I have a question regarding using docker for testing.
Our main solution is a client/server solution. However, the same server is also being used by our web applications. We know that our web applications, server and SQL Database can run in docker container, as it is today.
All our customers are currently running our web applications and server on either physical servers, or virtual machines.
From my knowledge that is obtained from the docker website, docker courses and the following stackoverflow post, there is a difference between a Virtual Machine and a Docker container.
But could there be such a big difference that our automated testing would have a different output or unable to catch errors in a docker container compared to a virtual machine?
From my understanding the main difference is that containers runs on host os, and VM's runs on its own instance of a OS. So, from my view the difference is not big enough to change the output of our testing in anyway?
Setup
Our container setup would be the exact same as it is in our VM testing environment
MS-SQL Server container
Server container (Windows container)
IIS Container
The differences between VM and container is usually visible from the management perspective e.g. different resource requirements or security concerns. From the client perspective there should be no difference. If the aplication uses well defined network interfaces e.g. Java has JDBC for communicating with the database the change from VM to container should be transparent, just like switching from one VM to another VM.
If the automated testing has different outcome on VM and container it means that either the application depends on something specific in the VM or there is an issue with the test suite. One way or another it should be debugged.
It all depends.
The first question is one of provisioning - you'll need to create the Docker images, install the dependencies, manage configuration settings etc. If that provisioning process is different to the way you provision VMs, it's possible that when you test on Docker, you'll not get the same results as on VMs (or indeed the target production environment). This is especially important for non-functional testing like load and performance testing. It could also affect functional testing, e.g. when configuring database code pages etc.
The second question is whether your applications rely on any operating system features, or display extreme resource requirements. For instance, if your database absolutely must have a certain amount of memory, or your application server needs a custom configuration for network timeouts, this may be hard to reflect on Docker containers.
I'm using Docker I have implemented a system to deploy environments (on a single server) based on Git branches using Traefik (*.dev.domain.com) and Docker Compose templates.
I like Kubernetes and I've never switched to it since I'm limited to one single server for my infrastructure. I've only used it using local installations (Docker for Windows).
So, my question is: does it make sense to run a Kubernetes "cluster" (master and nodes) on a single server to orchestrate and route containers (in place of Traefik/Rancher/Docker Compose)?
This use is for development and staging only for the moment, so high availability is not a prerequisite.
Thanks.
If it is not a production environment, it doesn't matter how many nodes you are using. So yes, it should be just fine in this case. But make sure all the k8s features you will need in production are available in test/dev, to keep things similar and portable.
AFAIU,
I do not see a requirement for kubernetes unless we are doing below at least for single host using native docker run or docker-compose or docker engine swarm mode -
Make sure there are enough(>=2) replicas of your app in a single server and you are balancing the load across those apps docker containers.
If you want to go bit advanced, we should be able to scale up & down dynamically (docker swarm mode supports this out of the box else use jwilder nginx proxy).
Your deployment should not cause a downtime. Make sure a single container is always healthy at any instant of time while deploying.
Container should auto heal(restart automatically) in case your HTTP or TCP health check fails.
Doing all of the above will certainly put you in a better place but single host is still a single source of failure which you got to deal with at regular intervals.
Preferred : if possible try to start with docker engine swarm mode or kubernetes single master or minikube. This will automatically take care of all the above scenarios out of the box and will also allow you to further scale up anytime by adding more nodes without changing much in your YML files for docker swarm or kubernetes.
Ref -
https://kubernetes.io/docs/setup/independent/create-cluster-kubeadm/
https://docs.docker.com/engine/swarm/
I would use single host k8s only if I managed clusters with the same project that I would like to deploy to the said host. This enables you to reuse manifests and all the automation you've created for your clusters.
Have I had single host environments only, I would probably stick to docker-compose.
If you're looking to try it out your easiest options are probably minikube (easy to run single-node cluster locally but without some features) or using one of the free trial accounts for a managed Kubernetes service from one of the big cloud providers (fully-featured and multi-node but limited use before you have to pay).
Good day
We have a development environment that consists of 6 virtual machines. Currently we are using Vagrant and Ansible with VirtualBox.
As you can imagine, hosting this environment is a maintenance nightmare particularly as versions of software/OS change. Not too mention resource load for developer machines.
We have started migrating some virtual machines to docker. But this itself poses problems around orchestration, correct configurations, communication etc. This led me to Kubernetes.
Would someone be so kind as to provide some reasoning as to whether Kubernetes would or wouldn't be the right tool for the job? That is managing and orchestrating 'development' docker containers.
Thanks
This is quite complex topic and many things have to be considered if it's worth to use k8s as local dev environment. Especially I used it when I wanted to have my local developer environment very close to production one which was running on Kubernetes. This helped to avoid many configuration bugs.
In my opinion Kubernetes(k8s) will provide you all you need for a development environment.
