This paper presents container technology with a particular focus on Docker®, the company, its technology, comparing containers with the VM approach, its involvement in the DevOPs and Platform as a service model, and partnerships with other IT players. It also touches upon the emergence of microservices architecture along with challenges to enterprise adoption.

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Are
containers the future?
A white paper by Orange Business Services (OCB Innovation) and Orange Silicon Valley

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Scope
This paper presents container technology with a particular focus on Docker®, the
company, its technology, comparing containers with the VM approach, its
involvement in the DevOPs and Platform as a service model, and partnerships with
other IT players. It also touches upon the emergence of microservices architecture
along with challenges to enterprise adoption.

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Executive summary
Over the years, information technology has evolved from expensive mainframes to
client-servers and now to cloud computing. A process once handled by a single,
large mainframe was then replaced with hundreds of servers until the birth of the
Internet when hundreds became thousands. As the server count increased, power
and cooling needs skyrocketed as well. By laying the foundation for new computing
architecture over the last decade, server virtualization has helped server
consolidation. Yet with so many advancements happening at only the infrastructure
level, application portability has remained the same over the years, leading to a
number of conflicts between development and operations teams.
Virtual servers that were created by virtualizing the operating system are commonly
known as containers and have been around since the early 2000s. DotCloud® built
their company based on Linux container technology and open sourced its software
before being renamed to Docker® in 2013 and renewing life for containers.
Container technology enables any application and its dependencies to be packaged
up as a lightweight, portable, self-sufficient container that can be deployed
anywhere.
Docker®’s rapid growth within such a short amount of time emphasizes how badly
enterprises have been looking for an application portability solution that would span
across different clouds and different environments within the datacenter during the
application lifecycle. Container technology has been instrumental in the renewed
interest in Platform as a Service (PaaS) model for enterprises, primarily because it
acts as a technology enabler. Containers are developer friendly while ensuring an
easy separation of duties and responsibilities for developer and operations teams,
thereby fully supporting the DevOps concept that is the top to-do list item for many
enterprises.
According to Tracxn®, by looking at the last two years alone one can see the rapid
emergence of the Docker® ecosystem as approximately $200 – $250 million dollars
of funding have been injected into different, related companies. The only competitor
to Docker® is CoreOS®, owner of Rocket® container technology. Security and a
lack of tools are the two biggest challenges for enterprise adoption of container
technology. It is not a question of whether enterprises will adopt containers or not,
rather the question is when they will adopt the technology. Virtual machines have
been the defacto standard for all enterprises over the last decade and while
containers are going to challenge that in the long run, in the short run containers will
co-exist with virtual machines.

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Birth of containers
Over the last fifteen years many organizations have undergone the journey to cloud,
first by virtualizing dedicated physical machines for applications, and then by
subsequently transitioning to an automated and self-service cloud. On this journey
the primary mover to cloud computing has always been the virtual machine. Server
virtualization is the masking of server resources, including the number and identity
of individual physical servers, processors, and operating systems, from server users.
The server administrator uses a software application to divide one physical server
into multiple isolated virtual environments.
There are three ways of creating virtual servers and each of them possesses
differences in how they allocate
resources to the servers.
 Hardware virtualization creates
virtual servers that emulate the
physical hardware.
 Paravirtualization presents a
software interface that functions like
underlying hardware to virtual
servers.
 Operating system virtualization
creates virtual servers that share an
operating system.
Within the last decade the runaway success of hardware virtualization has laid the
foundation for new computing architecture. Paravirtualization was never a success,
and while OS virtualization was temporarily popular it ultimately lost the race to
hardware virtualization. Virtual servers that were created using OS virtualization are
commonly known as containers. Although only recently popular, containers are not
new and several trending container technologies include chroot®, OpenVZ®,
Parallels®, FreeBSD Jail®, Linux Container LXC®, and libcontainer® several of
which were established in the early 2000s. DotCloud® based their company on
Linux container technology and open sourced their software before renaming the
company to Docker® in 2013 which renewed life for containers.
figure 1 – types of virtualization

