Book Image

Deployment with Docker

By : Srdjan Grubor
Book Image

Deployment with Docker

By: Srdjan Grubor

Overview of this book

Deploying Docker into production is considered to be one of the major pain points in developing large-scale infrastructures, and the documentation available online leaves a lot to be desired. With this book, you will learn everything you wanted to know to effectively scale your deployments globally and build a resilient, scalable, and containerized cloud platform for your own use. The book starts by introducing you to the containerization ecosystem with some concrete and easy-to-digest examples; after that, you will delve into examples of launching multiple instances of the same container. From there, you will cover orchestration, multi-node setups, volumes, and almost every relevant component of this new approach to deploying services. Using intertwined approaches, the book will cover battle-tested tooling, or issues likely to be encountered in real-world scenarios, in detail. You will also learn about the other supporting components required for a true PaaS deployment and discover common options to tie the whole infrastructure together. At the end of the book, you learn to build a small, but functional, PaaS (to appreciate the power of the containerized service approach) and continue to explore real-world approaches to implementing even larger global-scale services.
Table of Contents (18 chapters)
Title Page
About the Author
About the Reviewer
Customer Feedback

When should containerization be considered?

We've covered a lot of ground so far, but there is an important aspect that we did not cover yet but which is an extremely important thing to evaluate as containers do not make sense in a large array of circumstances as the end deployment target regardless of how much buzz there is around this concept, so we will cover some general use cases where this type of platform should really be considered (or not). While containerization should be the end goal in most cases from an operations perspective and offers huge dividends with minimal effort when injected into the development process, turning deployment machines into a containerized platform is a pretty tricky process, and if you will not gain tangible benefits from it, you might as well dedicate this time to something that will bring real and tangible value to your services.

Let's start this by covering scaling thresholds first. If your services as a whole can completely fit and run well on a relatively small or medium virtual machine or a bare-metal host and you don't anticipate sudden scaling needs, virtualization on the deployment machines will lead you down the path of pain that really isn't warranted in most cases. The high front-loaded costs of setting up even a benign but robust virtualized setup will usually be better spent on developing service features at that level.

If you see increases in demand with a service backed with a VM or bare-metal host, you can always scale up to a larger host (vertical scaling) and refocus your team but for anything less than that, you probably shouldn't go that route. There have been many cases where a business has spent months working to get the container technology implemented since it is so popular, only to lose their customers due to lack of development resources and having to shut their doors.

Now that your system is maxing out the limits of vertical scalability, is it a good time to add things such as Docker clusters to the mix? The real answer is "maybe". If your services are homogeneous and consistent across hosts, such as sharded or clustered databases or simple APIs, in most cases, this still isn't the right time either as you can scale this system easily with host images and some sort of a load balancer. If you're opting for a bit more fanciness, you can use a cloud-based Database as a Service (DBaaS) such as Amazon RDS, Microsoft DocumentDB, or Google BigQuery and auto-scale service hosts up or down through the same provider (or even a different one) based on the required level of performance.

If there is ample foreshadowing of service variety beyond this, the need for a much shorter pipeline from developer to deployment, rising complexity, or exponential growth, you should consider each of these as triggers to re-evaluate your pros/cons but there is no clear threshold that will be a clear cut-off. A good rule of thumb here, though, is that if you have a slow period for your team it won't hurt to explore the containerization options or to gear up your skills in this space, but be very careful to not underestimate the time it would take to properly set up such a platform regardless of how easy the Getting Started instructions look on many of these tools.

With this all, what are the clear signs that you need to get containers into your workflow as soon as you can? There can be many subtle hints here but the following list covers the ones that should immediately bring the containers topic up for discussion if the answer is yes, as the benefits greatly outweigh the time investment into your service platform:

  • Do you have more than 10 unique, discrete, and interconnected services in your deployment?
  • Do you have three or more programming languages you need to support on the hosts?
  • Are your ops resources constantly deploying and upgrading services?
  • Do any of your services require "four 9s" (99.99%) or better availability?
  • Do you have a recurring pattern of services breaking in deployments because developers are not considerate of the environment that the services will run in?
  • Do you have a talented Dev or Ops team that's sitting idle?
  • Does your project have a burning hole in the wallet?

Okay, maybe the last one is a bit of a joke but it is in the list to illustrate, in somewhat of a sarcastic tone, that at the time of writing this getting a PaaS platform operational, stable, and secure is neither easy nor cheap regardless of whether your currency is time or money. Many will try to trick you into the idea that you should always use containers and make everything Dockerized, but keep a skeptical mindset and make sure that you evaluate your options with care.