September 2018 Summaries

The Internet of Things (IoT) is experiencing hyper-growth, with revenue projected to explode from $3B in 2018 to $65B by 2026. As IoT touches various industry verticals and has wide-ranging applications, organizations are jumping on board, seeing the opportunity. However, building and maintaining an IoT system is not easy, with 60% of companies finding it more challenging than expected to build IoT services. Many organizations don't have an IoT testing strategy, which could lead to reliability, security, and performance issues. With proper testing, organizations can solve a range of problems across the spectrum with IoT, from monitoring and diagnostics to APIs, stress and performance testing, and using device simulators. Crafting an IoT testing strategy starts by understanding priorities, taking stock of the system's complexity, and devising the right tactics and tools. The key to building reliable, secure, and high-performing IoT systems is to ensure a robust testing strategy, especially for organizations with IoT applications in production or edge devices and sensors.

QAOps is a term used in the context of DevOps to describe the integration of Quality Assurance (QA) operations into the Continuous Integration and Continuous Deployment (CI/CD) pipeline. It aims to break down silos between QA, developers, IT Ops, and other teams involved in the delivery pipeline. QAOps focuses on automating testing, parallel testing, scalability, and collaboration among teams to ensure efficient and effective software quality. Despite its relatively low usage compared to other DevOps terms, QAOps has helped draw attention to the importance of QA in the age of DevOps and emphasizes the need for automated software testing and QA in delivering high-quality applications.

There are several factors to consider when deciding which tests to automate, including the importance of the feature to the overall application viability, whether the test is redundant and already covered by other automated tests, and the potential impact on build time and maintenance costs. Automating all tests may not be feasible or cost-effective due to the overhead in design and development, as well as the need for ongoing maintenance and adjustments when features change. A balanced approach that prioritizes automation for critical features and manual testing for less important ones is recommended, taking into account the benefits of automation, such as quick bug detection and reduced human error, against the potential drawbacks, including increased maintenance costs and redundancy issues.

The use of emulators to run Espresso tests in parallel on Sauce Labs' virtual device infrastructure can help overcome the challenges of native mobile app testing, including slow test results, high costs associated with real devices, and inefficient testing strategies. By leveraging parallelism techniques, developers can significantly reduce test execution time from 20-25 minutes to under 3-5 minutes, resulting in cost savings and faster feedback for their teams. While emulators may not replace real-device testing entirely, they offer a cost-effective solution for improving the performance of tests and enhancing overall testing efficiency.