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Role of containers
The best way to comprehend the role of application containers is by understanding
the analogy between shipping containers and how they revolutionized the
transportation of goods. Prior to World War II, there were several non-standard
methods of containerization across the globe ranging from wooden crates to railway
boxcars. During the war, it was the sheer volume of cargo needed to support the
war effort that led to a standardization of containers. In 1995 the idea of steel box
containers became a reality that allowed stacking in a manner that optimized
efficient loading and unloading of cargo. Over the next few years, ships and ports
changed dramatically to accommodate the shift to containerized transport. Today,
over 90% of bulk cargo travels in standard shipping containers. The use of
containers has shaped not only the landscape of the world’s ports but truck chassis,
pallets and forklift equipment as well as even cranes that have evolved to
accommodate containers.
figure 2 - transportation of goods (source: Docker.io®)
In the IT world, we have different types of applications and services that are
deployed on various hardware environments. The challenge is that every time an
application is written or re-written, it then needs to be deployed or re-deployed to
the different environments with each requiring a unique set of tools. Containers
enable any application and its dependencies to be packaged up into a lightweight,
portable, self-sufficient container that is easily deployable to any location. Docker®
acts as a shipping container for code and some of the key features of shipping an
application in comparison to shipping a container are listed below.
Content agnostic
 Shipping container holds any type of cargo
 Application container holds any type of payload
Hardware agnostic
 Standard shape allows containers to be moved to and from a train, truck,
ship, crane or warehouse
cargo transport pre-1960 cargo transport – today

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 Application container run on
VMs, bare metals, OpenStack
clusters or public instances
Separation of duties
 Shipper worries about what
goes inside and carrier
worries about the external
factors
 Developer worries about the
internal and operations
worries about the external.
Docker®
Company history
In early 2008, a company known as DotCloud® was founded on a Platform as a
Service product offered by Salomon Hykes and Sebastien Pahl, who graduated
from Epitech®, France. After a few years, due to lack of market adoption,
DotCloud® was open sourced in 2013 and within several months the company was
renamed to Docker® shifting the focus entirely on Linux container technologies.
Funding
 Series D – 95 Million in Mar 2015 led by Insight Venture® partners
 Series C – 40 Million in Sep 2014 led by Sequoia®
 Series B – 15 Million in Jan 2014 led by Greylock® partners
Numbers
 No. of funded startup in Docker® ecosystem: 40
 No. of GitHub projects with Docker® in the name: 33,000
 Dockerized applications: 100,000
 No. of organizations in DockerHub: 10,000
 Docker® containers downloaded: 320 million by 4 million developers
 No. of employees: 120 and expected to grow to 200 by end of the year
 Companies acquired: KiteMatci®, Koality®, SocketPlane®
figure 3 - transportation of application
(source: Docker.io®)

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Key terminology and concepts
LAYER
In traditional Linux, kernel mounts the
root file system as read only and later
switches to read-write mode. When
Docker® mounts the root file system
it starts as read only, and later
instead of turning into a read-write
file system, it adds a read-write file
system over the read-only file
system. In turn, there can be multiple
read-only file systems stacked on top
of each other. Each of the file
systems is called a layer.
IMAGE
In Docker®, a read only layer is
called an image. Each image depends on another image that forms a layer beneath
it. The lower image is referred to as the parent image. An image without a parent
image is called a base image.
The rebirth of containers has had a telling impact on key concepts like DevOps and
PaaS. It is also aiding the rise of a new microservices architecture.
DevOps
DevOps consists of blending tasks performed by a company's application
development and systems operations teams. The goal of DevOps is to ensure that
both the dev and ops team participate from, the point of idea inception all the way
to the stage of successful service implementation or product roll out. Docker® helps
both the developer and operations team work together as a unit while still allowing
them to separate necessary duties and responsibilities. Some of the DevOps related
key terms are:
AGILE DEVELOPMENT
A software development method within which requirements and solutions evolve
through collaboration between self-organizing, cross-functional teams. It
encourages a rapid and flexible response to change.
CONTINUOUS INTEGRATION
In software engineering this is the practice of assembling and packaging all the
working copies of developer code with a shared mainline, several times a day.
figure 4 – Docker® terminology
(source: Docker.com®)

