Ans: Docker is a containerization platform which packages your application and all its dependencies together in the form of containers so as to ensure that your application works seamlessly in any environment be it development or test or production.Now you should explain Docker containers.Docker containers, wrap a piece of software in a complete filesystem that contains everything needed to run: code, runtime, system tools, system libraries etc. anything that can be installed on a server. This guarantees that the software will always run the same,regardless of its environment.You can refer the diagram shown below, as you can see that containers run on a single machine share the same operating system kernel, they start instantly as only apps need to start as the kernel is already running and uses less RAM.
Note:Unlike Virtual Machines which has its own OS Docker containers uses the host OS
As you have mentioned about Virtual Machines in your previous answer so the next question in this Docker Interview Questions blog will be related to the differences between the two.
Ans: Docker image is the source of Docker container. In other words, Docker images are used to create containers. Images are created with the build command, and they’ll produce a container when started with run. Images are stored in a Docker registry such as registry.hub.docker.com because they can become quite large, images are designed to be composed of layers of other images, allowing a minimal amount of data to be sent when transferring images over the network.
Tip: Be aware of Dockerhub in order to answer questions on pre-available images.
Ans: This is a very important question so just make sure you don’t deviate from the topic and I will advise you to follow the below mentioned format:Docker containers include the application and all of its dependencies, but share the kernel with other containers, running as isolated processes in user space on the host operating system. Docker containers are not tied to any specific infrastructure: they run on any computer, on any infrastructure, and in any cloud.
Now explain how to create a Docker container, Docker containers can be created by either creating a Docker image and then running it or you can use Docker images that are present on the Dockerhub. Docker containers are basically runtime instances of Docker images.
Ans: Docker hub is a cloud-based registry service which allows you to link to code repositories, build your images and test them, stores manually pushed images, and links to Docker cloud so you can deploy images to your hosts. It provides a centralized resource for container image discovery, distribution and change management, user and team collaboration, and workflow automation throughout the development pipeline.
Ans: Docker containers are easy to deploy in a cloud. It can get more applications running on the same hardware than other technologies, it makes it easy for developers to quickly create, ready-to-run containerized applications and it makes managing and deploying applications much easier. You can even share containers with your applications.
If you have some more points to add you can do that but make sure the above the above explanation is there in your answer.
Ans: You should start this answer by explaining Docker Swarn.
Docker Swarm is native clustering for Docker. It turns a pool of Docker hosts into a single, virtual Docker host. Docker Swarm serves the standard Docker API, any tool that already communicates with a Docker daemon can use Swarm to transparently scale to multiple hosts.
I will also suggest you to include some supported tools:
Ans: Docker can build images automatically by reading the instructions from a Dockerfile.
Now I will suggest you to give a small definition of Dockerfle.
A Dockerfile is a text document that contains all the commands a user could call on the command line to assemble an image. Using docker build users can create an automated build that executes several command-line instructions in succession.
Ans: You can use json instead of yaml for your compose file, to use json file with compose, specify the filename to use for eg:
docker-compose -f docker-compose.json up
Ans: Explain how you have used Docker to help rapid deployment. Explain how you have scripted Docker and used Docker with other tools like Puppet, Chef or Jenkins.
If you have no past practical experience in Docker and have past experience with other tools in a similar space, be honest and explain the same. In this case, it makes sense if you can compare other tools to Docker in terms of functionality.
Ans: I will suggest you to give a direct answer to this.
We can use Docker image to create Docker container by using the below command:
| docker run -t -i command name |
This command will create and start a container.
You should also add, If you want to check the list of all running container with the status on a host use the below command:
| docker ps -a |
Ans: In order to stop the Docker container you can use the below command:
| docker stop container ID |
Now to restart the Docker container you can use:
| docker restart container ID |
Ans: Large web deployments like Google and Twitter, and platform providers such as Heroku and dotCloud all run on container technology, at a scale of hundreds of thousands or even millions of containers running in parallel.
Ans: I will start this answer by saying Docker runs on only Linux and Cloud platforms and then I will mention the below vendors of Linux:
Cloud:
Note that Docker does not run on Windows or Mac.
Ans: You can answer this by saying, no I won’t lose my data when Docker container exits, any data that your application writes to disk gets preserved in its container until you explicitly delete the container. The file system for the container persists even after the container halts.
