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What Is Continuous Testing in DevOps & How Does It Work?

Myra Nizami
|
11.4.2021

Wondering about continuous testing in DevOps? We explain what it is, how it works, best practices, and the tools you need for success.

What is continuous testing in DevOps?

Continuous testing is the process of automating tests at every stage of the software development lifecycle, with the goal of identifying and addressing problems early. Providing constant feedback to developers helps deploy reliable products quickly.


As a practice, DevOps is about delivering value to end-users, aka customers. Teams that build a solid foundation of continuous testing and deployment can deliver value to customers more consistently by freeing up resources and delivering a more advanced customer experience. 


Teams establish a continuous testing framework based on product needs, with the tests running automatically as code changes are merged into a single branch. Through the process, the testing is broken down into smaller chunks without a lot of manual intervention. Teams are alerted when code changes fail a test so they can go back to fix bugs and issues before sending it back for testing.


However, the continuous part of the process is very much defined by the teams themselves. For the practice to work, testing should occur at least daily. Other teams may choose to do it twice daily, hourly, or even more frequently, depending on bandwidth and resources. 


If we look at the broader CI/CD pipeline, continuous testing comes after development and before deployment. It’s a key part needed to identify and flag issues, and send them back to the development team as needed before it can be released to production.

Continuous Testing and Automation


Automation plays a big role as well. Continuous testing and automated testing aren’t necessarily different  — think of it as two pieces in the same puzzle. Automated testing is a way to test continuously, but continuous testing as a whole is a much bigger concept.


The process of continuous testing often means running automated tests on code changes coming from dev teams. These tests simulate the code running in an environment that matches production. The features are subjected to possible issues, like high load or strange inputs. Any issues that arise are automatically reported back to developers.  


Continuous testing changes the pipeline so that code is constantly being tested and fixed rather than at linear timepoints. So it’s ongoing, as opposed to only being done right before release. Automated testing is an effective way to make that process happen, as developers don’t need to spend dedicated time and effort testing for each of the many iterations.


Continuous testing effectively replaces traditional testing as development and quality assurance are no longer split up but moreover work together in tandem. That’s why it holds more value for customers and teams because testing is done throughout as opposed to right before release. 

Why does continuous testing in DevOps matter?

Looking at the big picture, continuous testing and continuous deployment in DevOps can be incredibly beneficial for both customers and teams.


With continuous testing, teams can break down key steps in the software development lifecycle and gain actionable feedback to make deployment smoother. By seeing exactly where things go wrong in development and deployment, they can make targeted improvements.


With the right testing framework and automation, continuous testing speeds up the development lifecycle without tying up more resources. As a result, teams can establish a more consistent working practice and eliminate bottlenecks, making deployment a smoother process for both dev and ops teams.


Customers benefit greatly too. As the development lifecycle gets faster, they’ll be able to enjoy new features more frequently. These features will likely come with fewer bugs too, as they’ll be caught sooner before impacting production and tying up resources with triaging incidents.


For teams that can implement a continuous testing process and adhere to it, there are significant advantages involved for end-users and the team itself. Continuous testing can save an immense amount of time for dev teams since code changes are automatically moved from the dev environment to testing. 

Plus, the testing is consistent since teams must work together to establish a specific framework and set up its automation. 


That means each code change runs through the same tests every time rather than manually setting up tests as needed and maximum coverage for potential failures. The consistency in testing leads to a more stable continuous deployment process. That means releases are faster and of better quality, making it easier for ops teams as well. 


With automation in place, testing requires little to no manual intervention. If the code fails a test, it goes straight back to the dev team. Otherwise, it moves into deployment without any bottlenecks or issues. That helps teams work faster and better without compromising on the product or the customer experience by pushing out unstable releases and changes.


Another key benefit of continuous testing in DevOps is visibility. The consistency of tests, coupled with the quickness of automation, ensures that teams spot issues right away. Using the right tools, teams can get detailed incident reports on errors and go back to the development process with a clear idea of what needs to be fixed. 

How does the continuous testing process work in DevOps?

The continuous testing process can differ based on product requirements and team capacity. Teams with more resources will be able to test more frequently and invest more in tools like automation. More critical services can also demand more continuous testing, as it’s essential that bugs in those areas don’t reach production. 


The scope for testing is broad, but key areas that teams are usually trying to identify issues with include security, reliability, stability, and functionality. As you drill down, you’ll find that teams can further extend the scope based on priorities, business expectations, and other considerations. For example, if the service involves transmitting personal information, security testing would need to be prioritized.


That’s why the process needs to start with collaboration because there are many moving parts that need to come together. So the first step in the process is to collectively decide what areas need to be tested and identify appropriate tests accordingly for automation. 

Some of the tests that teams may choose to incorporate include:

  • Static code analysis: Examines the source code for bugs and vulnerabilities without running the program itself.
  • UI testing: Used to identify functionality issues in user interface and visual elements of the software.
  • API testing: Testing the application program interface for reliability, functionality, and security
  • Database testing: Used to identify issues in data validation, data integrity, and other performance checks relating to the database.
  • Performance testing: Measures speed, response time, stability, reliability, and other performance elements.
  • Security testing: Identifies potential security threats and vulnerabilities as a result of changes.
  • Regression testing: Running and re-running the existing application to ensure new changes haven’t affected the existing features


Once a continuous testing framework is established, teams need to do some initial groundwork to start the process, such as setting up a stable test environment that can handle the load. It’s then a matter of building out the automated tests that have been identified using tools like Jenkins, Travis, or Selenium.


Once the test environment and automation is set up, teams can start pushing changes through. Tests run 

automatically, and if no failures are detected, it is pushed into the deployment stage. In case of test failure, the changes will be rejected, and the team is notified. Once the issue is fixed, teams send the code back to the testing environment, and the process continues.

Potential challenges of continuous testing

For continuous testing to work well and serve its purpose, having a plan in place is absolutely crucial — as is identifying the right tests. The way the continuous testing process is set up will ultimately define its success or failure, so take the time to invest in the beginning. 


That means solidifying the tests needed at each stage of the release cycle, investing in the bandwidth and resources needed for automation, and a strong testing environment that can handle the load. Otherwise, continuous testing can’t really succeed, which puts the rest of the development pipeline at risk. 


For some, there is a temptation to skip the automation part of continuous testing and do it manually instead. But ultimately, that doesn’t quite work. While manual testing does have its place, it’s important to recognize the limitations of solely relying on that form of testing. Manually testing and re-testing takes up significant developer resources and dramatically slows down the process. Plus, inconsistent testing will lead to issues during the deployment and delivery phase, thereby jeopardizing the customer experience. 


Automation is an integral part of continuous testing because it speeds up the process and provides teams with the continuous feedback needed to rectify issues quickly. That being said, it’s just as crucial to recognize some of the limitations of automated testing so that teams work as efficiently as possible. False positives and false negatives can and do occur, so staying vigilant is key throughout the process to minimize the risk of disruption. 

How does Blameless help with continuous testing?

Continuous testing works best when processes are automated, and teams use the right tools to optimize where possible. Blameless automates every stage of incident response, thereby streamlining incident management and helping teams identify issues immediately. Using Blameless, teams can structure service level objectives (SLOs) and gain visibility on reliability insights to accelerate development velocity.

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