Fabric, Ansible, Docker, and Chaos Monkey: The Top 10 DevOps Posts of 2015
By Hasan Yasar
Cyber Engineering Solutions Group
In August 2015, the DevOps blog launched its own platform. The blog offers guidelines, practical advice, and tutorials to the ever-increasing number of organizations adopting DevOps (up 26 percent since 2011). According to recent research, those organizations ship code 30 times faster. Despite the obvious benefits of DevOps, many organizations hesitate to embrace it, which requires a shifting mindset--and cultural and technical requirements--that prove challenging in siloed organizations. Given these barriers, posts by CERT researchers have focused on case studies of successful DevOps implementations at Amazon and Netflix, as well as tutorials on popular DevOps technologies, such as Fabric, Ansible, and Docker. This post presents the 10 most popular DevOps posts published in 2015 in ascending order.
Some say that DevOps is a method; others say it is a movement, a philosophy, or even a strategy. There are many ways to define DevOps, but everybody agrees on its basic goal: to bring together development and operations to reduce risk, liability, and time-to-market, while increasing operational awareness. Long before the term DevOps gained currency, though, its growth could be tracked in the automation tooling, culture shifts, and iterative development models (such as Agile) that have been emerging since the early 1970s.
While its community-driven evolution has given DevOps strength by infusing it with ideas from many corners of the software development world, it has also hindered the movement by not providing the community with a central set of operational guidelines.
Often, a company attempting to adopt DevOps will do so against a current of operational red tape and a culture of silos. This transition is not easy for companies that have built their enterprise (and their employees' expectations) on a foundation of "un-DevOps." Moreover, once the decision has been made and a group has the freedom to attempt implementation (which is often its own challenge), the group is faced with the problem of how to implement it properly. In the 10th most popular post published in 2015, The Missing Metrics of Devops, Tim Palko explores this issue.
Here is an excerpt:
Studies of DevOps adoption rates use the phrases "have adopted" or "will adopt," as though they are line items on an organization's quarterly goals and objectives. Does that mean they have achieved Flickr's 10 deployments a day, or do they use the word adopt in a softer connotation, where they have simply accepted their fate, and will now begin listening to DevOps philosophy? Given the many definitions DevOps carries, the word adopt has at least that many variations in meaning and probably more. In any case, DevOps is not a one or a zero, but a continuum of positive and negative attributes, and far from linear.
I'm not going to craft arbitrary milestones. In some teams, achieving any level of DevOps behavior is an accomplishment worthy of a catered lunch. But, to understand that DevOps is at once culture and technology goes a long way toward framing the goal. Another perspective is that your goal of DevOps adoption is what you need it to be. In other words, each organization has its own signature of pain points and struggles, and the vast array of solutions that DevOps offers is sure to provide a good start toward fixing them, even if just one or two are needed.
It seems as though the DevOps movement is doing just fine without some dry, boiled-down set of standards and metrics. However, if we focus on making changes without measuring them we risk being on an endless road to gold plating our process. This outcome would be fine, except customers are also investing real money into these cultural overhauls, whether they know it, want to, or neither. Changes must be planned, with a clear goal and a target date.
To read the complete post, The Missing Metrics of DevOps, please visit
Environment parity is an ideal state wherein the various environments in which code is executed behave equivalently. The lack of environment parity is one of the more frustrating and tenacious challenges of software development. Deployment and development both fall victim to this pitfall too often, reducing stability, predictability, and productivity. When parity is not achieved, environments behave differently, which makes troubleshooting hard and can make collaboration seem impossible. This lack of parity is a burden for too many developers and operational staff.
In the blog post DevOps Technologies: Vagrant, CERT researcher Tim Palko describes Vagrant, a developer's tool that provides a virtualized and provisioned environment to developers using operations tools with a single, declarative script and a simple command-line interface. Vagrant increases development and environment parity by using the same preconfigured (scripted) environment across all developers or in production. Vagrant eliminates the "it works on machine" excuse in application development lifecycle
Here is an excerpt:
The job of an operations team often involves implementing full parity across deployment environments, such as those used for testing, staging, and production. Conversely, the development team is almost entirely responsible for provisioning development machines. To achieve 100 percent parity between both sets of environments, both teams must speak the same language and use the same resources.
Chef and Puppet, both crafted for the operations role, are just slightly out of reach for a busy developer. Each has a respectable learning curve, and neither really solves the parity problem completely: developers still need to virtualize the correct production target platform. All this additional work incurs a decent amount of overhead when you just want to write code!
