The DevOps Methodology: Principles for Successful Implementations
The DevOps methodology merges two fields—software development and information technology (IT) operations. The DevOps methodology’s primary goal is fast product release, achieved through the use of automation, communication, and a continuous workflow.
DevOps’ main core principles are cross-training, collaboration, continuous improvement, accountability, transparency, and automation. DevOps teams apply these principles when creating a DevOps process, which typically includes seven phases—plan, code, build, test, deliver, deploy, and monitor.
In this article, you will learn:
- What is the DevOps methodology?
- 6 core DevOps principles
- What is a DevOps process?
- DevOps vs Agile: a comparison
What Is the DevOps Methodology?
The DevOps methodology is a set of practices that require the collaboration of development and operations teams throughout the software development lifecycle (SDLC). It incorporates Agile practices and focuses on breaking down team silos, automating manual tasks, and increasing productivity through continuous feedback.
When using DevOps teams, organizations often implement several practices and tools simultaneously. These include:
- Continuous integration / continuous deployment (CI/CD)—a set of processes that leverage automation to improve efficiency, quality, and speed in the software development lifecycle. CI involves frequent, small modifications to codebases that are tested and integrated as soon as possible. CD involves frequently releasing new code to production without the need for manual updates or patches.
- Cloud-based pipelines—pipelines are the toolchains used to perform workflows such as CI/CD. Often these toolchains are constructed of services and resources that are hosted in the cloud, allowing for cloud-native development and greater support of distributed teams.
- Microservices—an architecture used with cloud-native applications to enable greater scalability, availability, and flexibility. Microservices enable teams to build applications and pipelines that are loosely coupled and easy to modify or update.
- Infrastructure as code (IaaC)—a method that enables teams to provision, configure, and manage infrastructure through software and coded definition files. This method allows the automation of many infrastructure tasks and supports massive deployments without requiring significantly more team resources.
The Core DevOps Principles
When creating and operating under a DevOps methodology, there are several core principles you should consider adopting.
In DevOps, efforts are made for cross-training team members on all processes in the SDLC. This does not mean that all team members have to be equally skilled, but all should be familiar with the processes, tooling, and skills used.
When team member knowledge overlaps in this way, it is easier for team members to communicate. It promotes novel solutions since members are less “trapped” by the expectations of how things should be done. Cross-training can also prevent bottlenecks due to reliance on others, speeding productivity.
Collaboration and the communication that it requires are key elements of DevOps. This methodology relies on team members to work together smoothly and respond to feedback when something isn’t operating as expected. If team members are not able to collaborate, work becomes siloed and productivity is limited by the completion of stages.
DevOps uses an iterative process with small changes that are refined until a change passes inspection thresholds. As soon as a change is accepted, the next is started on. This continuous improvement is applied to all aspects of DevOps, including product development, pipeline performance, and process efficiency.
A DevOps model requires accountability for all tasks – whether development tasks or operational tasks – and both should be equally owned by all members of the organization. This eliminates the traditional thinking of “someone else’s problem”, helps ensure that teams are careful in their actions, whether they relate to development or operations. It also helps build and solidify relationships within a team since all members expect equal effort and responsibility.
Transparency of processes, configurations, tooling, and expectations are all important in DevOps. Without transparency, teams cannot effectively collaborate and there remains a sentiment of “us vs them”. This prevents communication and makes it difficult to hold others accountable. With transparency, all team members can help identify any issues that arise and can suggest improvements in the context of the bigger picture.
DevOps Automation helps teams streamline and standardize work. It also helps create transparency since it requires that procedures be defined and documented. By automating tedious or time-consuming tasks, DevOps teams can focus on higher-level work. This focus can improve quality and encourage innovation.
The DevOps Process
While individual procedures within the DevOps process may vary, the overall process follows a set of fairly uniform steps. These steps occur in a cycle and may change or loop back to previous steps depending on feedback loops. A DevOps lifecycle typically includes the following steps:
- Plan—at the beginning of a project, sprint/iteration, or day, work is planned and prioritized. This helps ensure that all team members understand current goals and defines what work is expected.
