Maximum Throughput of a Data Processing Pipeline - Atlassian Online Assessment

Problem Preview

"### Problem A data processing pipeline consists of n services connected in series where the output of service i serves as input to service i+1. Each service has varying latency, and the throughput of the ith service is represented by throughput[i] in messages per minute. Each service can be scaled up independently. Scaling up the ith service one unit of time costs scalingCost[i], and after scaling up x times, the service can process (throughput[i])^(1 + x) messages per minute. Given throughput and scalingCost arrays of size n, and a budget value, determine the optimal scaling configuration to maximize the throughput of the final service. Return the maximum throughput possible. ### Input - int throughput[n]: the throughput generated by each of the n services - int scalingCost[n]: the cost of scaling up a service one time - int budget: the available money ### Output - long int: the maximum value of the throughput generated at the end of the composite service after scaling within the budget "