This is where Vagrant comes in. Vagrant is a developer's tool that basically serves up a virtualized and provisioned environment to developers using operations tools with a single, declarative script and a simple command-line interface. Vagrant cuts out the grunt work needed to stand up a virtual machine (VM) and it removes the need to configure or run, for example, chef-server and chef-client. Vagrant hides all of this and leaves the developer with a simple script, an extensionless file named Vagrantfile, which can be checked into source control along with the code.
To read the complete post, DevOps Technologies: Vagrant, please visit
Conversations between key stake holders of a project team (e.g., developers, business analyst, project manager, and security team) and the platform on which communication occurs can have a profound impact on collaboration. Poor or unused communication tools lead to miscommunication, redundant efforts, or faulty implementations. On the other hand, communication tools integrated with the development and operational infrastructures can speed up the delivery of business value to the organization. How a team structures the infrastructure on which it communicates will directly impact its effectiveness.
In the post ChatOps in the DevOps Team, CERT researcher Todd Waits introduces ChatOps, a branch of DevOps that focuses on communications within the DevOps team. The ChatOps space encompasses the communication and collaboration tools within the team: notifications, chat servers, bots, issue tracking systems, etc.
Here is an excerpt:
In a recent blog post, Eric Sigler writes that ChatOps, a term that originated at GitHub, is all about conversation-driven development. "By bringing your tools into your conversations and using a chat bot modified to work with key plugins and scripts, teams can automate tasks and collaborate, working better, cheaper and faster," Sigler writes.
Most teams have some level of collaboration on a chat server. The chat server can act as a town square for the broader development teams, facilitating cohesion and providing a space for team members to do everything from blowing off steam with gif parties to discussing potential solutions to real problems. We want all team members on the chat server. In our team, to filter out the noise of a general chat room, we also create dedicated rooms for each project where the project team members can talk about project details that do not involve the broader team.
More than a simple medium, the chat server can be made intelligent, passing notifications from the development infrastructure to the team, and executing commands back to the infrastructure from the team. Our chat server is the hub for notifications and quick interactions with our development infrastructure. Project teams are notified through the chat server (among other methods) of any build status they care to follow: build failures, build success, timeouts, etc.
To read the complete post, ChatOps in the DevOps Team, please visit
Container-based virtualization platforms provide a means to run multiple applications in separate instances. Container technologies can provide significant benefits to DevOps, including increased scalability, resource efficiency, and resiliency. Unless containers are decoupled from the host system, however, there will be the potential for security problems. The blog posting by Chris Taschner, Container Security in DevOps, describes why, until that decoupling happens, administrators should keep a close eye on the privilege levels given to applications running within the containers and to users accessing the host system.
Containers have become the hot new technology in DevOps. One company in particular, Docker, has emerged as the go-to provider for container technology. Using the Docker platform, an application can be packaged into a unit referred to as an image, along with all its dependencies. Docker can then run instances of that image. Each instance resides within a container.
Docker is becoming synonymous with DevOps. If you are unfamiliar with the benefits of containers, in a nutshell they include the readily available images and easy-to-use public repository, image versioning, and the application-centric nature of Docker. (For more information see Three Reasons We Use Docker on devops.com.)
Containers also offer a lot of benefit when it comes to their size. Unlike a virtual machine, a container doesn't need the full operating system running or a virtual copy of all of the system's hardware. The container only needs enough of the operating system and hardware information to run the application that it is responsible for. As a result, the container can be much smaller than a virtual machine, so a host system can run far more containers than virtual machines.
To read the complete post, Container Security in DevOps, please visit
Regular readers of the DevOps blog will recognize a recurring theme in this series: DevOps is fundamentally about reinforcing desired quality attributes through carefully constructed organizational process, communication, and workflow. By studying well-known tech companies and their techniques for managing software engineering and sustainment, DevOps blog authors have been able to present valuable real-world examples for software engineering approaches and associated outcomes. These examples also serve as excellent case studies for DevOps practitioners. In the post DevOps Case Study: Amazon AWS, C. Aaron Cois explores Amazon's experience with DevOps.