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figure 6 – IaaS vs PaaS vs Saas
CONTINUOUS DELIVERY
This is a software
engineering approach in
which teams keep
producing valuable
software in short cycles
and ensure that the
software can be reliably
released at any time.
CONTINUOUS DEPLOYMENT
The released software is
automatically deployed into
production.
Cloud computing service models
Docker® has had a huge impact on two of the following three service models,
Infrastructure as a Service and Platform as a Service but not on Software as a
Service. Docker® has also played an instrumental role in the addition of a new
service model: Container as a Service.
INFRASTRUCTURE AS A SERVICE (IAAS)
The cloud provider delivers cloud computing infrastructure like servers, storage,
network, virtual machines, and
operating system as a service.
PLATFORM AS A SERVICE (PAAS)
The cloud provider delivers hardware
and software tools needed for
application development to its users
as a service. PaaS is targeted at
developers to allow them to perform
rapid software development.
SOFTWARE AS A SERVICE (SAAS)
Software is delivered as a service over
the internet with the entire stack
managed by the cloud provider.
CONTAINER AS A SERVICE (CAAS)
Container as a service can be seen as the layer between IaaS and PaaS, where IaaS
provides hardware virtualization and a template for the operating system but the
customer is responsible for managing the operating system. While PaaS provides
language specific application runtime and focuses on what is running inside the
process, CaaS acts as the glue by providing the generic framework necessary to run
any process on any infrastructure.
figure 5 – DevOps lifecycle

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figure 8 – Docker® components
(source: Docker.com)
figure 9 - client-server architecture
Microservices architecture
In traditional monolithic
applications the major
challenge was deployment of
an application and any
subsequent updates, because
the entire application needed
to be updated in
synchronization with all other
components. Microservices
creates a distributed model for
applications where every
component can be changed
independently without affecting any other components. With Docker® it is easier to
manage individual components separately by running them in different containers
rather than having the entirety of applications components in a single container.
Docker® advocates the use of Microservices architecture while designing container
based applications.
Docker® architecture
Docker® is an open platform for distributing and packaging applications and has
two major components:
 DockerEngine - a lightweight
application runtime and packaging
tool
 DockerHub - a place holder
for storing and managing Docker®
images
Docker® utilizes a client-server architecture where the client interacts with the
daemon. The client and daemon may both
reside in the same system, or the client can
connect to a remote daemon via restful API’s
or a socket connection. The daemon is
responsible for building, running and
distributing containers created from the
images. Images are stored in Docker® Hub,
a registry which can be set to public or
private viewing with the opportunity for
images to be both uploaded and
figure 7 - monolithic vs microservices

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downloaded easily. Docker® is also designed with an open source platform to build,
ship, and run distributed applications.
BUILD-SHIP-RUN
build Docker® daemon uses Dockerfile, a text file that allows the
creation of Docker® images by capturing the Docker® image
creation process in the form of a script. Currently, there are
about a dozen sets of different commands that a Dockerfile can
contain which are then used to build an image. The process to
build a Docker® image includes the following steps:
 Select the OS - specify the operating system or base
image to be used
 Construct Layers - run different commands as needed,
creating a layer for each command
 Set the environment – specify the arguments and
different ports for application configuration
 Build image – save the Dockerfile and build an image
Ship Once the image is built, it can then be shared locally or globally
using a private and public repository or registry.
Run Use the image and run containers anywhere regardless of
whether it is on physical, virtual or cloud servers (as long as the
underlying Linux kernel is the same).

