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200-901 Practice Question: A DevOps team manages a multi-site Cisco Meraki…

A DevOps team manages a multi-site Cisco Meraki network with 50 MX appliances and 200 MR access points. They use a Python script that calls the Meraki API to collect device utilization data every hour and stores it in a CSV file. Recently, the script started failing intermittently with HTTP 429 status codes. The team suspects rate limiting but notices that the failures occur even when only one script instance runs. The script uses a single API key and makes requests to the /devices/{serial}/uplink endpoint for each MX and the /devices/{serial}/wireless/status endpoint for each MR. The script is scheduled via cron and runs sequentially. The team wants to resolve the rate limiting while minimizing changes to the script. Which course of action should the team take?

⚠ Common exam trap

Cisco often tests the misconception that rate limiting can be solved by distributing requests across multiple keys, but the trap here is that the rate limit applies per key and the script's sequential nature means a single key is sufficient if delays are added.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Introduce a delay between API calls to stay within the rate limit.

The intermittent HTTP 429 errors indicate the script is exceeding the Meraki API rate limit, which applies per API key. Since the script runs sequentially with a single key, introducing a delay between API calls (e.g., using time.sleep()) is the simplest fix that stays within the rate limit without requiring architectural changes. This directly addresses the root cause while minimizing modifications to the existing script.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Introduce a delay between API calls to stay within the rate limit.

    Why this is correct

    Adding a small delay reduces request rate and avoids 429 errors.

  • Distribute the API requests across multiple API keys.

    Why it's wrong here

    While distributing requests across multiple API keys is a common strategy to overcome rate limits, it fails here because the problem isn't the *number* of requests originating from a single source, but rather the *total volume* of requests hitting the Meraki API within a given timeframe. This option is tempting as it addresses the symptom of hitting a limit, and would be correct if the rate limit was tied to a specific API key's usage, rather than an account-wide or IP-based limit.

  • Switch to a webhook-based approach to receive data instead of polling.

    Why it's wrong here

    Requires significant re-architecture and is not minimal.

  • Use the bulk API request feature to collect data in fewer calls.

    Why it's wrong here

    Meraki does not have a bulk endpoint for these data.

Visual reference

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

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