Ans: No, it is not. Different variations of containers technology were out there in *NIX world for a long time.Examples are:-Solaris container (aka Solaris Zones)-FreeBSD Jails-AIX Workload Partitions (aka WPARs)-Linux OpenVZ
Docker can run on any infrastructure, you can run docker on your laptop or you can run it in the cloud.
Docker has a Container HUB, it is basically a repository of containers which you can download and use. You can even share containers with your applications.
Docker is quite well documented.
Ans: Docker container is the runtime instance of docker image.
Docker Image does not have a state and its state never changes as it is just set of files whereas docker container has its execution state.
Ans: Well, I think, docker is extremely useful in development environments. Especially for testing purposes. You can deploy and re-deploy apps in a blink of eye.
Also, I believe there are use cases where you can use Docker in production. Imagine you have some Node.js application providing some services on web.
Eventually, if docker is good or not should be decided on an application basis. For some apps it can be sufficient, for others not.
Ans: To run an application in virtualized environment (e.g. vSphere), we first need to create a VM, install an OS inside and only then deploy the application.To run same application in docker all you need is to deploy that application in Docker. There is no need of additional OS layer. You just deploy the application with its dependent libraries, the rest (kernel, etc.) is provided by Docker engine.This table from a Docker official website shows it in a quite clear way.
Ans: Just fire docker ps –a to list out all running container with stauts (running or stopped) on a host21.How to stop and restart the container?
To stop container, we can use docker stop <container id>
To start a stopped container,docker start <container id>is the command
To restart a running container,docker restart <container id>
Ans: I came across Docker not long after Solomon open sourced it. I knew a bit about LXC and containers (a past life includes working on Solaris Zones and LPAR on IBM hardware too), and so I decided to try it out. I was blown away by how easy it was to use. My prior interactions with containers had left me with the feeling they were complex creatures that needed a lot of tuning and nurturing. Docker just worked out of the box. Once I saw that and then saw the CI/CD-centric workflow that Docker was building on top I was sold.
Ans: I think it’s the lightweight nature of Docker combined with the workflow. It’s fast, easy to use and a developer-centric DevOps-ish tool. Its mission is basically: make it easy to package and ship code. Developers want tools that abstract away a lot of the details of that process. They just want to see their code working. That leads to all sorts of conflicts with Sys Admins when code is shipped around and turns out not to work somewhere other than the developer’s environment. Docker turns to work around that by making your code as portable as possible and making that portability user friendly and simple.
Ans: It’s definitely the build pipeline. I mean I see a lot of folks doing hyper-scaling with containers, indeed you can get a lot of containers on a host and they are blindingly fast. But that doesn’t excite me as much as people using it to automate their dev-test-build pipeline.
Ans: Docker is operating system level virtualization. Unlike hypervisor virtualization, where virtual machines run on physical hardware via an intermediation layer (“the hypervisor”), containers instead run user space on top of an operating system’s kernel. That makes them very lightweight and very fast.
Ans: I think open source software is closely tied to cloud computing. Both in terms of the software running in the cloud and the development models that have enabled the cloud. Open source software is cheap, it’s usually low friction both from an efficiency and a licensing perspective.
Ans: I think there are a lot of workloads that Docker is ideal for, as I mentioned earlier both in the hyper-scale world of many containers and in the dev-test-build use case. I fully expect a lot of companies and vendors to embrace Docker as an alternative form of virtualization on both bare metal and in the cloud.
As for cloud technology’s trajectory. I think we’ve seen significant change in the last couple of years. I think they’ll be a bunch more before we’re done. The question of OpenStack and whether it will succeed as an IAAS alternative or DIY cloud solution. I think we’ve only touched on the potential for PAAS and there’s a lot of room for growth and development in that space. It’ll also be interesting to see how the capabilities of PAAS products develop and whether they grow to embrace or connect with consumer cloud-based products.
Ans: It’s very much a crash course introduction to Docker. It’s aimed at Developers and SysAdmins who want to get started with Docker in a very hands on way. We’ll teach the basics of how to use Docker and how to integrate it into your daily workflow.
Ans: That’s mostly a joke related to my partner. Like a lot of geeks, I’m often on my computer, tapping away at a problem or writing something. My partner jokes that I have two jobs: my “real” job and my open source job. Thankfully over the last few years, at places like Puppet Labs and Docker, I’ve been able to combine my passion with my paycheck.
