Discussing the difference between Docker containers and Virtual Machines

Bachelor seminar

Steven Grzbielok ￭ 12th of August, 2016

About me

Steven Grzbielok• Born in 1994, living in Ratingen• 6th term Information Systems (B.Sc.)• IT-Consultant for MT AG since 2014• Primarly deals with UI-Design

and web development

Agenda

1. What is Docker and what benefits are promised for the usage of Docker?

2.Comparison of an example: VM vs. Docker3.Conclusion: Guidelines

1. What is Docker and what benefits are promised for the usage of Docker?

Motivation

Virtual machines are often called heavyweight and slow.

Is Docker a promising alternative?

What are the differences between both techniques?

Fundamentals

• Virtualization → Dividing a physical computer into several virtual environments

• VM = large files and big processes

• Alternative: Linux containers• Docker: Promised to be lightweight, open,

secure and scalable

Di Liu & Zhao, 2014, p. 475; Bui, 2015, p. 1; Pahl, 2015, pp. 24-25; Docker Inc., 2016h

What is a virtual machine?

Virtualization means the operation of system components in an abstract environment that is

often detached from the hardware and the operating system which is used as a host.

Scalability and portability

Hofer & Fischer, 2008, p. 970

Evolution of VMs

• First virtualization approach from IBM (1960s/1970s) for dividing one physical machine

• First language level approach by Sun to deliver VMs with Java applications

• Microsoft developed virtualization techniques for running Windows even on a Mac

• Popularity was gained through Vmware which developed a simple workstation for the end user

Douglis & Krieger, 2013, p. 6; Ruest & Ruest, 2009, pp. 24–26;

What is a VM?

• Abstract version of a complete computer• Consists of

o A configuration file (amount of RAM, virtual disks)o Hard drive files (virtual version of a physical hard drive)o In-memory file (virtual version of the RAM) → saved when you

e.g. pause the VMo VM state file (saves the state of the VM when pausing or

shutting down)o Other OS specific files like logs

Ruest & Ruest, 2009, pp. 30–31

Virtualization models

Often free and easy to setup→Used for starting a project

More efficient, but harder to setup→Used for productive environments

Ruest & Ruest, 2009, pp. 33

What is a hypervisor?

• Small operating system that exists only for partitioning resources → Virtualizes the hardware

• Isolates VMs and blocks access attempts between the VMs

• Hypervisor type 1: Runs directly on hardware• Hypervisor type 2: Runs on top of a OS

Vogel, Koçogˇlu, & Berger, 2010, pp. 9–11; Ruest & Ruest, 2009, p. 39; Fox, 2012, p. 54

Downsides of VMs

• VM are heavyweight and inefficient compared to a non-virtualized system

• Applications are not easily portable• Slow in IT provisioning

Raj, Chelladhurai, & Singh, 2015, p. 2

Hypervisors

• Software virtualization is often used to start a project

• Hardware virtualization is often used for production environments

Nagy, 2015; Ruest & Ruest, 2009, p. 39;Fox, 2012, p. 54

Hypervisor:● Small OS that only exists to manage

the VMs● Can run insteadof the host OS (type 1)

or on top of the host OS (type 2)

Architecture of container virtualization

• Contains only the needed applications and dependencies

• Container share the same kernel with other containers

• Benefits also from the resource isolation and allocation like VMs

Di Liu & Zhao, 2014, p. 476; Bui, 2015, p. 2

Benefits of containers

• Virtualized hardware is slower than regular ones

• The negative effects can be reduced by sharing the same kernel → containers

• Container encapsulates single service (micro service architecture)

• Container packages all neccessary components• Communication through APIs• Container platforms are e.g. Docker or Rocket

Nagy, 2015

Docker

• Used by famous companies like Ebay, Spotify…• Can only host containers from the same type

as the host OS• Currently only Linux containers on a Linux host• Microsoft is developing the Docker support on

Windows Server 2016 to support Windows containers

Raj, Chelladhurai, & Singh, 2015, p. 2; Bui, 2015, p. 2; Docker Inc., 2016b

Docker engine is driven by LXC

• Linux Containers (LXC): Package to control user spaces

• Essential Feature:Namespaces (implemented on kernel-level) seperate the containers from the host OS

o PID: Process ID namespaceo IPC: Inter Process Communication namespacceo MNT: Mount namespaceo UTS: Unix Timesharing Systemo Networking namespace

Merkel, 2014; Di Liu & Zhao, 2014, p. 476

Other advantages of LXC

• Control groups isolate groups of processes and make it possible to manage the resource allocation between cgroups

• Union file sytem: Copy-on-write creates a copy of the data on modification and changes the current pointer to the right set of data after the process → Especially useful for data that is shared by multiple applications

Pahl, 2015, pp. 26-27; Anderson, 2015, p. 104; Joy, 2015, p. 344; Di Liu & Zhao, 2014, p. 476

Docker Hub: One of the reasons of the rapidly growing community

• Cloud service to upload and share containers• Upload for private or public usage• Easy to „pull“ a container and use it or modify

it• 320 Mio. downloads until beginning of 2015• Prebuilt containers with software such as

Node.js, MongoDB, Wordpress or the Apache web server

E N, Mulerickal, Paul, & Sastri, 2015, p. 697; Haydel et al., 2015, p. 366; Docker Inc., 2016c

2. Comparison of an example: VM vs. Docker Containersa “self-experiment”

Setup of the example

Host OS: Windows 10 Pro (64 Bit)Guest OS: Linux Server (AMD64) 16.04Notebook model: Dell Latitude E5550CPU: Intel Core i5-5300U @ 2,30GHz (Turbo-Boost to 2,90 GHz)RAM: 16 GBVM VirtualBox 5.0.22

RAM: 2GB

CPU: 1 Core

Docker Docker for Windows 1.12.0-rc2-beta16 (build: 4760)

RAM: 2GB

CPU: 1 Core

Installation process

Virtual Machine Docker

• Possible hosts: x86/x64 systems

• Possible guests: Windows (Server), Linux...

