Generative AI is revolutionizing business, but Quality Assurance (QA) is often overlooked. Many companies still use manual testing, leading to delays and defects. AI can enhance QA, not replace testers, by automating test case generation and creating realistic test data. This reduces test creation time by 50-70% and improves coverage. Predictive defect analysis using AI can also identify high-risk code areas before deployment, reducing production defects.

Best practices for cloud-native apps. Single codebase, explicit dependencies, env config. Backing services as resources. Build, release, run separate. Stateless processes, port binding. Scale via concurrency, ensure disposability. Dev/prod parity. Logs as streams. Admin processes same code/config. Updated for Kubernetes, GitOps, security. Key for modern apps.

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