Quick-Start Guide to Building Your DevOps Pipeline
Building a DevOps pipeline requires a mindset of continuous improvement. Whereas DevOps is responsive to changing demands, older methodologies are hard pressed to deviate from original plans. Some of these older methods’ outcomes include time delays, overspending, compromised quality, frustrated teams, and, often, dissatisfied customers.
The pipeline is at the core of the DevOps methodology. With a collection of steps designed to drive continuous improvement, DevOps strives to assemble team workflows that produce superior customer experiences.
Drive continuous improvement in your business by learning about DevOps pipeline elements and what it takes to build your own team to create the ideal customer experience.
Understanding DevOps: Key principles
DevOps is the abbreviated term for “development and operations,” which refers to the consolidation of the development team, with operations being the end user. DevOps also describes the principles and processes applied in the software development life cycle (SDLC).
Five principles lay the foundation of the DevOps methodology. Depending on who you speak to, these principles address continuous development, integration, testing, deployment, and monitoring. Our guide focuses on continuous integration (CI) and continuous delivery (CD), which support the next three principles of continuous deployment, continuous testing, and continuous operations.
- Continuous integration (CI): CI employs a central code control system that enables code inclusions from team members. This build system’s primary goal is to ascertain code accuracy because of its diverse origins and it automatically sends alerts when an issue is identified that interferes with the successful merging of codes. Immediate fixes equate to including ongoing code in the pipeline, which avoids wasting time on fixing code only after phase completion.
- Continuous delivery (CD): CD complements CI by promoting the rapid release of the build code through incremental updates during production. After release from CI, the team can choose to further evaluate or push code to production and assess behavior or release the live code.
- Continuous deployment: While continuous delivery highlights the manual process of coding, features, and updates, continuous deployment represents automation; updated coding is automatically released to the end user. However, several disadvantages accompany this process, including the potential release of faulty code, which can end up in production or, worse, result in downtime. Only small code updates should be considered for release and they should be paired with vigorous testing frameworks to guarantee they’re error-free before moving to production
- Continuous testing: Repeated testing throughout development helps teams evaluate risks before production and delivery. Testing includes both functional and nonfunctional and comprises a selection of tests designed to check for security errors, performance issues, how well the unit runs, system problems, integration, and compliance.
- Continuous operations: The strategic creation of continuous operations is aimed at maximizing app accessibility and environments. Users should not be aware of fixes behind the scenes, current code applications, or subjected to unnecessary downtime, which is only possible with a robust architecture.
Stages of the DevOps pipeline
DevOps pipeline stages will vary, depending on who you speak to. However, many of these stages overlap or incorporate components of the previous or the following step. Despite variations, the objective of the pipeline is to maintain a streamlined workflow rather than coming to a standstill once the product has been deployed.
This guide sticks to the basics of the DevOps strategy, outlining six stages that comprise the pipeline process. Many companies will alter this pipeline process to include eight steps, showing how it can suit individual needs.
- Planning: Managers generate a plan to lead the team and workflow before developers begin the coding process. All relevant stakeholders and user groups are consulted to provide information, after which the work is divided into bite-sized tasks that are more easily managed. Small tasks and sprints (typically lasting two weeks) are assigned to individual team members to hasten assignment completion. Consequently, teams produce outcomes fast because they engage in immediate problem solving to adapt to changing circumstances.
- Developing: Developers begin the coding process based on predetermined standards to produce a uniform outcome. The programming language used will also determine which technologies are installed on their computers, including integrated development environments (IDEs), code editors, and others to support productivity. As developers complete small coding sets, they may initiate a pull request to the shared repository for source code. Developers will then manually check the code and merge it with the master branch when they approve the pull request.
- Building: The build stage is designed for error detection before advancing further in the pipeline. Once merging has taken place in the shared repository, automated tests are conducted by the developers. Once a pull request has been initiated, the code might be compiled into a build via an automated system, which can be deployable or executable. Both the build and original pull request will fail if there’s a code problem, and the developer will be notified. Repeating this cycle promotes error-free code progressing down the pipeline.
- Testing: Once the code build successfully moves through the previous phase, it proceeds to testing, where developers conduct manual and automated tests to validate integrity. A user acceptance test (UAT) is frequently conducted, with users engaging with the app to determine whether further changes are required. At the same time, the app may be subject to performance, security, and load testing. If no more changes are needed, the code build will advance to production.
- Deployment: At this stage, the code is ready for production, and an automated deployment process is implemented if small changes are required. Alternatively, if the code has undergone substantial changes, a blue-green deployment strategy is executed to monitor code behavior in a simulated production environment. In this strategy, two matching environments are used. One hosts the current code, and the other hosts the newer version. This strategy also supports workflow because developers submit change requests to the relevant servers. If problems are experienced, the developers will return to the earlier production environment to prevent service disruptions.
