Docker Cookbook

9.12 Gaining Visibility into Your Containers’ Layout with Weave Scope | 297

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Figure 9-5. The Weave Scope dashboard
Navigate through the UI, explore the various grouping capabilities, and explore the
information of each container.
Discussion
Weave Scope is still in early development and considered pre-alpha as of this writing.
You should expect more features to be added to this open source product. Keeping an
eye on this visibility solution for Docker containers is definitely worthwhile.
Building from source is straightforward with a Makefile that builds a Docker image.
See Also
• Detect, Map, and Monitor Docker Containers with 
Weave Scope
298 | Chapter 9: Monitoring Containers

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CHAPTER 10
Application Use Cases
10.0 Introduction
To finish this book, I will argue that Docker makes building distributed applications
painless. You now have all the tools in your arsenal to build a microservices applica‐
tion that will scale within and outside of your datacenter. At the very least, deploying
existing distributed systems/frameworks is made easier because you need to only
launch a few containers. 
Docker Hub
 is full of MongoDB, Elastic, and Cassandra
images, and more. Assuming that you like what is inside those images, you can grab
them and run one or multiple containers, and you are done.
This last chapter presents a few use-cases that are meant as teasers and put you on
your way to building your own application. First in 
Recipe 10.1
, Pini Reznik shows
you how to build a continuous integration pipeline with Docker and Jenkins. He then
shows you how to extend it and build a continuous deployment pipeline using Mesos
in 
Recipe 10.2
.
In 
Recipe 10.3
, we present an advanced recipe that show you how to build a dynamic
load-balancing setup. It leverages 
registrator
with a 
consul
key-value store and
confd
. 
confd
is a system to manage configuration templates. It watches keys in your
key-value store and upon modification of the values of those keys automatically re-
writes a configuration file based on a template. Using this setup you can, for example,
automatically reconfigure a load-balancer when new backends are added. This is key
to building an elastic load-balancer.
With 
Recipe 10.4
, we build an S3-compatible object store, based on Cassandra run‐
ning in Kubernetes and a software called 
pithos
, which exposes an S3 API and man‐
ages buckets in Cassandra. It scales automatically through the use of Kubernetes rep‐
lication controllers.
299

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In 
Recipe 10.5
 and 
Recipe 10.6
 we build a MySQL Galera cluster using Docker Net‐
work. Docker network is still experimental at the time of writing but this recipe will
give you a great insight into what will be possible with it. With automatic container
linking, nodes of a MySQL Galera cluster can discover themselves on a multihost net‐
work and build a cluster as if the containers were on a single host. This is extremely
powerful and will simplify distributed application design.
We finish with a Big Data example by deploying 
Spark
, a large-scale data processing
system. You can run a Spark on a Kubernetes cluster but you can also run it on a
Docker Network–based infrastructure extremely easily. This last recipe shows you
how.
Enjoy this last chapter and hopefully it will spark your interest.