- Code—developers create and submit code changes or additions that meet the tasks defined for the current iteration. These are based on a master code base that all developers have access to. This step also includes code review and any clarifications or adjustments that are needed. When submitted code fails to pass testing, it is returned to this step for modification.
- Build—submitted code is compiled, unit tested, and packaged. This is generally the first automated step in the CI/CD pipeline. If a build fails, feedback is sent to the developer, and the submitted change is rejected. If the build is successful, it is passed on for additional testing.
- Test—successful builds are passed through a series of tests to ensure functionality, quality, and often security. Ideally, the fastest or most critical tests are performed first. This way, if a test fails, the originating code change can be returned with feedback as soon as possible, and effort is not wasted. If all tests pass, the build is passed to delivery, and the changes are merged into the master code branch. This ensures that all developers continue to work from the same base.
- Deliver—the last passing build is maintained and held for deployment.
- Deploy—a build may be deployed to a test environment for additional testing, such as user acceptance. Or, it can be delivered to staging or production environments for release.
- Monitor—after release, versions are monitored to identify any issues that were missed and to gather use data that can be applied to future improvements. You can learn more about DevOps monitoring in our article: DevOps Monitoring: The Abridged Guide.
DevOps vs. Agile: What’s the Difference and How Are They Related?
When talking about the DevOps methodology, it is often associated with Agile. This makes sense when you consider that many DevOps teams employ Agile practices. Also, both methodologies are focused on improving speed, efficiency, and quality. Despite this, the methodologies do differ, and one doesn’t necessarily require the other.
In Agile methodologies, the focus is on communication between teams and involving customers throughout the project process. Likewise, most feedback in Agile processes comes from customers.
In DevOps, communication is centered on developers and operations. Customer feedback plays a role in the planning steps and delivery steps but is generally not present during intermediate steps. Instead, teams rely on feedback from tooling and other team members to guide work.
Both Agile and DevOps prioritize skill sharing and cross-training. However, DevOps tends to apply these skills more to communication and collaboration than responsibility. In DevOps teams, developers are responsible for code creation, and testing and operations teams (called DevOps teams) are responsible for pipeline management, environment configuration, and deployment.
In contrast, Agile teams often blur the lines between responsibilities. Within an Agile team, everyone is encouraged to take up whatever tasks are required and roles are less segregated. As a result of this, Agile tends to work better with smaller teams while DevOps is better at providing the structure needed for larger teams.
Agile methodologies follow a sprint or time-limited iteration. Multiple sprints are performed until a project is completed with specific tasks and goals defined in each. Sprints and the work expected are often adjusted to match team output.
In DevOps implementations, the goal is to always have a deliverable product. However, teams may use sprints or iterations to define the work that is expected to go into a specific release. Additionally, DevOps teams are often held to more specific deadlines and benchmarks and have less flexibility defining when a product is done.
Automation for the DevOps Methodology: Continuous Operations, Monitoring, and Feedback With StackPulse
As our businesses become increasingly digital, the reliability of software services that are empowering them becomes a business-critical issue. Every software system, no matter how well-engineered, will have production alerts. These will either be local issues having little to no impact on the end-users or critical issues impacting the availability of the service to its users.
In both cases, the issues should be investigated, analyzed, and fixed if needed, by the relevant owners. Without proper automation, the large number of incidents and alerts in most organizations will lead to:
- Negative productivity impact on R&D and DevOps teams
- “Alert fatigue” for owners and supporting teams
- Longer downtime for production services.
StackPulse is an automation platform for the operations, monitoring, and feedback stages of the DevOps cycle. It allows DevOps and engineering teams to define codified playbooks for these processes. This allows your organization to automate processes in a repeatable and measurable way and trigger them as frequently as needed, without additional manual labor.
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