- Monitoring: Continuous monitoring takes place throughout the pipeline, but developers focus on constant monitoring in this final phase. Applications, systems, and infrastructure are sources of data collection, which can help with further analysis, monitoring processes, and user feedback collection. All information gathered in this phase goes toward making additional improvements to efficiencies in the pipeline. Any identified issues drive continuous development in future DevOps projects.
From these components, it’s easy to identify a process of continuous improvement. Work division, whether at the planning phase or monitoring, is carefully evaluated to check quality and performance. DevOps teams typically close out their projects with a strong sense of accomplishment, mimicking happy end users.
How to build your own DevOps pipeline
Recall that DevOps means “development and operations.” To achieve a final product, you need developers to generate code in line with the required app and users to test the final product.
You’ll need automation tools to accomplish the process described in the previous section. It’s necessary to have a source control environment, also known as a version control system, and a build server to run automated tests before the code can progress to production. Here are some of the basic steps for creating your DevOps pipeline.
If this is your first foray into DevOps, we recommend engaging independent talent through Upwork to help guide you through this pipeline development. Alternatively, consider partnering with skilled professionals to complement your team to speed up the process.
Step 1: Establish a version control system
In the first stage of the process, you’ll need a repository where code can be stored. A version control system can achieve this aim. Typically, GitLab, SVN, or Bitbucket suit this purpose.
You can register a free account on GitLab to create the shared repository and install Git on your computer. You need to install this software to send coding to the repository after it’s written.
When a development team works on the same project, the manual checking of code usually occurs before sharing on the repository, enabling a code merge to take effect. Consider independent technical professionals to help streamline this setup process.
Step 2: Choose a build server
Analysis software is available to check if the code is ready to be sent to production once it’s merged in the repository. Choosing the right software will depend on the app’s programming language and how big the project is.
Teams can choose to use Jenkins, Maven, Gradle, or other software to build their server. Jenkins is a popular open-source tool used to build servers for the continuous integration and testing of code. This software is also known to be compatible with many testing and deployment technologies, so it’s often favored by DevOps teams.
Once Jenkins is installed on the server, it must be linked to GitLab, after which it will need to be configured to run after each code change is made in the repository. Jenkins compiles and merges code to create a build, automatically sending alerts to the development team when problems are identified, enabling quick fixes before the entire coding process has been completed.
A virtual environment is recommended for further testing, which is where container software programs come in. The code is committed to containers for safekeeping and improved integration once removed from the team member’s computer.
Many teams use Docker software to facilitate the pre-production testing process because it’s portable, compatible across operating systems, and eliminates the need for constant configuration to maintain code integrity. Teams can use other container software programs, such as Mesos, CoreOs rkt, OpenVZ, and Containerd.
Step 3: Set up automated testing
Docker or another code container software is used to facilitate automated code tests, ranging from unit testing, integration, sanitization, and functional tests. Docker comprises a virtual environment where a server can be created on which comprehensive code tests are run.
Typically, automated tests are set to run consecutively, with the shortest tests being a priority, as these take the longest to complete. Once the code has passed all automated tests, it’s ready for production, where additional evaluations occur. Docker is used as a virtual environment for app simulation to check how it behaves before being approved for real-time use.
Step 4: Put code into production
App testing is required before the project can move to the production phase. Docker, Apache, or another container software can be set up on servers to test run code before progressing to the final testing phase. A virtual machine is usually established for a cloud-based app, but specific project requirements will determine what cloud server will best suit the needs of the DevOps team.
For example, the team may prefer a virtual, dedicated, or bare metal cloud server for specific project needs. In other words, the server choice will depend on performance variations, such as control, speed, and convenience, that must be weighed against the cost of the server used.
App deployment can also occur manually or automatically, but manual positioning is recommended as a starting point. Once manual deployment has been completed, an automated process can be undertaken. Automation is also only advisable once teams realize that effective barriers will prevent code errors from reaching this stage.
The build server must be configured to automatically execute a script to release code into production. Once all code checking and app testing are complete, the product is ready to go live.
Independent developers are fully equipped to complement existing teams or drive the DevOps pipeline setup from start to finish.
Bring the top developers to your DevOps team
This guide explains the foundations of DevOps and how to build your own pipeline. Although companies will employ their own systems to achieve their goals, Upwork clients have expressed satisfaction when partnering with professional talent on our platform.
Director of Software Engineering for PGA of America, George Whitaker, experienced 50% savings and project completion rates that were three times faster than normal when using Upwork talent. GE shared a similar experience, stating they experienced a 50% improvement in project completion rates compared to traditional methods.
Against this background, businesses can share in the benefits derived from engaging independent professionals from Upwork. Our pool of independent talent can make a significant difference to your team at multiple levels across the DevOps pipeline.