image in Artifact Registry that does a unit of work:
it expects input files inside a certain directory (let's call it main_input)
runs them, does some sequences of computation, and outputs results into an output folder in Google Storage
The run time of each does not exceed 30 minutes, but I have thousands of such runs to perform.
Inside a single VM, I can create various containers from this image by mounting the main_input directory inside the container to the correct ones on the host, and run.
However, I wonder if Cloud Run is a more scalable solution for this? or shall I look at other services/strategies?
Managing thousands of runs is not an easy task, you can use a scheduler like airflow or argo worfkflows to run the tasks and restart them if needed.
For the containers environment, I propose Kubernetes (GKE) over Cloud Run, for some reason:
you have more permissions than Cloud Run
to be agnostic from GCP (your code can work on other platforms like AWS)
better management for apps configurations and secrets, and supported with all the CI/CD tools
less expensive: you can create scalable preemptible node pools to reduce the cost and add a lot of resources when needed
you can use the same cluster to run other applications for your company
you can use open source tools for log collections, monitoring, HTTP reverse proxy, ...
I'm trying to deploy and run a docker image in a GCP VM instance.
I need it to access a certain Cloud Storage Bucket (read and write).
How do I mount a bucket inside the VM? How do I mount a bucket inside the Docker container running in my VM?
I've been reading google cloud documentation for a while, but I'm still confused. All guides show how to access a bucket from a local machine, and not how to mount it to VM.
https://cloud.google.com/storage/docs/quickstart-gsutil
Found something about Fuse, but it looks overly complicated for just mounting a single bucket to VM filesystem.
Google Cloud Storage is a object storage API, it is not a filesystem. As a result, it isn't really designed to be "mounted" within a VM. It is designed to be highly durable and scalable to extraordinarily large objects (and large numbers of objects).
Though you can use gcsfuse to mount it as a filesystem, that method has pretty significant drawbacks. For example, it can be expensive in operation count to do even simple operations for a normal filesystem.
Likewise, there are many surprising behaviors that are a result of the fact that it is an object store. For example, you can't edit objects -- they are immutable. To give the illusion of writing to the middle of an object, the object is, in effect, deleted and recreated whenever a call to close() or fsync() happens.
The best way to use GCS is to design your application to use the API (or the S3 compatible API) directly. That way the semantics are well understood by the application, and you can optimize for them to get better performance and control your costs. Thus, to access it from your docker container, ensure your container has a way to authenticate through GCS (either through the credentials on the instance, or by deploying a key for a service account with the necessary permissions to access the bucket), then have the application call the API directly.
Finally, if what you need is actually a filesystem, and not specifically GCS, Google Cloud does offer at least 2 other options if you need a large mountable filesystem that is designed for that specific use case:
Persistent Disk, which is the baseline filesystem that you get with a VM, but you can mount many of these devices on a single VM. However, you can't mount them read/write to multiple VMs at once -- if you need to mount to multiple VMs, the persistent disk must be read only for all instances they are mounted to.
Cloud Filestore is a managed service that provides an NFS server in front of a persistent disk. Thus, the filesystem can be mounted read/write and shared across many VMs. However it is significantly more expensive (as of this writing, about $0.20/GB/month vs $0.04/GB/month in us-central1) than PD, and there are minimum size requirements (1TB).
Google Cloud Storage buckets cannot be mounted in Google Compute instances or containers without third-party software such as FUSE. Neither Linux nor Windows have built-in drivers for Cloud Storage.
GCS VM comes with google cloud SDK installed. So without mounting you can copy in and out files using those commands.
gsutil ls gs://
I watched this YouTube video on Docker and at 22:00 the speaker (a Docker product manager) says:
"You're probably thinking 'Docker does not support multi-tenancy'...and you are right!"
But never is any explanation of why actually given. So I'm wondering: what did he mean by that? Why Docker doesn't support multi-tenancy?! If you Google "Docker multi-tenancy" you surprisingly get nothing!
One of the key features most assume with a multi-tenancy tool is isolation between each of the tenants. They should not be able to see or administer each others containers and/or data.
The docker-ce engine is a sysadmin level tool out of the box. Anyone that can start containers with arbitrary options has root access on the host. There are 3rd party tools like twistlock that connect with an authz plugin interface, but they only provide coarse access controls, each person is either allowed or disallowed from an entire class of activities, like starting containers, or viewing logs. Giving users access to either the TLS port or docker socket results in the users being lumped into a single category, there's no concept of groups or namespaces for the users connecting to a docker engine.
For multi-tenancy, docker would need to add a way to define users, and place them in a namespace that is only allowed to act on specific containers and volumes, and restrict options that allow breaking out of the container like changing capabilities or mounting arbitrary filesystems from the host. Docker's enterprise offering, UCP, does begin to add these features by using labels on objects, but I haven't had the time to evaluate whether this would provide a full multi-tenancy solution.
Tough question that others might know how to answer better than me. But here it goes.
Let's take this definition of multi tenancy (source):
Multi-tenancy is an architecture in which a single instance of a software application serves multiple customers.
It's really hard to place Docker in this definition. It can be argued that it's both the instance and the application. And that's where the confusion comes from.
Let's break Docker up into three different parts: the daemon, the container and the application.
The daemon is installed on a host and runs Docker containers. The daemon does actually support multi tenancy, as it can be used my many users on the same system, each of which has their own configuration in ~/.docker.
Docker containers run a single process, which we'll refer to as the application.
The application can be anything. For this example, let's assume the Docker container runs a web application like a forum or something. The forum allows users to sign in and post under their name. It's a single instance that serves multiple customers. Thus it supports multi tenancy.
What we skipped over is the container and the question whether or not it supports multi tenancy. And this is where I think the answer to your question lies.
It is important to remember that Docker containers are not virtual machines. When using docker run [IMAGE], you are creating a new container instance. These instances are ephemeral and immutable. They run a single process, and exit as soon as the process exists. But they are not designed to have multiple users connect to them and run commands simultaneously. This is what multi tenancy would be. Instead, Docker containers are just isolated execution environments for processes.
Conceptually, echo Hello and docker run echo Hello are the same thing in this example. They both execute a command in a new execution environment (process vs. container), neither of which supports multi tenancy.
I hope this answers is readable and answers your question. Let me know if there is any part that I should clarify.
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 ?