This article will aim to explain the importance of DevOps continuous testing in our ever-accelerating world. We will delve into various methods for seamless integration with your team, the myriad benefits of constant testing in DevOps, and its handful of drawbacks.
DevOps is a relatively new concept within organizations that have in-house operations and development teams. It facilitates both teams to come together and collaborate on faster and more efficient software development solutions. The result is a speedier software development lifecycle (SDLC) with fewer bugs and more frequent patching and updates.
Continuous testing in DevOps is the constant prodding of an application for errors in code or communication. It is omnipresent through both the continual integration and successive development phases of the CI/CD process.
Traditionally, developers compiled their code and sent it off to a testing environment. Then, a quality assurance (QA) team ran tests against the code to find bugs and vulnerabilities. If anyone finds issues the QA team sent them back to the developer to fix, and the process is repeated.
QA worked as fast as possible to find bugs, but deadlines were often missed, and patches might not be deployed for weeks. DevOps brings a new way to perform testing by automating the process. As developers code, their pieces are compiled and tested continuously. The automation scripts find bugs and send notifications to developers when issues are found. This method speeds up the testing process and gives developers feedback before they deploy to a testing environment.
The benefits of continuous testing in DevOps share a common motif: speed. Over-capacity programmers forged this prodding process to keep pace with their shrinking release schedules. However, as constant testing carved away more significant chunks of their valuable time, many independently created automated & manual testing processes to rewind the clock. Each process uncovered the profound benefits of continuous testing in DevOps and encouraged further exploration.
Quickly and reliably deliver code changes
Automated steps create additional time to focus on code quality & security
Smaller code differentials allow for easier identification of defects
Eliminates testing bottlenecks
More agility with a constant understanding of what is working well and what is not
This leads to more educated release decisions
Delivers a consistent experience to users
Benefits flow to end-users as well. For example, a business that relies heavily on its software might make changes based on user feedback (e.g., a gaming developer), and DevOps continuous testing improves the velocity of development. Testing is performed automatically, feedback is sent immediately to developers, and developers can fix bugs as reported rather than wait for a human QA team.
The benefits of continuous testing in DevOps are far-reaching, but even these streamlined processes come with their own set of drawbacks. Often, leaner companies do not have the required resources to set up proper continuous testing processes, or the time investment outweighs the benefits for their relatively static application.
Disadvantages:
Additional training may be required for developers not accustomed to CI/CD timelines.
Testing requires some technical architecture skills and honed time management.
Establishing tests can be time-consuming, with variations and workarounds often needed for the many layers of an application.
Most businesses find that the most significant disadvantage is the additional cost of infrastructure and in-house staff. The DevOps team requires new staff trained to deal with development, operations, and testing automation. This team could be current staff, but then staff needs training on new software and infrastructure.
Other additional costs include the software and hardware necessary to execute automation. Free, open-source software is available, but it usually does not have the features for enterprise DevOps. In addition, for new DevOps teams, staff often need time to test and review the software before it's implemented as part of the automation process, which takes time and resources from other development projects.
Architects understand that varying climates require unique designs suited to regional temperature fluctuations. For example, homes in colder regions often have roofs at steeper angles to prevent snow accumulation. In contrast, warmer weather homes utilize heavier building materials to absorb heat during the day and dissipate it at night. The same approach can be seen by technical architects, deploying tests to amplify the application's benefits while mitigating and preparing for its weaknesses.
Suppose a technical architect designed a DevOps testing strategy for an application with ample moving parts passing through many sets of the developer's hands. In that case, a unit testing method might be selected. This enables rapid feedback on new code by breaking down and testing the code in digestible units. Unfortunately, unit testing is only one of the many tools a technical architect possesses in their "Mary Poppin's-esque" tool chest.
Additional examples include production testing, exploratory testing, automated end-to-end testing, regression testing, etc. Each of these examples possesses its benefits of continuous testing in DevOps and drawbacks to be strategically implemented case by case.
User acceptance testing (UAT) is a specific type of continuous testing to determine if the application satisfies the user's expectations and needs. Software design starts with collecting user requirements, and they must be tested to ensure that contracts are met.
Testing can be done by other developers or users themselves, depending on the target. For example, in-house developers test software meant for external users before presenting it to the customer, but the end-user might test software when it's meant for in-house tools. For basic requirements, automated scripts test for functionality defined in contracts and planning documents.
Another widely used DevOps testing strategy is performance testing. This method of testing ensures that software does not crash from too many concurrent users. It tests for loads dependent on the number of users projected to use the software. For example, if 1000 users are projected to use the application concurrently, then performance testing ensures that software executes efficiently with 1000 user connections and no performance degradation is detected.
Smoke testing is a continuous testing process that uses subsets of testing procedures to test the most critical parts of a new code deployment functionality. This testing step is performed right before the code is passed to QA. It ensures that basic functionality works before human testers review software features. Smoke testing saves time on QA because it finds bugs before staff spends too much time on buggy code.
User interface elements are created by designers and sent to developers to integrate into the code. These elements must be tested for bugs and user errors. For example, a layout might consist of desktop and mobile designs. UI testing ensures that features and assets render properly on both screen sizes and both layouts dynamically render based on devices and their screen resolutions.
As developers add new features to the software, they must ensure that changes do not affect current functionality. Regression testing ensures that recent code changes don't break current
features in software. It can be automated with some human QA also reviewing old features to ensure that users do not lose functionality when new functionality is added.
Continuous testing is a highly effective tool for improving code deployments and creating better coding practices. Still, developers and cloud engineers alike can benefit significantly from integrating a continuous testing process with GCP.
With Google Cloud Monitoring and the cloud operations suite, teams can use metrics and traces to gather meaningful insights from every build and establish performance indicators across cloud applications. In addition, DevOps teams can evaluate the success of their deployments and automation scripts to improve testing continuously.
For developers, continuous integration and testing mean faster velocity during the software development lifecycle. Developers can deploy updates and patches faster because continuous testing gives feedback on the latest code changes. As developers write code, they know to fix bugs before it's compiled and sent to QA.
With automation and GCP, developers can reduce deployment times from several weeks to potentially minutes. In addition, automation speeds up deployment, and GCP provides the reliability and scalability needed for enterprise applications.