WiFi SDN Test Automation

The Client

Plume WiFi is a cloud SDN SaaS company, leading the way in developing a cloud-based wireless controller, which can control Wi-Fi networks worldwide. The company is into designing cloud controllers to auto-provision different Wi-Fi network elements using various policies.

Key Outcomes

Automated 500+ APIs testing to achieve 100% test coverage and reduce quality gap.
Developed virtual APs to scale SDN platform testing.

Business Challenges

Plume WiFi wanted to create a robust continuous test automation framework to accelerate the development of carrier-grade Wi-Fi Network-as-a-Service (NaaS) CloudTech platform. It was facing issues in the orchestration of complex test automation for mobile apps and WebUI. The company wanted to focus upon the Agile Development Process and concurrent predictable feature release cycles to target the enterprise and telecom carriers market in a better way.

Business Impacts / Key Results Achieved

Plume WiFi was able to develop reliable continuous integration, automated unit testing, automated end-to-end system QE, and automated DevOps processes. It ultimately achieved a robust continuous test automation framework to accelerate the development of carrier-grade Wi-Fi Network-as-a-Service (NaaS) CloudTech platform. The company was able to get a hold of the Agile Development Process and concurrent predictable feature release cycles. Zymr successfully automated 1000+ mobile test cases with 80% test coverage in a short time, nightly regression, and various other test jobs.

Strategy and Solutions

We created a Robot-based QE Automation framework that helped orchestrate complex test automation for mobile apps and WebUI. We automated 1000+ mobile test cases with 80% test coverage in a short time. By developing Jenkins and Gradle based CI automation, we leveraged the GitFlow source-code and branching protocol. Our team used Jenkins as a master QE automation test controller, and we integrated Zephyr with Jira to provide test execution pass/fail coverage reports. Using Selenium, we developed Web UI automation scripts. We created a QE Automation framework using Python, Selenium, and Jenkins. Our team developed a test reporting server that compiles test results in a drill-down report that can be pushed in PDF format and also saved for further analysis. We worked on various Python and Puppet based scripts to deploy multiple types of builds to Dev, QE, Staging, and Production VM clusters on Amazon AWS. As far as test goals were concerned, we automated the testing of web console with various Role-Based Access Control (RBAC). In AP Enrollment Mobile Apps Testing, we automated testing of lightweight iOS and Android apps that allow end-customers to enroll new Wi-Fi Access Points as well as push notifications. We also automated the testing of REST APIs between the UI tier and the Cloud server tier, and MongoDB data consistency and scalability; and Wi-Fi Access Point functionality using its CLIs

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