Here is an excerpt:
Amazon is one of the most prolific tech companies today. Amazon transformed itself in 2006 from an online retailer to a tech giant and pioneer in the cloud space with the release of Amazon Web Services (AWS), a widely used on-demand Infrastructure as a Service (IaaS) offering. Amazon accepted a lot of risk with AWS. By developing one of the first massive public cloud services, they accepted that many of the challenges would be unknown, and many of the solutions unproven. To learn from Amazon's success we need to ask the right questions. What steps did Amazon take to minimize this inherently risky venture? How did Amazon engineers define their process to ensure quality?
Luckily, some insight into these questions was made available when Google engineer Steve Yegge (a former Amazon engineer) accidentally made public an internal memo outlining his impression of Google's failings (and Amazon's successes) at platform engineering. This memo (which Yegge has specifically allowed to remain online) outlines a specific decision that illustrates CEO Jeff Bezos's understanding of the underlying tenets of what we now call DevOps, as well as his dedication to what I will claim are the primary quality attributes of the AWS platform: interoperability, availability, reliability, and security.
To read the complete post, DevOps Case Study: Amazon AWS, please visit
While DevOps is often approached through practices such as Agile development, automation, and continuous delivery, the spirit of DevOps can be applied in many ways. In this blog post, C. Aaron Cois examines another seminal case study of DevOps thinking applied in a somewhat out-of-the-box way by Netflix.
Here is an excerpt:
Netflix is a fantastic case study for DevOps because their software-engineering process shows a fundamental understanding of DevOps thinking and a focus on quality attributes through automation-assisted process. Recall, DevOps practitioners espouse a driven focus on quality attributes to meet business needs, leveraging automated processes to achieve consistency and efficiency.
Netflix's streaming service is a large distributed system hosted on Amazon Web Services (AWS). Since there are so many components that have to work together to provide reliable video streams to customers across a wide range of devices, Netflix engineers needed to focus heavily on the quality attributes of reliability and robustness for both server- and client-side components. In short, they concluded that the only way to be comfortable handling failure is to constantly practice failing. To achieve the desired level of confidence and quality, in true DevOps style, Netflix engineers set about automating failure.
To read the complete post, DevOps Case Study: Netflix and the Chaos Monkey, please visit
In the post Development with Docker, Joe Yankel offers a tutorial on how to get started developing software with Docker in a common software development environment by launching a database container (MongoDB), a web service container (a Python Bottle app), and configuring them to communicate forming a functional multi-container application.
Here is an excerpt:
If you haven't learned the basics of Docker yet, you should go ahead and try out their official tutorial here before continuing.
To get started, you need to have a virtual machine or other host that is compatible with Docker. Follow the instructions below to create the source files necessary for the demo.
For convenience, download all source files from our github repository and skip to the demo section. Our source contains a Vagrant configuration file that allows you to run the demo in an environment that will work. See our introductory post about Vagrant here.
To read the complete post, Development with Docker, please visit
When Agile software development models were first envisioned, a core tenet was to iterate more quickly on software changes and determine the correct path via exploration--essentially, striving to "fail fast" and iterate to correctness as a fundamental project goal. The reason for this process was a belief that developers lacked the necessary information to correctly define long-term project requirements at the onset of a project, due to an inadequate understanding of the customer and an inability to anticipate a customer's evolving needs. Recent research supports this reasoning by continuing to highlight disconnects between planning, design, and implementation in the software development lifecycle. In the blog post, Continuous Integration in DevOps, C. Aaron Cois highlights continuous integration to avoid disconnects and mitigate risk in software development projects.
Here is an excerpt:
A cornerstone of DevOps is continuous integration (CI), a technique designed and named by Grady Booch that continually merges source code updates from all developers on a team into a shared mainline. This continual merging prevents a developer's local copy of a software project from drifting too far afield as new code is added by others, avoiding catastrophic merge conflicts. In practice, CI involves a centralized server that continually pulls in all new source code changes as developers commit them and builds the software application from scratch, notifying the team of any failures in the process. If a failure is seen, the development team is expected to refocus and fix the build before making any additional code changes. While this may seem disruptive, in practice it focuses the development team on a singular stability metric: a working automated build of the software.
Recall that a fundamental component of a DevOps approach is that to remove disconnects in understanding and influence, organizations must embed and fully engage one or more appropriate experts within the development team to enforce a domain-centric perspective. To remove the disconnect between development and sustainment, DevOps practitioners include IT operations professionals in the development team from the beginning as full team members. Likewise, to ensure software quality, QA professionals must be team members throughout the project lifecycle. In other words, DevOps takes the principles of Agile and expands their scope, recognizing that ensuring high quality development requires continual engagement and feedback from a variety of technical experts, including QA and operations specialists.
