Challenge - 5 Problems
Horizontal Scaling Master
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Test your skills under time pressure!
🧠 conceptual
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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?
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❓ model choice
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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?
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💻 code output
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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))
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❓ metrics
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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?
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🔧 debug
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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?
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