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AZ-204 Practice Question: Connect to and consume Azure services and third-party services

An application calls a Event Grid event stream through HTTP. The developer must implement retries without overwhelming the remote system during partial outages. Which retry pattern is best?

⚠ Common exam trap

Test-takers frequently think immediate retries or disabling timeouts are acceptable for reliability, but Azure explicitly recommends exponential backoff with jitter and a cap to protect both the client and the service from overload during outages.

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

Exponential backoff with jitter and a maximum retry limit

Exponential backoff with jitter and a maximum retry limit is the best pattern because it prevents overwhelming the Event Grid endpoint during partial outages by progressively increasing wait times between retries, while jitter randomizes those intervals to avoid thundering herd problems. The maximum retry limit ensures the system does not retry indefinitely, aligning with Event Grid's own retry policy (which uses exponential backoff up to 30 minutes and a max of 30 retries for HTTP 5xx errors). This balances resilience with resource protection.

Answer analysis

Option-by-option breakdown

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

  • Immediate infinite retries

    Why it's wrong here

    Immediate and infinite retries are highly detrimental as they can overwhelm a struggling remote service, preventing its recovery and potentially amplifying an outage into a distributed denial-of-service (DDoS) scenario. This approach also consumes client resources indefinitely, lacking any mechanism for graceful degradation or eventual failure handling, making the client itself unstable.

  • Retry only after restarting the application

    Why it's wrong here

    Restarting an entire application to handle a transient network or service error is an extremely heavy-handed and inefficient approach to resilience. This action introduces significant downtime, causes loss of in-memory state, and is not a controlled programmatic pattern for addressing temporary faults. Such a method is disproportionate to the problem and fails to provide a seamless recovery experience.

  • Disable all timeout settings

    Why it's wrong here

    Disabling all timeout settings for HTTP calls is a critical anti-pattern that severely compromises application stability and resource management. Without defined timeouts, client threads can remain indefinitely blocked waiting for responses from an unresponsive Event Grid endpoint, leading to thread pool exhaustion and resource starvation. This ultimately results in cascading failures across the application, preventing it from failing fast or recovering gracefully.

  • Exponential backoff with jitter and a maximum retry limit

    Why this is correct

    This strategy is optimal for handling transient faults by progressively increasing the delay between retries, allowing the remote service time to recover without being overwhelmed. Jitter adds a random component to these delays, preventing a 'thundering herd' problem where multiple clients retry simultaneously and exacerbate the issue. The maximum retry limit ensures the application eventually gives up on persistent failures, conserving resources and enabling alternative error handling.

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Last reviewed: Jun 11, 2026

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