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Agentic_aiml~20 mins

Scaling agents horizontally in Agentic Ai - Practice Problems & Coding Challenges

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Challenge - 5 Problems
🎖️
Horizontal Scaling Master
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Test your skills under time pressure!
🧠 conceptual
intermediate
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Understanding horizontal scaling of agents

Imagine you have a team of helpers (agents) working on a task. What does it mean to scale these agents horizontally?

ACombining multiple agents into one bigger agent.
BMaking each agent work faster by improving its code.
CAdding more agents to work in parallel on the task.
DReducing the number of agents to save resources.
Attempts:
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model choice
intermediate
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Choosing the right approach for horizontal scaling

You want to scale your AI agents horizontally to handle more user requests simultaneously. Which approach best supports this goal?

ADeploy multiple independent agent instances behind a load balancer.
BOptimize a single agent to use GPU acceleration.
CReduce the agent's response time by simplifying its logic.
DIncrease the memory of the machine running the agent.
Attempts:
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💻 code output
advanced
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Output of agent scaling simulation code

What is the output of the following Python code simulating agent task completion times when scaling horizontally?

Agentic_ai
import random

def simulate_agents(num_agents, tasks_per_agent):
    times = []
    for _ in range(num_agents):
        agent_time = sum(random.uniform(0.8, 1.2) for _ in range(tasks_per_agent))
        times.append(agent_time)
    return max(times)

random.seed(0)
result = simulate_agents(3, 5)
print(round(result, 2))
A6.00
B5.00
C4.75
D5.51
Attempts:
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metrics
advanced
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Evaluating horizontal scaling efficiency

You measure the throughput (tasks per second) of your agent system as you add more agents horizontally. Which metric best shows how efficiently the system scales?

AAccuracy of each agent's predictions
BSpeedup = Throughput with N agents / Throughput with 1 agent
CLatency of a single task processed by one agent
DMemory usage per agent
Attempts:
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🔧 debug
expert
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Debugging horizontal scaling bottleneck

You horizontally scaled your agents by adding more instances, but the system's throughput did not improve as expected. Which issue below most likely causes this bottleneck?

AA shared resource like a database is limiting concurrent access.
BEach agent instance has too much CPU power.
CAgents are running on separate machines with network isolation.
DThe number of agents is too high, causing perfect scaling.
Attempts:
2 left