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figure 11 – dev to prod using Docker®
(source: Thomason.io, Author - James)
Use cases
Docker® advocates eight different use cases out of which three key examples are
explained below.
figure 10 - use cases
DEVELOPER PRODUCTIVITY
Developers are a very expensive
resource; therefore they should
neither wait for infrastructure
resources nor work on issues
pertaining to environment. Here,
containerization has some obvious
technical advantages including better
resource utilization and control of
guest operating systems. One of the
more nuanced benefits however has
to do with abstraction of the
operating system and its resource
dependencies from the application
and its dependencies. The latter
benefit helps enable an idealized
workflow called immutable infrastructure, where the state of the application
configuration and dependencies is preserved from development through testing and
on into production. Containers have a finite life cycle that is optimized for developer
productivity and changes are not made to a production environment but rather to
the container itself, making it possible for the application to work everywhere.

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figure 12 – release process using Docker®
figure 13 – virtual machines to Docker®
RAPID DEPLOYMENT
Docker® images are built on union
file systems with changes added as
layers. The steps to build an image
are mentioned in Dockerfile, which is
why deploying containers from
images using Dockerfile takes mere
seconds. Since the same image is
then used across different
environments like development, QA,
staging and production, deployment
is much faster. Also, only changes
are pulled into any environment
rather than the whole image for
continuous deployment. For large
scale deployments many
orchestration tools are evolving to
handle the interdependencies
between containers and how
individual containers can be updated without disrupting the operations of other
containers.
SERVER CONSOLIDATION
Virtual machines (VMs) ushered in the age of consolidation, where servers were
better able to utilize computing power
compared to running applications
directly in a physical server. Unlike
VMs, containers do not need to run a
full version of an operating system,
opening the door to a new level of
consolidation. The consolidation ratio
with containers is better at least by
tenfold compared to consolidation
achieved using virtual machines.

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Vendor ecosystem
A rapid emergence of the Docker® ecosystem is obvious when looking at the last
two years alone and seeing approximately $200 to $250 million dollars of funding
injected into related companies.
figure 14 – container market map by investment (source: Tracxn.com®)
Some of the funded companies are listed below.
ClusterHQ®, the company behind open source Flocker® data
volume manager and container manager, is a tool for database
portability and has received $12 million in funding. Flocker®
enables the stateful live migration of an application which is not
feasible using Docker®.
CoreOS® was a partner of Docker®, until they came up with
their own container: Rocket® at the end of 2014. Kubernetes,
Google®’s open source program, allows companies to manage
a cluster of containers as though they were a single system.
CoreOS® also announced Tectonic, a commercial distribution
of CoreOS® and its containers along with Kubernetes.
CoreOS® has received $20 million in funding with $12 million
coming from Google® Ventures and a combined $8 million from
various other ventures.
Shippable® helps companies ship software faster by giving
them a virtual build, test, and deployment environment in the
cloud. It provides a continuous integration platform built natively
on Docker®. They recently received $8 million in funding in
addition to a previously received $2 million.

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Zett® has developed the Weave project, focusing on Docker®’s
network issue by providing Docker® containers with a single
virtual network even when they are in different hosts. Existing
internal systems can also be exposed to application containers
irrespective of their location. Zett® has received $5 million in
funding from Accel® Partners.
Mesosphere®, whose founders are from Twitter® and Airbnb®,
has built a data center OS (DCOS) which functions as an
operating system that spans all servers in a physical or cloud-
based data center and runs on top of any Linux distribution.
They received $36 million in funding headed by Khosla®
ventures, proving that even an old company riding the Docker®
wave can make the company appealing to investors.
figure 15 - partner map
 VMWare® is partnering with Docker® to ensure
Docker® containers work from the vSphere to
vCloud air using VMWare products and to ensure
interoperability of Docker® images with vCenter,
vCloud automation center and vCloud air.
 VMWare® has developed a mutually beneficial
partnership with Google® that allows support of
Kubernetes from inside VMWare products.
Google® plans on replicating the pod based