Ans: It’s OSCON time again, and this year the tech sector is abuzz with talk of cloud infrastructure. One of the more interesting startups is Docker, an ultra-lightweight containerization app that’s brimming with potential
I caught up with the VP of Services for Docker, James Turnbull, who’ll be running a Docker crash course at the con. Besides finding out what Docker is anyway, we discussed the cloud, open source contributing, and getting a real job.
Your bio says “for a real job” you’re the VP of Services for Docker. Do you consider your other open source work a hobby?
That’s mostly a joke related to my partner. Like a lot of geeks, I’m often on my computer, tapping away at a problem or writing something. My partner jokes that I have two jobs: my “real” job and my open source job. Thankfully over the last few years, at places like Puppet Labs and Docker, I’ve been able to combine my passion with my paycheck.
Ans: Compose stop attempts to stop a container by sending a SIGTERM. It then waits for a default timeout of 10 seconds. After the timeout, a SIGKILL is sent to the container to forcefully kill it. If you are waiting for this timeout, it means that your containers aren’t shutting down when they receive the SIGTERM signal.
There has already been a lot written about this problem of processes handling signals in containers.
To fix this problem, try the following:
Make sure you’re using the JSON form of CMD and ENTRYPOINT in your Dockerfile.
For example use ["program", "arg1", "arg2"] not"program arg1 arg2". Using the string form causes Docker to run your process using bash which doesn’t handle signals properly. Compose always uses the JSON form, so don’t worry if you override the command or entrypoint in your Compose file.
Ans: Compose uses the project name to create unique identifiers for all of a project’s containers and other resources. To run multiple copies of a project, set a custom project name using the -p command line option or theCOMPOSE_PROJECT_NAME environment variable.
Ans: Typically, you want docker-compose up. Use up to start or restart all the services defined in a docker-compose.yml. In the default “attached” mode, you’ll see all the logs from all the containers. In “detached” mode (-d), Compose exits after starting the containers, but the containers continue to run in the background.
The docker-compose run command is for running “one-off” or “adhoc” tasks. It requires the service name you want to run and only starts containers for services that the running service depends on. Use run to run tests or perform an administrative task such as removing or adding data to a data volume container. The run command acts like docker run -ti in that it opens an interactive terminal to the container and returns an exit status matching the exit status of the process in the container.
The docker-compose start command is useful only to restart containers that were previously created, but were stopped. It never creates new containers.
Ans: Yes. Yaml is a superset of json so any JSON file should be valid Yaml. To use a JSON file with Compose, specify the filename to use, for example:
docker-compose -f docker-compose.json up
Ans: You can add your code to the image using COPY or ADD directive in a Dockerfile. This is useful if you need to relocate your code along with the Docker image, for example when you’re sending code to another environment (production, CI, etc).
You should use a volume if you want to make changes to your code and see them reflected immediately, for example when you’re developing code and your server supports hot code reloading or live-reload.
There may be cases where you’ll want to use both. You can have the image include the code using a COPY, and use a volume in your Compose file to include the code from the host during development. The volume overrides the directory contents of the image.
Ans: There are many examples of Compose files on github.
Compose documentation:
Ans: Last year, we encountered an organization that developed a modular application while allowing developers to “use what they want” to build individual components. It was a nice concept but a total organizational nightmare — chasing the ideal of modular design without considering the impact of this complexity on their operations.
The organization was then interested in Docker to help facilitate deployments, but we strongly recommended that this organization not use Docker before addressing the root issues. Making it easier to deploy these disparate applications wouldn’t be an antidote to the difficulties of maintaining several different development stacks for long-term maintenance of these apps.
Ans: Chances are that your application already has a framework for shipping logs and backing up data to the right places at the right times. To implement Docker, you not only need to replicate the logging behavior you expect in your virtual machine environment, but you also need to prepare your compliance or governance team for these changes. New tools are entering the Docker space all the time, but many do not match the stability and maturity of existing solutions. Partial updates, rollbacks and other common deployment tasks may need to be reengineered to accommodate a containerized deployment.
If it’s not broken, don’t fix it. If you’ve already invested the engineering time required to build a continuous integration/continuous delivery (CI/CD) pipeline, containerizing legacy apps may not be worth the time investment.
