If you want to avoid losing $440 million USD and bankrupting your company, let Knight Capital Group serve as a cautionary tale. In less than forty-five minutes, Knight's reliance on outdated practices—including deficient testing and a manual, error-prone deployment process—led to catastrophic losses. These weren't isolated mistakes but symptoms of a broader issue—a lack of robust automation and modern DevOps practices.
At the heart of Knight's catastrophe was a deployment process riddled with human error and a lack of automated safeguards. A single manual oversight during deployment triggered outdated test code, unleashing $7 billion USD in trades in minutes. This stark example highlights the dire consequences of neglecting automating testing—bankruptcy in mere minutes.
Every software company has its own way of doing things. With countless valid methods, it's ill-advised to claim there's only one right way of doing things. That said, certain practices and patterns have repeatedly proved problematic—and testing is one area where cutting corners is never recommended.
No matter how your team operates, testing is a non-negotiable part of development. With fast-paced delivery cycles, automated testing isn't just helpful—it's necessary. It reduces the time spent on repetitive tasks, enhances consistency across releases, and lets you ship code faster and more frequently.
When you pair automated testing with a continuous delivery philosophy like DevOps, you can create robust software delivery processes tailored to your company's needs. In this article, you'll learn about various testing strategies and the common challenges associated with each, giving you the tools you need to maintain speed without sacrificing quality.
The Role of Test Automation in DevOps Pipelines
DevOps is a philosophy that bridges development and IT operations to streamline software processes. Instead of prescribing exact methods, it emphasizes continuous development, testing, and deployment to quickly address bugs, pivot designs, and improve disaster recovery. These practices are collectively known as continuous integration, continuous delivery (CI/CD).
It's worth repeating: automated testing is at the core of a well-designed CI/CD pipeline. The only way to integrate changes regularly is to test them with the same frequency using the following test types.
Types of Automated Tests
There are three main types of tests often integrated into a CI/CD pipeline. Each one serves a different role, but they all aim to ensure that every code change undergoes rigorous validation before it's integrated into the main branch or deployed to production.
- Unit testing examines individual components or functions to ensure they perform as expected. The test works by providing an example payload to a function and evaluating that it outputs the expected value. If any response other than the expected is returned, the unit test fails. Developers often write unit tests when developing their code because they know what the expected behavior is. They serve as the first line of defense against bugs.
- Integration testing focuses on detecting issues resulting from the interaction between multiple modules or services after unit testing is complete. It involves testing several components together by sending a payload through one, which passes it to the next step in the application flow. By combining related components, you can verify that the final output is correct, errors are properly surfaced, and no unexpected issues occur.
- End-to-end testing simulates real-world user scenarios to validate entire application flows in a production-like environment. The scope of end-to-end testing is larger than integration testing. Instead of testing logical clusters of components, you test full user flows. For example, if you're testing an e-commerce application, you would simulate the whole buyer journey, from login to item selection, checkout, and confirmations.
Implementing these tests in some capacity immediately improves any development process.
Benefits of DevOps Test Automation
Integrating automated tests into your pipelines has many benefits, including reducing bottlenecks in development pipelines, promoting faster development cycles, and improving software quality.
Keep the Code Flowing and Accelerate Delivery Cycles
Code validation takes a significant amount of time when done manually; implementing test automation helps organizations significantly reduce bottlenecks in their CI/CD pipelines. Automated tests can be executed in parallel to any extent needed, which means scalability stops being an issue, especially for complex suites of tests. This is also a great opportunity to ensure every piece of code has a purpose—you wouldn't write a test for a piece of obsolete code. This would have prevented the Knight Capital disaster.
While manual testing has its place, it shouldn't account for the majority of the testing in your processes. If you have to wait for a person to execute, analyze, report, and iterate test results before you fix your code, solving your issues will be a drawn-out process. Teams with proper automated DevOps push changes 182 more times per year compared to teams with manual processes.
Automated tests also create a fast feedback loop. When you execute tests after each code commit, you can quickly determine if your changes are on track. A fast feedback loop also means that you don't get stuck waiting for test results. If you have a well-designed suite of tests, you can merge changes as soon as the automated tests are done and move on to your next project.
Improve the Quality of Code Commits
How often have you seen new functionality deployed to production only to be rolled back because it breaks something completely unrelated? Or how often have you experienced new code that works but slows everything else down? What about dead code like Knight Capital? Automated tests can help prevent these issues by flagging changes that break existing functionality or increase loading time. While each case is unique, proper testing allows you to define quality standards and avoid these disruptive setbacks.