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networking model of open vSwitch to enable
multi-cloud integration.
 VMWare®, Pivotal® and Docker® will all work
together in enhancing the libcontainer project with
capabilities from warden.
 Red Hat® is working on project atomic, where the
focus is on re-architecting its own operating
system for the container world.
 Red Hat® announced a partnership with Docker®
and intends to use Docker® containers to replace
its own, working together to ensure native support
for Docker®.
 Red Hat® partnered with Google® Kubernetes for
integrating Kubernetes into OpenShift.
 Red Hat® GearD converts application sources to
Docker® images while OpenShift broker will act
as the glue between OpenShift and GearD.
 Microsoft® re-architected its operating system to
come up with a nano server for the container
world.
 Microsoft® partnered with Docker® to ensure that
Docker® containers can work in Azure® hosted
Linux machines.
 Microsoft® is working with Docker® to have
containers in Windows® as well.
 IBM® partnered with Docker® to announce an
integrated solution called Docker® Hub Enterprise
(DHE).
 IBM® is working with Docker® to ensure
containers are supported in IBM®s cloud.
 IBM® sees an opportunity to support hybrid cloud
to its enterprise customers using containers.
Challenges to enterprise adoption
Server virtualization laid the groundwork for adoption of a new computing
architecture that allowed the creation of multiple virtual machines and helped
consolidate infrastructure resources (servers, storage and network) into a shared
pool. On the other hand, containers, by abstracting applications from VMs to run on
a common OS layer, have recently gathered steam due to their ability to consolidate
the resources even further and thereby increasing both the CAPEX and OPEX

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savings.
Even though containers can reduce cost, enterprise adoption is still in the early
stages. According to a survey done by StackEngine® it was found that security and
lack of operational tools are major challenges for enterprise adoption.
Security
Security is one of the top most priorities for any enterprise when selecting newer
technologies, especially when the technology is only two
years old. There are several areas of concern when
planning to deploy containers, for instance: change
control, asset tracking and management, patch
management and configuration management. All these
concerns tie back into security and how people are trained
with respect to handling different processes. Docker®
containers are built upon the Linux container (LXC) that is
not designed to provide security, therefore security related
issues must be addressed outside of Docker®. As a result, the ecosystem is
evolving to provide the required governance and ensure that containers work in a
real multi-tenant environment.
Operational Tools
In the shipping analogy mentioned before, it took several years before the entire
cargo travel industry had transitioned to standard shipping
containers for the transportation of goods. This is because
changes were needed for ships, ports, cranes, trucks,
and forklifts to accommodate the new standard
container. One can extend this analogy further to
application containers and also see that it is going
to take some time for the ecosystem to evolve in a
way that will allow enterprises to feel comfortable
using containers. Docker® containers are good at packaging an application so that
the application can run anywhere, but it is not meant for managing the lifecycle of
the containers at scale. Container Lifecycle management, capacity management,
performance management, cluster management, configuration management and
governance are some of the tools that are evolving with the help of a vendor
ecosystem. Service discovery is another field that is gaining attention with the
emergence of Docker®.

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Conclusion
With containers changing the way applications can be transported there will be less
worrying about underlying infrastructure related dependencies, revolutionizing an
application delivery process that had remained stagnant the last few decades. Yet,
even though containers are solving the application delivery process, they do not
possess the same level of security as virtual machines. As a result, virtual machines
compliment containers by providing them with their required isolation. Over the next
few years both virtual machines and containers will co-exist before containers can
be used in a standalone fashion by enterprises. While Docker® is leading the
container race, CoreOS® is the only main competitor with their container
technology, Rocket®.

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