Software testing is a continuously evolving sphere. Often, testers only have hours to test a software and as a result, QA engineers tend to opt for automation and parallelization. Enter Docker containers. Dockers have revamped the way testing is integrated into the CI/CD pipeline: the multi-container testing approach eliminates time and resource-based bottlenecks.
Containerization is a process that isolates an application in its own operating environment, which is lighter and faster than a virtual machine (VM). Containerization operates alongside Selenium, WebDriver and similar automated testing tools. You can package the dependencies of an application in an operating environment that is independent of any external agent that might affect the testing process.
What is Docker?
Docker is an open-source tool used for running applications with the help of containers. Containers use the host operating system and run in isolation, this means that a failure that occurs in any of the containers will not affect other containers.
In order to test with a Docker container, you will need a Docker file that has all the dependencies or project code for running the application.You will then need to build a Docker image using the Docker file. You can use or pull this image to create multiple containers. Our expert engineers have provided examples of the formats you would need for Docker files, building an image and creating a container below:
Docker file format:
FROM centos:7
RUN yum -y install wget
RUN yum -y install java
RUN yum -y install maven
Build image from docker file:
docker build -t image-name
To create a container:
docker run --name=docker_test -it $imageid /bin/bash
Advantages of Docker Containers:
You will not require manual intervention or custom scripts to deploy the build, environment, or any other tool on multiple VMs if you are using Docker: If you need Java, Ruby, Python, RSpec, Maven, Selenium, different browsers and other utilities for setting up automation, for example, you would have to create a script or perform manual setup for all the dependencies on different VMs if you did not use Docker. This is not a reliable solution due to its platform dependencies, script issues and high maintenance.To avoid these drawbacks, you can create a Docker image with all dependencies to get all of the tools or dependencies into containers that can directly run any code or application.
Docker delivers a predictable and reproducible testing environment: There is no need to pre-allocate any RAM to containers. The containers run on the host operating system or the machine where the Docker image is available.
Containers reduce the number of external environment variables that you have to test: Environmental variables are reduced since you are able to pack most of the application’s dependencies and configuration data inside a container. As a result, continuous integration and testing are performed in parallel and assures that the application behaves similarly during testing and production.
If you have to test an application on both Windows and Linux machines, containers enable you to run tests on separate containers and in an isolated environment: You can also reuse the container testing whenever the application code changes and you need to rerun the tests. However, you can kill or delete the container at any stage and can always create a new container at run time. Since the environment remains consistent, there are minimal chances that the application would behave differently in production.
Docker Containers Make Software Testing and QA Easier:
Docker containers enable faster and reliable software delivery. Let’s recap what containers mean for software testing and QA in general:
More Convenient Software Delivery due to Consistent Deployment Environment:
- Once the Dev team pushes the code to the feature branch, the automated test runs and those tests pass, we can review and merge the feature code. By running the automated tests again, we check the build’s health. There is a lot of back and forth testing being performed, signifying that this set of feature code is ready to be pushed to the production environment.
- Relying on CI tools and a process without good amount of test coverage is not a good idea, as this leads to errors and bugs post release.
- Containers provide a consistent deployment environment that can be used at all stages of the software delivery life cycle. In other words, whether you are building the software, testing a software or deploying a software in any environment, you are able to use the same environment using Docker containers.
Increased Efficiency, Speedy Delivery, and Cost Saving:
- Containerization increases the efficiency and speed of SDLC, which is obviously good for business.
- Automation is an important part of QA - Docker improves the efficiency by decreasing infrastructural dependencies.
- Docker helps your organization to save costs by exceptionally reducing the infrastructure-related resources.
Flexibility and Easy Maintenance:
- It’s easier to maintain the tests and environments as all containers run in isolation. Even if an error occurs in one of the containers, other containers will not be affected.
- You can always create a new container at run time.
- It’s easy to run a new application or automation suites in a new container.
In conclusion
Dockers allow you to test in containers and isolate your tests for both development and deployment. Testing becomes predictable, which assures you that when something works on your system, it will also work for your end users. Docker containers enhance the overall SDLC, helping you get a faster, reliable, robust and cost-efficient software delivery.
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