Ans: At AWS Re:Invent last month, Amazon chief technology officer Werner Vogels spent a significant portion of his keynote on AWS Lambda, an automation tool that deploys infrastructure based on your code. While Vogels did mention AWS’ container service, his focus on Lambda implies that he believes dealing with zero infrastructure is preferable to configuring and deploying containers for most developers.
Containers are rapidly gaining popularity in the enterprise, and are sure to be an essential part of many professional CI/CD pipelines. But as technology experts and CTOs, it is our responsibility to challenge new methodologies and services and properly weigh the risks of early adoption. I believe Docker can be extremely effective for organizations that understand the consequences of containerization — but only if you ask the right questions.
Ans: Docker uses cache to speed up builds significantly. Every command in Dockerfile is build in another docker container and it’s results are stored in separate layer. Layers are built on top of each other.
Docker scans Dockerfile and try to execute each steps one after another, before executing it probes if this layer is already in cache. When cache is hit, building step is skipped and from user perspective is almost instant.
When you build your Dockerfile in a way that the most changing things such as application source code are on the bottom, you would experience instant builds.
You can learn more about caching in docker in this article.
Another way of amazingly fast building docker images is using good base image – which you specify inFROMcommand, you can then only make necessary changes, not rebuild everything from scratch. This way, build will be quicker. It’s especially beneficial if you have a host without the cache like Continuous Integration server.
Summing up, building docker images with Dockerfile is faster than provisioning with ansible, because of using docker cache and good base images. Moreover you can completely eliminate provisioning, by using ready to use configured images such stgresus.
$ docker run --name some-postgres -d postgres No installing postgres at all - it's ready to run.
Also you mention that docker allows multiple apps to run on one server.
It depends on your use case. You probably should split different components into separate containers. It will give you more flexibility.
Docker is very lightweight and running containers is cheap, especially if you store them in RAM – it’s possible to spawn new container for every http callback, however it’s not very practical.
At work I develop using set of five different types of containers linked together.
In production some of them are actually replaced by real machines or even clusters of machine – however settings on application level don’t change.
Here you can read more about linking containers.
It’s possible, because everything is communicating over the network. When you specify links in dockerrun command – docker bridges containers and injects environment variables with information about IPs and ports of linked childreninto the parent container.
This way, in my app settings file, I can read those values from environment. In python it would be:
import os VARIABLE = os.environ.get('VARIABLE')
There is a tool which greatly simplifies working with docker containers, linking included. It’s called fig and you can read more about it here.
It depends how your production environment looks like.
Example deploy process may look like this:
-Build an app using docker build . in the code directory.
-Test an image.
-Push the new image out to registry docker push myorg/myimage.
-Notify remote app server to pull image from registry and run it (you can also do it directly using some configuration management tool).
-Swap ports in a http proxy.
-Stop the old container.
You can consider using amazon elastic beanstalk with docker or dokku.
Elastic beanstalk is a powerful beast and will do most of deployment for you and provide features such as autoscaling, rolling updates, zero deployment deployments and more.
Dokku is very simple platform as a service similar to heroku.
Ans: Docker is an open platform that both IT operations teams and Developer team use to build, ship and run their applications, giving them the agility, portability and control that each team requires across the software supply chain. We have created a standard Docker container that packages up an application, with everything that the applications requires to run. This standardization allows teams to containerize applications and run them in any environment, on any infrastructure and to be written in any language.
Ans: Containerization is very different from virtualization. It starts with the Docker engine, the tool that creates and runs containers (1 or more), and is the Docker installed software on any physical, virtual or cloud host with a compatible OS. Containerization leverages the kernel within the host operating system to run multiple root file systems. We call these root file systems “containers.” Each container shares the kernel within the host OS, allowing you to run multiple Docker containers on the same host. Unlike VMs, containers do not have an OS within it. They simply share the underlying kernel with the other containers. Each container running on a host is completely isolated so applications running on the same host are unaware of each other (you can use Docker Networking to create a multi-host overlay network that enables containers running on hosts to speak to one another).
The image below shows containerization on the left and virtualization on the right. Notice how containerization (left), unlike virtualization (right) does not require a hypervisor or multiple OSs.
Docker containers and traditional VMs are not mutually exclusive, so no, containers do not have to replace VMs. Docker containers can actually run within VMs. This allows teams to containerize each service and run multiple Docker containers per vm.
Ans: By Dockerizing their environment enterprise teams can leverage the Docker Containers as a Service Platform (CaaS). CaaS gives development teams and IT operations teams agility, portability and control within their environment.
