How can AI and machine learning create business value?

Edge AI changing the industry in 2025 by enabling real-time performance, on-device intelligence, reducing costs, improving data privacy & privacy, and enhancing system resilience.

Use feature flags to expose Vertex AI features only to pilot users based on attributes like role or email. Enforce access with IAM roles and conditions, and isolate usage in a separate GCP project or folder. Monitor activity with audit logs and usage metrics.

The safest way to roll out updates on Amazon Bedrock without risking peak-hour outages is to use a canary deployment strategy. This technique involves directing a small, incremental percentage of live traffic to the new model or configuration while closely monitoring its performance. If any issues are detected, traffic can be instantly routed back to the stable version, mitigating risk during peak hours.

The blue/green method, while effective, can be less granular and riskier for AI models, where behavior changes are more subtle. Canary deployments provide fine-grained control and a real-world testing period.

Automation testing tools can be categorized by the type of application they test (web, mobile, API, desktop), the type of testing they perform (unit, functional, regression, performance, security), or the testing framework they are built on (linear, data-driven, keyword-driven, hybrid). Popular tools include Selenium (web), Appium (mobile), Postman (API), JUnit (unit testing), and JMeter (performance).

Yes, you can generate code using generative AI models.