Why is Manual Testing Not Sufficient For Continuous Delivery


Software development professionals often use continuous delivery. The introduction of new app code is streamlined by automation. It starts the process by which a software developer changes the application, and it may be automatically uploaded to the code repository registry.

Statistics show that 65% of managers and software engineers say their companies have begun utilizing continuous delivery.

  • It accomplishes everything, including supplying the infrastructure's environment and deploying the tested software to the staging or production environment.
  • Additionally, CD uses pipelines to guarantee that the app code has been bundled with all necessary components for deployment to any selected environment.

Let's examine the CD pipeline principles in more detail and determine whether or not manual testing fits within it.

How does Continuous Delivery work?

According to statistics on software deployment frequency, most developers (31.3%) release software once per week to once per month. Additionally, 27.3% of developers release new software every month to six months. Only 10.8% of developers, however, consistently release new software.

  • Continuous delivery users expect their software release processes to be automated and iterative.
  • The software development teams can schedule their releases thanks to CD. Following the deployments, they would start automating the infrastructure. The teams can efficiently manage the cloud resources in this way.

Other groups could start using microservice testing. For a successful release, CD must be able to adjust to a wide range of deployment circumstances. Software releases are a significant obstacle to the delivery of software because of this.

Because it moves toward a speedier release as well as robust and dependable operations, CD is a recommended practice in DevOps. Continuous testing is done throughout the delivery phase since automation here makes it possible to release adjustments on a frequent basis to environments with standard settings. Additionally, the releases are repetitive and predictable.

What testing on CD looks like?

There are five steps of CD testing:

1. Build
The repository's source code is retrieved at this point. A connection to the relevant modules has been made in either a public or private repository. The binary artifact has finally been created after compilation of all the components. The build process may use tools like scripts, a virtual machine, or even a Docker container, depending on the scripting language and IDE.

2. Commit
Checking and adding the most current source code revisions to the repository are all part of the committing process. For the deployment process, a new case is created with each check-in. A release candidate has been created after the first step has been successful. Eliminating any builds that fail to meet production standards is the goal of this stage, and the developers are also informed of the release candidate's shortcomings.

3. Test
After the source code has passed static testing throughout the testing process, the completed build is completely dynamically tested. There are two steps in this:

  • To validate new features and functions, use unit or functional testing.
  • Regression testing ensures that the newly added and modified features don't break the already functional ones. The findings are passed back to the developers for analysis and the development of fixes for next releases when the mistakes have been found.

4. Staging
The production environment is replicated in the staging environment. This covers the size, architecture, software, hardware, and configuration. A staging environment can be set up as part of the release cycle and removed after the production deployment.

5. Deploy
To deploy an app, a deployment environment must be set up, and the build must be moved to the deployment destination. With scripts or other automation tools, developers automate this procedure. Additionally, you must connect to the tools for reporting errors and tickets. These tools enable users to submit bug reports and assist in locating unforeseen faults following distribution.

Why is Manual Testing not apt for Continuous Delivery?

The ideal method for testing that can keep up with CD and Agile development is not manual testing. Manually testing every function of the software in a brief cycle is challenging. The preferred method of testing has historically been manual testing. But altogether, iterations are fairly boring.

Major Challenges of Manual Testing

The time interval between development and testing completion

The main CD bottleneck is a start-up delay. Inadequate test procedures and testing equipment cause this. Parallel to development, testing should begin from the beginning of the SDLC.

Takes a lot of time, resources, and cost
This bottleneck can be time-consuming since many test cases are still being tested manually. Because the program is being tested manually, this has a significant cost. The length and size of the app will grow as a result.

Difficult to cope with changes
Testing apps meant to operate for a long period is not best done manually. These programs often receive updates and improvements.

Humans are fallible. The quality of an app might decline as it moves through the development process if a mistake is not caught in time. Automation with programmed test results has more precision and saves more time.

Lack of real testing environments
To account for all potential faults, it is crucial to guarantee that the testers have access to the real test environment.

Manual testers must verify compatibility and other issues across all hardware, operating systems, and browser combinations. This is challenging and time-consuming given the current device fragmentation, as it is challenging to manually build up these test settings for each tester.

Less Test Coverage
Additionally, manual testers may overlook a few test cases, which would reduce the overall test coverage. As a result, the entire procedure gets tiresome.

Zero Collaboration
There may not be enough time for team cooperation due to the size of the test cases for the manual testing bottleneck. Developers can quickly repair errors and save time if they receive immediate feedback. Manual testing is nearly impossible with the Agile and CD approaches. So, automated testing is a superior option.

Alternative to Manual Testing in Continous Delivery

It is commonly agreed that in the modern day, test automation should take the role of manual testing. Functional testers are people that spend a lot of time evaluating apps at each step up until the product launch.

  • When it comes to automated testing, the scripts ensure that all necessary tests are done at that point.
  • The code for test automation scripts only has to be created once because it will remain running until the program is ready for release.
  • It is helpful for apps that must go through several upgrades where ongoing testing is necessary after examining each unit.

Therefore, automated testing is compatible with CD and Agile processes. However, functional testers might find it a little overwhelming. A smooth transition from manual testing to test automation should be possible with the use of a test automation solution.

Why should you opt for Automated Testing?

Quicker Releases
The rapid testing of the complete application by QA testers is made possible through automation testing, which helps find and fix errors rapidly.

Eases The Reporting
For testing the complete program automatically with only a few clicks, automated testing scripts are provided. For QA testers, it saves a lot of time and effort. A report is produced at the conclusion of the testing process outlining the issues that need to be fixed.

Errors can occur during manual testing conducted by humans. In contrast, automated testing is thorough and accurate in that it finds problems and fixes flaws. It is therefore the approach that QA testers favor the most.

How Does Testing on Real Devices Make a Difference?

Utilizing actual hardware during testing is mostly done to imitate what end customers would encounter while using a given program. It provides a thorough insight of the app's capabilities and efficiency.

One of the essential components of any SDLC is to test these features on a real device cloud. Actual device testing aids in more accurate bug identification. Real devices can be more expensive to test on, though. However, there is a superior solution to all of this.

QA teams can integrate with the choice of their automated testing frameworks, test native device features, and even opt for parallel testing to scale at the speed of agile.

In conclusion, this article has clarified the argument for why manual testing is insufficient for continuous delivery.