PCDOE Optimizing service performance Practice Test 7 — 15 Questions

Question 1

A company wants to reduce the response time of a globally distributed web application. Which Google Cloud service can cache static content at edge locations to improve performance?

Accepted Answer

Cloud CDN. Cloud CDN (Content Delivery Network) uses Google's globally distributed edge caches to serve static content (e.g., images, CSS, JavaScript) from locations closer to users, reducing latency and offloading origin servers. It integrates with external HTTPS load balancers to automatically cache responses based on cache-control headers, directly addressing the goal of improving response time for a globally distributed web application.

Answer

Cloud DNS

Answer

Cloud NAT

Answer

Cloud Armor

Question 2

A team is using Cloud Run for a containerized application. They notice that requests have high latency due to cold starts. Which configuration change would most effectively reduce cold start latency?

Accepted Answer

Set the min-instances parameter to a value > 0. Setting the `min-instances` parameter to a value greater than 0 keeps a baseline number of container instances always warm and ready to serve requests. This eliminates the cold start penalty because the runtime environment, including the container and its dependencies, is already initialized and listening for traffic. Cloud Run will scale down to this minimum count, ensuring that new requests are routed to pre-warmed instances rather than triggering a new container startup.

Answer

Enable concurrent requests

Answer

Increase the function timeout

Answer

Reduce the container image size

Question 3

A DevOps team wants to optimize resource utilization for their GKE deployment. Which built-in Kubernetes resource can automatically adjust CPU and memory requests based on historical usage?

Accepted Answer

VerticalPodAutoscaler. The VerticalPodAutoscaler (VPA) is the correct choice because it automatically adjusts CPU and memory resource requests (and limits) for pods based on historical usage data, optimizing resource utilization without manual intervention. Unlike the HorizontalPodAutoscaler, which scales the number of pods, the VPA modifies the resource specifications of existing pods to match observed demand.

Answer

HorizontalPodAutoscaler

Answer

ResourceQuota

Answer

PodDisruptionBudget

Question 4

Which service should be used to monitor the health of HTTP endpoints from multiple locations?

Accepted Answer

Cloud Monitoring. Cloud Monitoring (formerly Stackdriver Monitoring) includes uptime checks that can be configured to probe HTTP endpoints from multiple global locations, measuring latency, availability, and response content. This makes it the correct service for monitoring the health of HTTP endpoints from diverse geographic regions.

Answer

Cloud Trace

Answer

Cloud Logging

Answer

Cloud Debugger

Question 5

Which Cloud Run setting controls the maximum number of requests a container can handle concurrently?

Accepted Answer

concurrency. The `concurrency` setting in Cloud Run defines the maximum number of simultaneous requests that a single container instance can process at any given time. This directly controls how many requests are routed to a single container before Cloud Run spins up additional instances, optimizing resource utilization and preventing overload.

Answer

timeout

Answer

max-instances

Answer

min-instances

Question 6

Which tool can be used to capture and analyze latency spikes in a distributed application?

Accepted Answer

Cloud Trace. Cloud Trace is the correct tool for capturing and analyzing latency spikes in a distributed application because it provides end-to-end latency tracking by instrumenting requests as they traverse microservices. It collects trace spans with timing data, allowing you to identify bottlenecks and pinpoint the exact service or operation causing the spike.

Answer

Cloud Logging

Answer

Cloud Debugger

Answer

Cloud Monitoring

Question 7

Which storage class provides the lowest cost for data accessed less than once a year?

Accepted Answer

Archive. Archive storage class is the correct answer because it is specifically designed for long-term data retention where access is extremely infrequent, such as less than once a year. It offers the lowest storage cost among Google Cloud Storage classes, but with higher retrieval costs and a minimum storage duration of 365 days, making it ideal for data that is rarely accessed.

Answer

Nearline

Answer

Standard

Answer

Coldline

Question 8

Which service is commonly used for time-series data and real-time analytics?

Accepted Answer

Bigtable. Bigtable is a fully managed, scalable NoSQL database optimized for large analytical and operational workloads, including time-series data and real-time analytics. It provides sub-10ms latency for high-throughput reads and writes, making it ideal for IoT, monitoring, and financial data streams. Its column-oriented storage and automatic sharding support efficient time-based queries and aggregation.

Answer

Cloud SQL

Answer

Firestore

Answer

Cloud Spanner

Question 9

A company runs a high-traffic web application on GKE. Which three practices can help optimize performance under load? (Select THREE.)

