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Cloud Digital Leader Practice Question: A company hosts a web application that receives…
A company hosts a web application that receives requests from users globally. To handle failures, they run three identical copies of their application behind a load balancer. When one copy fails, the load balancer automatically stops sending traffic to it. What load balancing feature enables this?
⚠ Common exam trap
The GCDL exam often tests the distinction between traffic distribution algorithms (like round-robin) and health monitoring features, leading candidates to mistakenly believe that round-robin inherently handles failures because it 'spreads traffic evenly,' when in fact it has no awareness of instance health.
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
✓
Health checks — the load balancer probes backend instances and removes unhealthy ones from the serving pool.
Health checks are the load balancing feature that proactively monitors the status of backend instances by sending periodic probes (e.g., HTTP GET requests, TCP SYN packets) to a configured endpoint. If a health check fails (e.g., non-2xx response, timeout, or connection refused), the load balancer automatically marks that instance as unhealthy and stops routing new traffic to it, ensuring high availability and fault tolerance.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Round-robin distribution — traffic cycles evenly across all instances regardless of health.
Why it's wrong here
Round-robin distribution is a simple scheduling algorithm that cycles traffic evenly across all backend instances, but it does not incorporate any liveness or health signals. When an instance fails or becomes unhealthy, the load balancer continues to forward requests to it, causing intermittent connection errors and failed responses for a portion of client traffic. It is a pure load-balancing policy, not a fault-detection mechanism, so it cannot automatically remove failed backends from the active rotation.
- ✓
Health checks — the load balancer probes backend instances and removes unhealthy ones from the serving pool.
Why this is correct
Health checks are the load balancer's active fault-detection mechanism: it sends periodic probe requests (e.g., HTTP GET, TCP connect, or gRPC health check) to each backend on a configured interval and at a specific path or port. If a backend fails to respond within a timeout or returns an unexpected status code, the load balancer marks it as unhealthy and stops routing new connections to it until it passes the health check again. This continuous probing enables automatic removal of failed instances and ensures traffic is only distributed to backends that can actually serve requests, which is exactly why it is the correct answer.
- ✗
SSL termination — decrypting HTTPS traffic before forwarding to backends.
Why it's wrong here
SSL termination offloads cryptographic decryption from backend instances by having the load balancer terminate the HTTPS connection, decrypt the traffic, and then forward plaintext HTTP to the backends. This reduces CPU load on the application servers and centralizes certificate management, but it is entirely a security/perfomance feature that says nothing about the operational status of those backends. It neither probes for liveness nor influences which instances remain in the serving pool, so it is irrelevant to the problem of detecting and removing failed backends.
- ✗
Session affinity — routing the same user to the same backend instance.
Why it's wrong here
Session affinity, also known as sticky sessions, uses a cookie, source IP, or application-generated key to consistently route a specific client to the same backend instance. This is intended to preserve in-memory session state across requests, but it does not evaluate whether that backend is alive; if the chosen instance is down, the user's traffic will be sent to a dead endpoint, or the load balancer may fail over in a way that ignores stickiness. It is a statefulness feature, not a health-aware failover mechanism, so it cannot proactively detect and remove unhealthy backends.
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Related to this question
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High Availability: 99.9% vs 99.99% vs 99.999%
Key term
Fault tolerance
Fault tolerance is the ability of a system to continue operating properly even when one or more of its components fail.
Key term
Load balancer
A load balancer is a device or software that distributes incoming network traffic across multiple servers so no single server gets overwhelmed.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This GCDL practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the GCDL exam.