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Technical Guidelines and Practical Advice for DevOps

Fabric, Ansible, Gauntlt, and Chaos Monkey: The Top DevOps Posts of 2016

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By Hasan Yasar
Technical Manager
Cyber Engineering Solutions Group

Awareness and adoption of DevOps continues to grow. A 2016 DevOps trends report found that DevOps adoption increased from 66 percent in 2015 to 74 percent in 2016

In 2016, visitors to the SEI DevOps Blog were drawn to posts highlighting successful DevOps implementations at Amazon and Netflix, as well as tutorials on Fabric, Ansible, and Docker. This post presents in descending order (with number one at the bottom being the most popular) the five most popular DevOps posts in 2016.

5. Monitoring in the DevOps Pipeline

In the realm of DevOps, automation often takes the spotlight, but nothing is more ubiquitous than the monitoring. There is value to increased awareness during each stage of the delivery pipeline. However, perhaps more than any other aspect of DevOps, the act of monitoring raises the question, "Yes, but what do we monitor?" There are numerous aspects of a project you may want to keep an eye on and dozens of tools from which to choose. This blog post by Tim Palko explores what DevOps monitoring means and how it can be applied effectively.

Here is an excerpt:

Before getting into the state of monitoring in DevOps, I want to take a minute to discuss tooling. Because there are so many products trying to promote monitoring, choosing among them can be distracting. It is best to, first, understand what holds business value to you and your customers. You should also recognize that not everything that can be monitored should be monitored. Discussing any particular tool isn't the aim of this post, but it is worth noting that most vendors offer free trials, and many other products are simply free, so it might be worth your time to sample a few after you have determined your monitoring strategy.

Infrastructure and service monitoring have been around long before DevOps, so how does DevOps really affect monitoring strategy, and is DevOps even needed for monitoring? Strangely, yes, in a way.

Read the complete post.

4. DevOps Case Study: Amazon AWS

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.

Read the complete post.

3. DevOps Case Study: Netflix and the Chaos Monkey

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.

Read the complete post.

2. Continuous Integration in DevOps

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.

Read the complete post.

1. DevOps Technologies: Fabric or Ansible

In the blog post DevOps Technologies: Fabric or Ansible, 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.

Read the complete post.

Wrapping Up and Looking Ahead

In 2017, 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:

  • Requirements Gathering for Successful Rugged DevOps Implementation
  • Security Requirements and Threat modeling Integration on Secure DevOps
  • DevOps Case Study: Successful DevOps implementation at Scale on HP Printer Development

We welcome your feedback on the DevOps blog as well as suggestions for future content. Please leave feedback in the comments section below.

Additional Resources

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.

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