Tag: introduction

  • Back to Basics

    Back to Basics

    We here at devopsy.kinsta.cloud do sometimes suffer from The Curse of Knowledge. We write about DevOps regularly for an audience that is doing or managing DevOps. We assume knowledge, but there are still a fair number of people and organizations who are unclear about some of the terminology/technology that we talk about.

    So if you are a regular reader of my blog, this might be a redundant post—but read on because it might have info you haven’t had a reason to consider yet.

    I’m going to start with the obvious—how most readers got here to begin with: DevOps. DevOps is automating the build process so that builds are automated and repeatable. Teamed with Agile development, DevOps means that development teams can rapidly iterate through development and generate regular updates to their applications. Everything else in this blog is based on the premise that it is running in a DevOps environment.

    Continuous integration: Typified by Jenkins, continuous integration (CI) is the part of DevOps that runs the automated builds. It includes reporting and defect resolution only in the sense that it feeds into other systems that track defects. With CI in place, a developer or DevOps engineer can say, “Okay, ready to test a build,” and with one command, can kick off a build that will result in a finished artifact. Or result in a built product, anyway. ‘Finished’ is optional, and the target of CI is not generally a running application.

    Continuous delivery: One of the most confusing things for new DevOps people is CD. The way that the space evolved, there are actually two things that CD could stand for; continuous delivery–automated build of the complete application —or continuous deployment—delivery of a running application onto infrastructure. Continuous delivery is straightforward and means all the bits of the application are code complete–or at least the current state of the application is complete enough to build an application. Continuous deployment is much more convoluted. It might mean deployed to a development environment for developer-level testing or a test environment for running automated (continuous testing) tests on or in production. It might be a staged rollout, where users are siphoned over, or it might be a hard rollout where the old version is replaced by the new in a manner similar to ripping a Band-Aid off.

    Continuous test: Automated testing is at the heart of continuous test (CT), and it is only now becoming a real possibility for most short-staffed enterprises. Advancements in machine learning (ML) mean that tests can be run, results filtered to eliminate false or duplicate results, and IT staff is only notified of the important bits. Unlike traditional testing, staff is required only to create the tests and to look at meaningful results.

    Infrastructure-as-Code: Infrastructure-as-Code (IaC) is the ability to define all relevant elements of infrastructure with text files. Often this is done in YAML and sometimes in a variety of other formats. The idea is that infrastructure provisioning can be on-demand and adaptable. It is certainly more agile to change a text file from port 80 to 8080 and then run a command to process the text file–now the port is documented and whenever needed the command can be re-run to move to a known state. IaC largely relies upon software implementations over physical. While the idea of software-defined networking (SDN) has fallen out of favor, the underlying principles are everywhere and part of IaC, for example.

    GitOps: All the rage these days, GitOps is probably best defined as applying DevOps to operations. That does sound weird, but I like to break it up as “traditional DevOps is DevOps, while IaC (to a lesser extent) and GitOps (to a huge extent) are DevOps.” The point being that GitOps uses the text files generated in IaC and worker nodes generally designed for continuous deployment and then performs operations tasks based on those text files. If IaC defines the entire environment that an application needs and DevOps defines all of the sources that an application is composed of, bundling the two together will enable full-on automation from conception to decommissioning. When a new version of a source file or configuration file is checked into Git, the system then makes certain that every instance of the application is updated with the new version. Of course, this process, like every one listed here, is far more complex than that in implementation; we are talking about ‘what, not how’ at this level.

    All of this really is the very tip of the iceberg, but that was the goal here – to offer readers a place to start if they’re finding themselves looking at DevOps for the first time. As you dig deeper, things like DevSecOps and test driven development (TDD), or defect tracking and Agile methodologies start to play into the landscape, and maybe I’ll write an intro bit for those also. But this time, we’re out of space.

    As always, keep rocking it. No matter which or how much of the above you are using, if the organization’s applications are up and running, that’s you. And you deserve more kudos than you are likely getting. But keep grinding through—the rest of us get it, and thank you.

    Image source: Photo by Towfiqu barbhuiya on Unsplash

  • An Introduction to DevOps

    An Introduction to DevOps

    What is DevOps

    You can ask 10 people for a definition of DevOps and likely get 10 different answers.

    If you want to find a definition of your own, your research will probably begin by asking Google, “what is DevOps”. Naturally, Wikipedia is one of the first result so that is where we will begin. The first sentence on Wikipedia defines DevOps as “a software development method that stresses communication, collaboration and integration between software developers and information technology (IT) professionals.” Well, that’s a fairly dense definition, yet still pretty vague. I think DevOps can be explained simply as operations working together with engineers to get things done faster in an automated and repeatable way.

    So let’s delve into how DevOps works and can better adjoin two traditionally opposing departments.

    Growing pains

    When you are responsible for large distributed applications the operations complexity grows quickly.

    • How do you provision virtual machines?

    • How do you configure network devices and servers?

    • How do you deploy applications?

    • How do you collect and aggregate logs?

    • How do you monitor services?

    • How do you monitor network performance?

    • How do you monitor application performance?

    • How do you alert and remediate when there are problems?

    Combining the power of developers and operations

    The focus on the developer/operations collaboration enables a new approach to managing the complexity of real world operations. I believe the operations complexity breaks down into a few main categories: infrastructure automation, configuration management, deployment automation, log management, performance management, and monitoring. Below are some tools I have used to help solve these tasks.

    Infrastructure Automation

    You no longer have to build a server from scratch, buy power and connectivity in a data center, and manually plug a machine into the network. After wearing the operations hat for a few years I have learned many operations tasks are mundane, manual, and often have to be done at two in the morning once something has gone wrong. DevOps is predicated on the idea that all elements of technology infrastructure can be controlled through code. With the rise of the cloud it can all be done in real-time via a web service. Infrastructure automation solves the problem of having to be physically present in a data center to provision hardware and make network changes. The benefits of using cloud services is that costs scale linearly with demand and you can provision automatically as needed without having to pay for hardware up front.

    Configuration Management

    Configuration management solves the problem of having to manually install and configure packages once the hardware is in place. The benefit of using configuration automation solutions is that servers are deployed exactly the same way every time. If you need to make a change across ten thousand servers you only need to make the change in one place.

    There are other vendor-specific DevOps tools as well:

    In the operations environments I have worked in there were always strict controls on who could access production environments, who could make changes, when changes could be made, who could physically touch hardware, and who could access what data centers. In these highly regulated and process oriented enterprises the thought of blurring the lines between development and operations seems like a non-starter. There is so much process and tradition standing in the way of using a DevOps approach that it seems nearly impossible. From an operational perspective, my first instinct is to understand the application architecture so I can start thinking about the proper deployment model for the infrastructure components. From a development perspective, my first milestone is to make sure the ops team fully understands the application and what it takes to deploy it to a pre-production environment.

    DevOps isn’t just a set of tools, but a philosophical shift that needs that requires buy-in from all folks involved to truly succeed. It’s only through a high-level of collaboration that things will change for the better.