To read the complete post, please visit
Docker is quite the buzz in the DevOps community these days, and for good reason. Docker containers provide the tools to develop and deploy software applications in a controlled, isolated, flexible, and highly portable infrastructure. In the post DevOps and Docker, CERT researcher Joe Yankel introduces Docker as a tool to develop and deploy software applications with substantial benefits to scalability, resource efficiency, and resiliency.
Here is an excerpt:
Linux container technology (LXC), which provides the foundation that Docker is built upon, is not a new idea. LXC has been in the linux kernel since version 2.6.24, when Control Groups (or cgroups) were officially integrated. Cgroups were actually being used by Google as early as 2006, since Google has always been looking for ways to isolate resources running on shared hardware. In fact, Google acknowledges firing up over 2 billion containers a week and has released its own version of LXC containers called lmctfy, or "Let Me Contain That For You."
Unfortunately, none of this technology has been easy to adopt until Docker came along and simplified container technology, making it easier to utilize. Before Docker, developers had a hard time accessing, implementing, or even understanding LXC let alone its advantages over hypervisors. DotCloud founder and current Docker chief technology officer Solomon Hykes was on to something really big when he began the Docker project and released it to the world as open source in March 2013. Docker's ease of use is due to its high-level API and documentation, which enabled the DevOps community to dive in full force and create tutorials, official containerized applications, and many additional technologies. By lowering the barrier to entry for container technology, Docker has changed the way developers share, test, and deploy applications.
To read the complete post, please visit
In the blog post DevOps Technologies: Fabric or Ansible, CERT researcher Tim Palko highlights use cases associated with the DevOps deployment process, including evaluating resource requirements, designing a production system, provisioning and configuring production servers, and pushing code to name a few.
Here is an excerpt:
The workflow of deploying code is almost as old as code itself. There are many use cases associated with the deployment process, including evaluating resource requirements, designing a production system, provisioning and configuring production servers, and pushing code to name a few. In this blog post I focus on a use case for configuring a remote server with the packages and software necessary to execute your code. This use case is supported by many different and competing technologies, such as Chef, Puppet, Fabric, Ansible, Salt, and Foreman, which are just a few of which you are likely to have heard on the path to automation in DevOps. All these technologies have free offerings, leave you with scripts to commit to your repository, and get the job done. This post explores Fabric and Ansible in more depth. To learn more about other infrastructure-as-code solutions, check out Joe Yankel's blog post on Docker or my post on Vagrant.
One difference between Fabric and Ansible is that while Fabric will get you results in minutes, Ansible requires a bit more effort to understand. Ansible is generally much more powerful since it provides much deeper and more complex semantics for modeling multi-tier infrastructure, such as those with arrays of web and database hosts. From an operator's perspective, Fabric has a more literal and basic API and uses Python for authoring, while Ansible consumes YAML and provides a richness in its behavior (which I discuss later in this post). We'll walk through examples of both in this posting.
To read the complete post, please visit
Wrapping Up and Looking Ahead
DevOps can be seen as an extension of Agile methods that requires all the knowledge and skills necessary to take a project from inception through sustainment to be contained within a dedicated project team. Organizational silos must be broken down. Only then can project risk be effectively mitigated.
In 2016, the DevOps blog will continue to publish guidelines and practical advice to organizations seeking to adopt DevOps in practice with upcoming posts on the following topics:
- Integration OWASP ZAP and GAUNTLT into Secure DevOps Pipeline
- Applying DevOps Principles to Address Dynamic Threat Changes in Cyberspace
- DevOps in Government: Cultural Changes and Governance Structure
We welcome your feedback on the DevOps blog as well as suggestions for future content. Please leave feedback in the comments section below.
To view the webinar DevOps Panel Discussion featuring Kevin Fall, Hasan Yasar, and Joseph D. Yankel, please click here.
To view the webinar Culture Shock: Unlocking DevOps with Collaboration and Communication with Aaron Volkmann and Todd Waits please click here.
To view the webinar What DevOps is Not! with Hasan Yasar and C. Aaron Cois, please click here.
To listen to the podcast DevOps--Transform Development and Operations for Fast, Secure Deployments featuring Gene Kim and Julia Allen, please click here.
To read all of the blog posts in our DevOps series, please click here.