Developers love Docker because it gives them the ability to quickly build and ship applications. Since Docker containers are portable and can run in any environment (with Docker Engine installed on physical, virtual or cloud hosts), developers can go from dev, test, staging and production seamlessly, without having to recode. This accelerates the application lifecycle and allows them to release applications 13x more often. Docker containers also makes it super easy for developers to debug applications, create an updated image and quickly ship an updated version of the application.
IT Ops teams can manage and secure their environment while allowing developers to build and ship apps in a self-service manner. The Docker CaaS platform is supported by Docker, deploys on-premises and is chock full of enterprise security features like role-based access control, integration with LDAP/AD, image signing and many more.
In addition, IT ops teams have the ability to manage deploy and scale their Dockerized applications across any environment. For example, the portability of Docker containers allows teams to migrate workloads running in AWS over to Azure, without having to recode and with no downtime. Team cans also migrate workloads from their cloud environment, down to their physical datacenter, and back. This enables teams to utilize the best infrastructure for their business needs, rather than being locked into a particular infrastructure type.
The lightweight nature of Docker containers compared to traditional tools like virtualization, combined with the ability for Docker containers to run within VMs, allowing teams to optimize their infrastructure by 20X, and save money in the process.
Ans: The Docker engine is the software that is installed on the host (bare metal server, VM or public cloud instance) and is the only “Docker infrastructure” you’ll need. The tool creates, runs and manages Docker containers. So actually, there is no hardware installation necessary at all.
The Docker Engine itself is very lightweight, weighing in around 80 MB total.
Ans: A Dockerized node is anything i.e a bare metal server, VM or public cloud instance that has the Docker Engine installed and running on it.
Docker can manage nodes that exist on-premises as well as in the cloud. Docker Datacenter is an on-premises solution that enterprises use to create, manage, deploy and scale their applications and comes with support from the Docker team. It can manage hosts that exist in your datacenter as well as in your virtual private cloud or public cloud provider (AWS, Azure, Digital Ocean, SoftLayer etc.).
Ans: Docker containers do not package up the OS. They package up the applications with everything that the application needs to run. The engine is installed on top of the OS running on a host. Containers share the OS kernel allowing a single host to run multiple containers.
Ans: The Docker Engine runs on all modern Linux distributions. We also provide a commercially supported Docker Engine for Ubuntu, CentOS, OpenSUSE, RHEL. There is also a technical preview of Docker running on Windows Server 2016.
Ans: Docker isn’t focused on managing your infrastructure. The platform, which is infrastructure agnostic, manages your applications and helps ensure that they can run smoothly, regardless of infrastructure type via solutions like Docker Datacenter. This gives your company the agility, portability and control you require. Your team is responsible for managing the actual infrastructure.
Ans: As far as the number of containers that can be run, this really depends on your environment. The size of your applications as well as the amount of available resources (i.e like CPU) will all affect the number of containers that can be run in your environment. Containers unfortunately are not magical. They can’t create new CPU from scratch. They do, however, provide a more efficient way of utilizing your resources. The containers themselves are super lightweight (remember, shared OS vs individual OS per container) and only last as long as the process they are running. Immutable infrastructure if you will.
Ans: The best way for your team to get started is for your developers to download Docker for Mac or Docker Windows. These are native installations of Docker on a Mac or Windows device. From their, developers will take their applications and create a Dockerfile. The Dockerfile is where all of the application configuration is specified. It is essentially the blueprint for the Docker Image. The image is a snapshot of your application and is what the Docker Engine looks at so it knows what the container it is spinning up should look like.
Ans: I added this in because this is one of the biggest misconceptions about Docker. Docker can absolutely be used for to containerize monolithic apps as well as microservices based apps. We find that most customers who are leveraging Docker containerize their legacy monolithic applications to benefit from the isolation that Docker containers provide, as well as portability. Remember Docker containers can package up any application (monolithic or distributed) and migrate workloads to any infrastructure. This portability is what enables our enterprise customers to embrace strategies like moving to the hybrid cloud.
In the case of microservices, customers typically containerize each service and use tools like Docker Compose to deploy these multi-container distributed applications into their production environment as a single running application.
We’ve even seen some companies have a hybrid environment where they are slowly restructuring their dockerized monolithic applications to become dockerized distributed applications over time.