QA in DevOps, Going Cloud with Test Automation
DevOps is not just a strong implementation of agile processes and principles, but it is more of a culture built upon trust among the stakeholders involved in developing and delivering the software. DevOps focuses on reducing the friction among teams aligning their work efforts in getting the product to quickly reach the customers. This is achieved by automating the development and deployment tools, allowing accelerated delivery. We can clearly see the significance and involvement of development and operations team here but, people often find it difficult to picture where the QA team plays its part.
In a real-world, quality assurance is a continuous activity of implementing processes, procedures, and standards to ensure that an organization is providing the best possible product or service to the customer, and it happens at every single instance in the form of continuous testing.
We perform various types of tests to make sure the delivered software meets the quality standards on a functional, usability and performance basis (categorized on a high level). And to contribute to the agility of DevOps where the focus is to deliver faster, it is hard to ignore the fact that: “it’s easy to deliver things quickly, but delivering quality things quickly is difficult”. In order to speed things up, a quality analyst relies on test automation.
To unleash the real power of test automation (test execution/ run), we can leverage the cloud with the right blend of open-source tools. In the presentation, a demonstration on a test automation skeleton built on Robot Framework will be given, which leverages docker containers placed on the cloud platform (AWS). This test automation skeleton automates web apps, mobile apps (native & hybrid) in headless mode utilizing the Selenium & Appium libraries in a CI /CD mode.
Robot Framework - What is it? Click here.
Docker - What is it? Click here.
Tech Stack - Skeleton: Robot Framework, Selenium, Appium, Docker containers, AWS cloud platform
Supporting Tools: Jenkins (CI Tool), Sauce Labs (also supports other similar device lab platforms)
Outline/Structure of the Demonstration
• Where QA fits in DevOps
• CI / CD - Leveraging test automation to contribute to the accelerated delivery
• Overview of the test automation skeleton
- Robot Framework (with Selenium & Appium)
- Dockers on AWS Platform
- Driving efficiency and cost-effectiveness
• Going cloud - docker containers, device labs & AWS platform
• Demo - Implementation of all the above
• Understanding about quality assurance in DevOps culture
• Familiarity with another potential framework - Robot Framework
• Enhancing the idea of taking test automation to cloud with Docker containers & cloud platforms
Test automation professionals, leads, managers, researchers
Prerequisites for Attendees
• Basic hands-on experience in test automation using Selenium & Appium
• Conceptual understanding of cloud platforms and Docker containers
schedule Submitted 1 year ago
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QAOps is Continuous Testing Strategies when
frequent software delivery matters.
It is no surprise that automation and orchestration
make life very easy, be it a small organization or
a large-scale industry that houses hundreds of
servers. IT automation is essentially the ability to
orchestrate and integrate tools,
people, and processes through a certain workflow. I will be using Ansible and Docker to showcase the same and writing ansible tests on top of that.
Ansible - Ansible is an IT automation tool which can configure systems, deploy software, and orchestrate more advanced IT tasks such as continuous deployments. Ansible is actually designed to be a “fail-fast” and ordered system, therefore it makes it easy to embed testing directly in Ansible playbooks.
Docker - A docker container is a lightweight, stand-alone, executable package of a piece of software that includes everything needed to run it: code, runtime, system tools, system libraries, settings. Containers isolate software from its surroundings, for example differences between development and staging environments and help reduce conflicts between teams running different software on the same infrastructure.