• Regular installation process via an executable file

• No Hyper-V support

• Simple and short installation wizard

• Hosts: x64 systems• Possible guests: Linux• Hyper-V has to be

activated!→ Docker activates it if necessary. Restart has to be done to complete the installation

Build: General

Both systems offer the following options:1. Use a prebuilt image/container (and adapt it to

your needs)2. Build your own image/container

1. By hand2. Scripted

Oracle, 2016a; VirtualBoxes, 2016; VirtualBoxImages.com, 2008

Prebuilt images

Virtual Machine Docker

• Prebuilt systems downloadable from Oracle or non-official repositories like VirtualBoxes or VirtualBoxImages

• Should not be used as a production environment (only for testing and development purposes)

• Pull an image from the Docker Hub (e.g. Docker pull ubuntu)

Build your own image

Virtual Machine Docker

• By Hand → Create a new VM, install the OS, install your applications

• Scripted build process with Vagrant and Puppet

• By hand → Pull a basic Linux image and modify it until it fits the requirements

• Scripted build process:– Docker build for the

creation with a Dockerfile

– Docker compose for multi-container applications

– Automated build with Puppet

HashiCorp, 2016a; HashiCorp, 2016b; Heidi, 2013a; Heidi, 2013b; Docker Inc., 2016a ; Docker Inc., 2016f; Docker Inc., 2016g; Mouat, 2016, p. 19

Build your own image

Virtual Machine Docker

• Deployment process:Export VM from host 1 → Import VM to host 2

• Export and import via the GUI of VirtualBox

• Deployment process can take up to one hour (depending on image size and host performance)

• Continuous Integration with a private VirtualBox cloud and the Jenkins VirtualBox plugin

• Docker push to upload the image to the Docker Hub (either private or public repository)→ Afterwards can be pulled from every client

• CI is possible with the integration of Docker, GitHub and Jenkins to automatically push and pull new builds

Oracle, 2010; Oracle, 2012, pp. 5–6; Jenkins-CI, 2013; Docker Inc., 2015; Docker Inc., 2016a

Run: CPU Benchmark¹

Virtual Machine

Goal: Fast execution of the process

Docker(~0,57% slower)

¹ All benchmarks are done with Sysbench for Linux

Run: File IO Benchmark

Virtual Machine Docker(~78,45% faster)

Transfer of a 50GB file

Run: MySQL Benchmark

Virtual Machine Docker(~3,94% slower)

Transactional processes on 1.000.000 test records

Run: Conclusion

• Docker performs much better in the file IO benchmark

• The VM was slightly better when it comes to CPU and database performance → But the difference was very small, it could be influenced by side effects

HowtoForge, 2016

3. Conclusion: Comparison based on Quality Issues

• Architecture of a VM guarantees isolation. Container isolation depends hardly on the used virtualization platform (e.g. Docker)

• Docker manages the communication between containers but the architecture is not 100% safe against unwanted accesses

→ VM is more suitable for processing business critical data

Security

Joy, 2015, p. 343

Performance

• Possible to run more virtual systems on a single server with containers (-->share OS kernel)

• Processing of Docker containers can be up to three times faster but this depends on the hardware that is related to the work that has to be done → CPU processing is nearly the same, hard drive access is much faster in Docker containers

Joy, 2015, pp. 342-345;

Portability

• Docker containers only need around 200MB while a VM needs around 8GB → Better deployment with Docker containers

• Build, push and pull is done within a few seconds or a few minutes with Docker Containers, VMs need up to one hour

• Higher portability due to the better deployment • Standardized host OS for Docker containers• VMs are independend from their host OS• VMs can be configured and used like a regular

computerSeo, Hwang, Moon, Kwon, & Kim, 2014, pp. 108-110; Dua, Raja, & Kakadia, p. 614

Scalability

• Startup of a container needs not much resources and can be done in 10% of the time that a VM needs → Better scalabilty

• Docker containers can be scaled up and down 22 times faster than VMs

Seo et al., 2014, p. 109; Joy, 2015, p. 345

Guidelines - When to use Docker, when to use a VM

1. When the number of guest systems and their size should be scalable (e.g. cloud).

2. When the performance of the virtual system is a critical criterion (e.g. in cloud and PaaS scenarios).

3. When continuous integration should be easily used.4. When fast deployment should be established and

portability e.g. for the development team is necessary.5. When you wan to guarantee a standardized host OS for

your virtual system.

When to use Docker?

1. When processing business critical data and you want full isolation wihtout root access on the host system due to the architecture.

2. When the installation and configuration of additional software should be easy even for inexperienced users.

3. When the VM should be independent of its host OS and the virtualization platform.

When to use a VM?

Thanks for your attention!A more specific talk “Boost your APEX deployment with Docker” based on this research will be hold at DOAG2016.

Bibliography (1/4)

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Copyright

I do not own any of the used images. All rights are owned by Docker Inc. or the University Duisburg-Essen