In our current logic (https://github.com/Netflix-Skunkworks/service-capacity-modeling/blob/main/service_capacity_modeling/models/org/netflix/key_value.py#L85), we scale the C* cluster by a factor of `1 - estimated_kv_cache_hit_rate`, where `estimated_kv_cache_hit_rate` is configurable (default 0.8). Per a previous convo with @jolynch and @szimmer1, we discussed possibly tying in the read/write ratio from the user desires into this calculation. One toy example: ``` estimated_cache_hit_rate = extra_model_arguments.get("estimated_cache_hit_rate", 0.8) estimated_cache_miss_rate = 1 - estimated_cache_hit_rate rps_interval.scale(min(estimated_cache_miss_rate, max(0.1, 1 - read_write_ratio))) ```
In our current logic (https://github.com/Netflix-Skunkworks/service-capacity-modeling/blob/main/service_capacity_modeling/models/org/netflix/key_value.py#L85), we scale the C* cluster by a factor of
1 - estimated_kv_cache_hit_rate, whereestimated_kv_cache_hit_rateis configurable (default 0.8).Per a previous convo with @jolynch and @szimmer1, we discussed possibly tying in the read/write ratio from the user desires into this calculation.
One toy example: