AI/ML trends
The integration of AI and ML into DevOps, DevSecOps, and SRE practices is rapidly transforming how teams approach continuous testing, quality, security, and feedback. The rising need for AI/ML solutions is driven by the increasing complexity of systems, the volume of data generated, and the demand for faster, more efficient delivery cycles. Here’s how AI/ML is likely to impact these crucial areas:
- Continuous testing:
- Automated test creation and optimization: AI/ML can analyze application data and user interactions to automatically generate and optimize test cases, reducing the manual effort required in test creation. This leads to broader test coverage and more efficient testing processes, ensuring that all relevant application scenarios are accounted for.
- Predictive analytics for flaw detection: ML algorithms can predict potential flaws based on historical data, enabling teams to focus testing efforts where they are most needed before defects become apparent...