Ensure Consistency Across Environments
Even organized developers don't always reset their working environment for every new piece of code. This can lead to lingering issues or configuration mismatches that result in bugs later. A suite of tests on ephemeral environments that mimic production can help catch these issues early. Teams that establish proper DevOps practices deploy code 127 times faster than teams with poor DevOps implementation.
Avoid Overworked QA
If your project grows too much too fast, you can overextend your QA team and set them up for failure. If the volume of tests expected out of your QA teams becomes unrealistic, quotas will be missed or the quality will decrease. Automating most of your QA leads to a lower change failure rate.
Automated tests can scale as much as your process needs them to and help your QA team succeed by letting them focus on test design instead of user experience.
Best Practices for DevOps Test Automation
Hopefully, you're now convinced that you need to automate your tests as much as possible. If so, there are a series of best practices that sets you up for success. The following best practices are mindsets more than prescriptive rituals. It's best to start thinking about these guidelines before you start your next project.
Implement Shift-Left Testing
Shift-left testing is often described as involving QA as soon as possible in the development cycle, but that explanation is often too generic. Shift-left testing goes beyond just early QA involvement; shift-left means proactively identifying potential issues even before the solution to the problem is fully defined. Shift-left testing focuses on anticipating challenges and addressing them early in the process.
Shift-left testing starts with setting clear expectations with stakeholders and ensuring developers understand them. Without defined criteria, it's impossible to know whether a feature has succeeded or failed. If you're defining proper success criteria, including having code tests that are actively being developed instead of waiting for integration phases, as well as catching bugs earlier, then you're shifting left.
Enforce Continuous Testing
A CI/CD pipeline carries its philosophy in the term _continuous_. You should test along the way—when creating new code, merging it into your stable branch, and promoting it across environments. This is why automated tests are so crucial; it would be impossible to manually execute all the tests you need to in a reliable way.
Automate Multiple Layers
There are three types of tests, and you must focus on more than just one. While any form of testing is better than none, building a robust suite of tests takes time. Don't abandon the process until you achieve full coverage.
You have to determine what full coverage looks like for you, but the tools at your disposal don't stop at unit, integration, and end-to-end tests. The following tests can also help improve your code deployment flow:
- Smoke tests quickly verify the stability of a new build before proceeding with other more time-consuming tests to speed up failure detection. Check only for critical functionality and don't go too in-depth.
- Regression tests verify that all previously working functionality keeps working after a new one is added. This process is slow but critical before major releases.
- Performance tests emulate traffic equal to what you expect your application to handle under stress. If deficiencies are found, you need to optimize the code.
- Security tests look for vulnerabilities in the codebase (static application security testing or SAST) and vulnerabilities in the working application (dynamic application security testing or DAST).
- Exploratory tests are the perfect candidate for manual testing; they explore your application without a defined test case in mind. Exploratory tests are not meant to be done all the time, but putting actual people in front of the application can help uncover issues that are invisible to the scripts.
Design Maintainable Tests
Emphasizing automated tests for speed and eliminating bottlenecks are meaningless unless you keep your tests up-to-date. To ensure your tests remain effective, design them with maintainability in mind from the start.
Use reusable code where possible and avoid external dependencies or calls that slow down your tests. The last thing you need is for the cause of the test failure to reside on an external API or database. Make sure the results are clear (the test should either pass or fail) and don't require manual intervention.
Whenever possible, write tests that can be executed in any order. Keep each test focused on a single objective—avoid testing multiple things at once unless it's the specific target. Break down tests into smaller, manageable pieces that fit together in a logical flow. Finally, avoid hardcoding any parameter that could be passed at run time.
Use Standardized Tools
Many tools exist like JUnit for unit testing, Cypress for end-to-end testing, Selenium to emulate user actions on the application, and Jenkins to automate script execution. These tools provide ready-made solutions for different testing needs. More often than not, using established tools to write your tests speeds up the process significantly. You should write your testing frameworks from scratch only when your use case demands it.
Test Automation Implementation Challenges and Solutions
No journey is without hiccups, and implementing automated tests is no exception. Fortunately, many of the most common pitfalls are well-known.
Flaky Tests
A flaky test, or a test that produces inconsistent results, is a common test automation issue. Besides the frustration that such tests can produce, they also lead to false positives or missed bugs.
If you start to notice flaky tests, dig into your environment setup. There might be inconsistencies or recent misconfigurations. The first thing to inspect is external factors, like failing hardware or a slow network. If unstable infrastructure is not the cause, verify that each environment is set up independently and that the variables for execution are not injected manually by testers. If neither of these is the cause, it's time to look at the code itself.
- Don't rely on external dependencies. If you have any dependencies, mock them and repeat your tests.