It gives you much flexibility and does much configuration itself. Few examples:
An easy way to deploy new version into local kubernetes stack
You prepare k8s replication controller files for each of your application module (keep in mind that they need to be stateless modules)
In replication controller you specify the docker image and that's it.
Using this approach you can push new docker images to local docker_registry and then using kubectl control the lifecycle of your application.
Easy way to scale your application modules
For example:
kubectl scale rc your_application_service --replicas=3
This way k8s will check how many pods you have running for your service and if it recognises that the number is smaller then the replicas value it will create new to satisfy the replicas number.
It's endless topic and many other things come to my mind, but I would suggest you to try it out.
There is a https://github.com/kubernetes/kubernetes/blob/master/docs/devel/developer-guides/vagrant.md project for running the k8s cluster in vagrant.
Of course you have to remember that if you have many services all of them have to be pushed to local repository and run by k8s. This will require some time but if you automate local deploy with some custom scripts you won't regret.
As wsl mentioned before, it is a quite complex topic. But i'm doing this as well at the moment. So let me summaries some things for you:
With Kubernetes (k8s) you're going to orchestrate your SaaS Application. In best case, it is a Cloud-native Application. The properties/requirements for a Cloud-native Application are formulated by the Cloud Native Computing Foundation (CNCF), which basically were formed around k8s, after Google donates it to the Linux Foundation.
So the properties/requirements for a Cloud-native Application are: Container packaged, Dynamically managed and Micro-services oriented (cncf.io/about/charter). You will benefit mostly from k8s, if your applications are micro-service based and every service has a separate container.
With micro-service based applications, every service can be developed independently. The developer only needs to follow the 12Factor Method (12factor.net) for example (use env var instead of hard coded IP addresses, etc).
In the next step the developer build the container for a service and pushes it the a container registry. For a local develop environment, you may need to run a container registry inside the cluster as well, so the developer can push and test his code locally.
Then you're able to define your k8s replication-controllers, services, PetSets, etc. with Ports, Port-mapping, env vars, Container Images... and create and run it inside the cluster.
The k8s-documentation recommend Minikube for running k8s locally (kubernetes.io/docs/getting-started-guides/minikube/). With Minikube you got features like DNS, NodePorts, ConfigMaps and Secrets
Dashboards.
But I choose the multi node CoreOS Kubernetes with Vagrant Cluster for my Development Environment as Puja Abbassi mentioned in the Blog "Finding The Right Local Kubernetes Development Environment" (https://deis.com/blog/2016/local-kubernetes-development-environment/), it is closer to the my production environment (12Factor: 10 - Dev/prod parity).
With the Vagrant Environment you got features like:
Networking with flannel
Service Discovery with etcd
DNS names for a set of containers with SkyDNS
internal load balancing
If you want to know, how everything works look inside this Github repo github.com/coreos/coreos-kubernetes/tree/master/multi-node (vagrant and generic folder).
So you have to ask yourself, if you or your developers really need to run a complete "cloud environment" locally. In many cases a developer can develop a service (based on micro-services and containers) independently.
But sometimes it is necessary to have multiple or all services run on your local machine as a dev-environment.
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 ?
I want to migrate my current deploy to docker, it counts on a mongodb service, a redis service, a pg server and a rails app, I have created already a docker container for each but i have doubts when it comes to start and linking them. Under development I'm using fig but I think it was not meant to be used on production. In order to take my deployment to production level, what mechanism should I use to auto-start and link containers together? my deploy uses a single docker host that already runs Ubuntu so i can't use CoreOS.
Linknig containers in production is a tricky thing. It will hardwire the IP addresses of the dependent containers so if you ever need to restart a container or launch a replacement (like upgrading the version of mongodb) your rails app will not work out of the box with the new container and its new IP address.
This other answer explains some available alternatives to linking.
Regarding starting the containers, you can use any deployment tool to run the required docker commands (Capistrano can easily do that). After that, docker will restart running the containers after a reboot.
You might need a watcher process to restart containers if they die, just as you would have one for a normal rails app.
Services like Tutum and Dockerize.it can make this simpler. As far as I know, Tutum will not deploy to your servers. Dockerize.it will, but is very rough (disclaimer: I'm part of the team building it).
You can convert your fig configuration to CoreOS formatted systemd configuration files with fig2coreos. Google App Engine supports CoreOS, or you can run CoreOS on AWS or your cloud provider of choice. fig2coreos also supports deploying to CoreOS in Vagrant for local development.
CenturyLink (fig2coreos authors) have an example blog post here:
This blog post will show you how to bridge the gap between building
complex multi-container apps using Fig and deploying those
applications into a production CoreOS system.
EDIT: If you are constrained to an existing host OS you can use QEMU ("a generic and open source machine emulator and virtualizer") to host a CoreOS instance. Instructions are available from the CoreOS team.