Software defects can be fatal. And in the DevOps-driven world of Continuous Delivery and rapid release cycles, eliminating these defects requires testing teams to streamline connections between otherwise siloed Dev and Ops segments. This is an ongoing process, with QA responsibilities to enable Continuous Testing encompassing the wider Dev, Ops and QA segment alike. Developers need to work together with QA professionals to push for short build-test cycles accelerated to minutes and hours instead of days or weeks. Ops must merge with the Dev segment to enable Continuous Delivery of high quality, defect-free and production-ready software iterations. To bring these ideas to life, DevOps teams must employ a strategic approach to accelerate Continuous Testing to fail often and early, and generate fast, deployable software at the rapid pace of DevOps.
Assigning Continuous Testing responsibilities explicitly to a select few QA professionals will ensure accelerated DevOps processes. However, cloud-driven interconnected applications and network endpoints can fail in various ways, and maintaining stable, resilient and high-performance backend is critical to achieving the DevOps goal of Continuous Delivery by applying Continuous Testing practices. Cross-training DevOps professionals on test analysis and recovery of testing environments further ensures these test results that occur fast and in continuity are never overlooked.
Prepare multidisciplinary teams that follow definitive workflows and best practice test designs for fast response to test failures and efficient result analysis. Continuous Testing system architects must define workflows such as performing pre-determined actions to tune Continuous Testing for speed based on the organizational DevOps strategy. Peer-reviewed test scripts in compliance with this strategy and fast approval of the tooling budget required to automate testing and offload manual efforts save valuable time in high-risk testing practices well before reaching production stages.
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The testing system as well as systems-under-test can fail and bring the entire DevOps chain to a grinding halt. Anticipating and preparing for timely recovery of these failures is possible when DevOps teams practice failure simulation runs at the frequency of expected failure probability.
Scheduling for application testing should itself facilitate high-risk early failures. Using cache initialization and predefined network resource topologies ensures the system is ready to launch tests as soon as the build is ready. Conducting all tests in parallel, prioritizing test cases and aborting tests that exceed failure escape threshold optimizes Continuous Testing pace. Eliminating dependencies among tests is a prerequisite for running tests in parallel or in standalone. And at the same time, correlating results from multiple successive build tests and using trends analysis further accelerates diagnostics.
Continuous Testing requires powerful, resilient and stable network resources to speed up the testing process. Establishing a flexible network infrastructure to spin servers and processing resources up and down in a whim without the need of IT helps eliminate bottlenecks surrounding testing environment set up. Using service virtualization is one way to scale and optimize these resources for speed and cost.
Testing automation is the spirit of DevOps and additional investments on the tooling is naturally compensated later in the development lifecycle in the form of fast software release cycles that add business value. Implementing tools as autonomous services integrated via APIs to manage and invoke separately serve as the foundation of automated and Continuous Testing practices.
Designing optimal testing workflows is crucial to streamline the DevOps cycle. Continuous Testing is only effective as long as the underlying infrastructure is stable enough to support continuous and uninterrupted DevOps cycle. When systems are inherently prone to disruptions that raise false alarms, testing teams end up wasting valuable time in analyzing false-negative test reports. Use appropriate tooling to separate these false negatives from actual product failures and leverage monitoring systems to verify real-time performance of interconnected network components.
DevOps teams should design Continuous Testing workflows to automate manual testing procedures and follow a priority-based approach to analyze mission critical test results and verdicts that lead to faster and progressive development practices. The system should be designed to escalate failure automatically to the second level of response teams once failure thresholds are exceeded and the SLA time for first responders expires. A centralized repository collecting test results from all channels and test agents ensures the reports are available in real-time for developers to perform necessary changes in subsequent builds as per the end goal of Continuous Testing.
And by the way, Continuous Testing is not bound by definitive strategies. Everything I mentioned above is potentially invalid as I write since strategy variations to Continuous Testing can be as many as the companies operating on a DevOps model of software development. Continuous Testing as a journey can take many routes, directions, and guidelines that can fill multiple book volumes but end goals such as identifying and fixing software defects early during the development lifecycle and pushing high-quality software out of the door at the rapid pace of DevOps remains unchanged.
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