Cloud Migrated Continuous Testing in DevOps: A Game-Changer for P&C Insurers

Aim: The study examines Continuous Testing (CT) in a DevOps environment for cloud migration within the Property & Casualty (P&C) insurance industry and InsurTech companies. The study evaluates the impact of AI/ML-driven test automation, security testing, and performance validation using tools like Selenium like Selenium, JUnit, and TestNG; CI/CD pipelines such as Jenkins, GitHub Actions, and Azure DevOps. Experimental testing with comparative evaluations shows that a CT structured approach simplifies any cloud migration project and improves defect propagation and compliance ratios in regulated industries.

Industry and Scientific Application: Beyond insurance, this study applies to other industries and scientific research. Continuous Testing drives innovation by detecting real-time defects, reducing deployment risks, and ensuring regulatory compliance. These findings can serve as a model for organizations integrating DevOps-driven testing in cloud migration.

Benefits of Cloud Migration: CT in DevOps optimizes cloud migration by automating testing, reducing errors, and improving deployment efficiency. Companies using CT see 40-60% faster deployments and 35% fewer defects post-implementation. Automated security checks enhance compliance, while test automation lowers costs. These benefits make CT essential for a smooth, secure, and cost-effective cloud transition, especially in regulated sectors like finance, healthcare, and insurance.

Case Studies and Real-World Application: Case studies of Liberty Mutual and Progressive Insurance have shown that Continuous Testing is effective and accelerates DevOps-centered cloud migration. Liberty Mutual used cloud-embedded automated test frameworks to reduce the release time period by 50% and achieve compliance, thereby cutting time-to-market. Progressive Insurance streamlined the testing of APIs and mobile applications, using CI/CD-integrated testing automation to produce faster claims processing at the rate of up to 30% and a drop of around 90% in API failures. Here, in these case studies, one sees how Continuous Testing massively contributes to deployment efficiency, system resilience, and adherence to regulations in real world case applications in insurance.

Study Design: "This study takes a mixed methods approach that incorporates case studies, industry surveys, and experimental testing to assess the efficiency of Continuous Testing in cloud-migration strategies," instead. Its research targets insurance companies which have recently adopted DevOps-driven cloud migration and investigate their testing frameworks.

Place and Duration of Study: This study is based on a review of industry practices, integration strategies and analysis of cloud migration strategies in global insurance firms across various companies in North America and Asia-Pacific, focusing on solutions implemented between 2018 and 2024.

Methodology: The study employs a multiple research method approach, including reviews of the literature, case studies, surveys, and experimentation, to assess the impact of continuous testing (CT) for the DevOps-driven cloud migration of P&C insurers. Following a detailed literature review about the extant state of the research into CT and cloud adoption in insurance, case studies are available to demonstrate insurance URLs using CT-based frameworks. Surveys and interviews with IT and DevOps in-house experts underline the challenges and good practices. Through experimentation with automated testing tools such as Selenium, JUnit, and Jenkins, we measure the improvements in efficiency. A comparative analysis will measure the performance indicators prior to and after the CT implementation.

Results: Continuous testing (CT) substantially enhances cloud-migration efficiency for P&C insurance. Companies that have had CT in their version of DevOps have executed a 40-60% increase in software release cycles, leading to faster deployments. Automated testing dragged post-deployment issues down by 35%, thereby increasing the reliability of the software. Compliance with industry requirements was much better because continuous security checks lessen risks. Another benefit included a reduction of about 20-30% in testing costs due to automation that replaced human testing. On top of this, the way for more applications to be resilient to system failures was opened; applications were supported and maintained. The post-migration data should always specify that applications have 99.9% up time. In the heavily regulated insurance sector, continuous testing thus becomes a much faster, more secure, and cost-effective measure for moving to the cloud.

Conclusion: Continuous Testing in DevOps significantly enhances cloud migration for P&C insurers by improving speed-to-market, quality, and compliance. According to this discussion, automation is the key enabler for cloud adoption, which in turn mitigates risk and improves operational agility. One could advocate that P&C insurers' ability to pursue a CT division in the cloud epoch is tantamount to ensuring the unremitting progress of digital transformation.