How Docker and containers are transforming testing

Published December 5 2018 by Team Askida
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In 2018, Docker is impossible to ignore. The company’s container technology allows development teams to package an application, tools, libraries and configuration files into an isolated container that can then be deployed onto various host machines according to demand or need. Docker’s data shows that more than 3.5 million applications have been packaged using the company’s technology and its applications have been downloaded more than 37 billion times.

In its annual State of the Cloud report, Rightscale claimed that Docker’s container technology’s adoption rate is close to 50% in the industry. Docker’s potential is therefore massive since containers are continuing to grow in popularity. The marketing firm 451 Research believes that this market could be worth 3.4 billion dollars before 2021.

What are containers and why are they so popular?

As mentioned above, containers allow teams to package an application and everything it needs to run properly into an isolated container, separating the software from its technological environment. In other words, with containers, you don’t need to ask yourself, “Does this work on Windows or Linux?”, only, “Does this work on Docker?”

Various factors can explain the rise of containers. Containers are flexible and can be integrated easily into a Continuous Integration/Continuous Deployment process, or CI/CD, including DevOps. They use fewer resources than virtual machines, which can represent important and valuable gains when you scale up. Docker also allows larger applications to be divided into smaller individual modules that can then be developed by Agile teams. In the end, Docker allows teams to optimize the way they build, deploy and manage their applications.

How containers transform testing

To ensure an outstanding software quality, testing must be able to keep up with the pace of development. Whereas testing a software solution from end-to-end once required several weeks, an application can now be tested in several hours thanks to test automation.

With Docker, automated tests can be integrated into a continuous integration and deployment process, allowing QA specialists to test an application even if it’s deployed dynamically in real time. This approach also encourages companies to integrate QA specialists within development teams, allowing specialists to create more business value while also ensuring the software quality of an application throughout the entire development cycle.

Microservices and containers

Containers are often used to develop microservices, a software architectural style that structures an application as a collection of independent services. By creating isolated environments for precise functionalities, Docker simplifies the process of identifying and fixing bugs and other errors since QA specialists can detect the source of an error faster and more easily.

While containers and microservices possess many advantages for tests, they also create new problems. Data-dependant services, for example, are harder to test in isolation. To fix this problem, it is possible to virtualize a service to simulate an environment or data moving through the system.

Performance can also be an issue. Teams sometimes deploy applications without testing to see how they scale up and how they handle high demand. Performance tests are very important for an infrastructure that relies on containers as they can react differently during high traffic periods. Measuring your infrastructure’s performance can help you pre-emptively identify bottlenecks and other problems.

Deploy faster

Docker’s technology is clearly a winner. According to a study by the company Puppet that surveyed over 4600 software development professionals, teams that used containers and a DevOps or Agile process were able to deploy the new version of an application more than 200 times faster than the teams that used more traditional methods (i.e. “Waterfall”).

Overall, Docker allows teams to develop flexible but robust applications, to separate bigger applications into smaller individual modules and to manage dynamic applications simply and smoothly. When you consider all these advantages, it’s easy to see how and why Docker became impossible to ignore for software developers.

Do you use Docker in development? How does it affect your testing process?

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