- Make sure your libraries haven't been recently upgraded or downgraded as different versions might be incompatible with your existing tests.
- Do not use some arbitrary wait time if your test needs to wait for something to happen at runtime. Use the presence or absence of an element on the page as a trigger to continue the test.
- Make sure that you are not relying on random data or some other form of nondeterministic source if you're generating data for the test.
- Do not reuse test environments. Use an ephemeral environment like Docker containers for testing.
Issues with tests can also be mitigated by planning for test maintenance and refactoring. Don't fall into the trap of setting some tests once and forgetting about them. Plan for consistent refactoring windows and refactor tests as the application changes.
Overtesting
While not doing tests ultimately leads to disaster, overtesting leads to frustration, test abandonment, and then disaster. Finding the right balance is as much science as it is art.
Make sure you cover all essential features in your application and back compatibility but don't go overboard with the number of tests or their complexity. If you create an excessive number of tests, your test pipelines will take a long time to complete, and your developers will dread contributing to the project. Focus on tests that provide value.
Mishandling of Test Data
Finally, make sure that the data you use in your tests reflects the type of data your application will use in the real world. Include a stage in your tests that reflects the amount of traffic and performance needs that real-world scenarios would demand.
Don't expose real production data to tests, especially if it's sensitive customer data. You can run a script to anonymize data and then use it in your tests. This is known as data masking and might be a legal requirement in certain industries. Verify that the resulting data is still a good substitute for the real one. If, for example, you accept unicode in your customer submission forms, do not test your applications using exclusively ASCII data.
If you keep these common scenarios in mind, you'll likely save yourself from many unnecessary headaches and countless debugging hours. But even then, some new challenges may arise. Appropriate integration of automated tests and a tool that facilitates test management will be a great ally in your journey.
Integration of Test Automation with DevOps Tools
Integrating testing into your development cycle is the only way to make sure tests remain a valuable tool rather than a nuisance. Many popular platforms for managing your DevOps cycle allow you to create declarative configuration files to define your CI/CD workflows. While these platforms can have a learning curve—requiring you to understand their design philosophies, features, and limitations—they offer the potential to build robust pipelines that meet your automation needs. Here's an overview of some of the most widely used options:
- Jenkins is an open source automation server with a vast catalog of plugins. However, it requires setup, maintenance, and operation; so a dedicated team is often needed.
- CircleCI is a specialized CI/CD platform focused exclusively on testing automation setups.
- GitHub Actions is GitHub's CI/CD solution that integrates seamlessly with your GitHub repositories. It's a great choice if you're already in the GitHub ecosystem, and it supports workflows triggered by various GitHub events.
- GitLab is similar to GitHub actions and provides full repository integration and a suite of pipeline execution utilities and monitoring tools, as well as security testing capabilities. Along with its proprietary offerings, it publishes an open-source community edition.
The Role of DuploCloud
DuploCloud offers a turnkey DevOps automation and infrastructure provisioning solution tailored for organizations that don't have a dedicated DevOps team or have a very small one. Instead of relying on your cloud provider's tools, DuploCloud lets you provision and manage a secure and compliant infrastructure all from a single platform. With DuploCloud, managing infrastructure is fast and easy.
What sets DuploCloud apart is its ability to combine DevOps, security, automation, observability, and self-service tools in a simplified package. It doesn't aim to replace other tools but rather work alongside them, bypass them, or abstract them away for convenience, compliance, and security.
DuploCloud works across all major cloud providers and has its own Terraform provider and Pulumi compatibility through its Terraform compatibility layer. The DuploCloud developer tools aren't just wrappers around the cloud provider's API—they abstract away complex configurations where needed and allow you to adjust advanced settings. According to Gartner, over 75 percent of DevOps initiatives fail to meet expectations due to organizational issues.
Conclusion
Given the fast pace of market demands for innovation and new features, automated tests are non-negotiable for software development. By implementing best practices like shift-left testing, doing continuous testing, and ensuring test scripts are maintained, you'll set your company up for success. And remember, you don't have to navigate this journey alone.
Gain the peace of mind of knowing that every single new deployment in your company will meet the specifications of the Payment Card Industry Data Security Standard (PCI DSS), Health Insurance Portability and Accountability Act (HIPAA), SOC 2, and General Data Protection Regulation (GDPR) with audit-ready reporting. With DuploCloud, new developers can produce value right away using deployment templates, and experienced developers can deploy cloud-native infrastructure ten times faster and reduce operational costs by 75 percent.
In the last year, the DuploCloud offering of automation tools for CI/CD has grown rapidly—check out our plug-and-play scripts for GitHub Actions and command line tools for automation—with more to come soon.
