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How can you implement A/B testing for a new product recommendation algorithm in an ecommerce application deployed behind a global HTTP(S) load balancer to evaluate its impact on sales through randomized user allocation?
A
Split traffic between versions using weights.
B
Enable the new recommendation feature flag on a single instance.
C
Mirror traffic to the new version of your application.
D
Use HTTP header-based routing.