Accepted Answer

Use a global load balancer. Option A (Use a global load balancer) is correct because a Google Cloud global external load balancer distributes traffic across multiple regions using anycast IP and Google's global edge network, reducing latency and absorbing load spikes for a high-traffic web application on GKE. Option C (Store session state in Cloud Memorystore) is correct because externalizing session state to a managed Redis/Memcached service makes pods stateless, allowing horizontal scaling and even distribution of requests without session affinity bottlenecks. Option D (Enable HorizontalPodAutoscaler with custom metrics) is correct because HPA with custom metrics (e.g., via Stackdriver/Cloud Monitoring adapters) scales pod replicas based on application-level signals like requests per second or queue depth, matching capacity to real load rather than just CPU. Option B (Use a multi-cluster ingress) is not among the correct answers because it addresses multi-cluster traffic routing and failover rather than directly optimizing performance under load for a single GKE workload. Option E (Increase the number of nodes to maximum) is not among the correct answers because blindly maximizing node count is costly and inefficient without autoscaling policies tied to actual demand.

Answer

Use a multi-cluster ingress

Answer

Increase the number of nodes to maximum

Question 10

Refer to the exhibit. A DevOps engineer observes that a GKE cluster's node performance is degraded during high I/O workloads. Based on the exhibit, which change would most likely improve disk I/O performance?

Accepted Answer

Change diskType to pd-ssd. The exhibit shows a GKE node pool using the default pd-standard disk type, which is backed by HDDs and has lower IOPS and throughput compared to SSDs. Changing diskType to pd-ssd directly improves disk I/O performance by providing higher IOPS and lower latency, which is critical for high I/O workloads.

Answer

Change machineType to n2-standard-4

Answer

Change imageType to UBUNTU

Answer

Change serviceAccount to a custom one

Question 11

Refer to the exhibit. A team is troubleshooting a pod crash loop. Based on the exhibit, which infrastructure change should be prioritized to resolve the issue and optimize service performance?

Accepted Answer

Mount a ConfigMap or volume containing the missing file. The exhibit indicates a pod crash loop caused by a missing file, which is a configuration issue rather than a resource or scheduling problem. Mounting a ConfigMap or volume that provides the missing file directly resolves the crash by ensuring the pod has the required configuration at startup. This fix also optimizes service performance by eliminating unnecessary restarts and allowing the pod to serve traffic consistently.

Answer

Increase the pod's CPU request

Answer

Increase the maximum number of pods per node

Answer

Enable pod anti-affinity

Question 12

A company serves static assets (images, CSS) to global users. Users in distant regions experience slow load times. Which service should they use to optimize delivery?

Accepted Answer

Cloud CDN. Cloud CDN (Content Delivery Network) caches static assets (images, CSS) at edge locations worldwide, reducing latency for distant users by serving content from a nearby point of presence (PoP). This directly addresses slow load times caused by geographic distance, as the origin server is no longer the sole source of delivery.

Answer

Cloud Load Balancing

Answer

Cloud NAT

Answer

Cloud Armor

Question 13

An application running on GKE experiences high latency during traffic spikes. The team wants to scale pods based on request latency. Which metric should they use in the HorizontalPodAutoscaler?

Accepted Answer

Custom metric: request latency percentile (e.g., p95). To scale based on request latency, the HorizontalPodAutoscaler (HPA) must use a custom metric that directly reflects the application's response time, such as the p95 latency percentile. CPU or memory utilization are system-level metrics that do not capture the user-perceived performance degradation caused by traffic spikes. Custom metrics like request count correlate with load but not directly with latency, making the p95 latency percentile the correct choice for latency-based autoscaling.

Answer

Custom metric: request count

Answer

Memory utilization

Answer

CPU utilization

Question 14

A team notices that a Cloud Run service occasionally has high latency. They suspect a memory leak or excessive CPU usage. Which tool should they use to identify the bottleneck during those periods?

Accepted Answer

Cloud Profiler. Cloud Profiler is the correct tool because it continuously gathers CPU and memory usage data from your Cloud Run service, allowing you to identify which functions or code paths are consuming excessive resources during high-latency periods. Unlike monitoring or logging, Profiler provides a flame graph that pinpoints the exact bottleneck (e.g., a memory leak or CPU spike) at the function level, which is essential for diagnosing performance issues in a serverless environment.

Answer

Cloud Trace

Answer

Cloud Monitoring

Answer

Cloud Logging

Question 15

A web application frequently reads the same set of reference data from Cloud SQL. This causes high database load and slow responses. Which design change would most improve performance?

Accepted Answer

Implement caching with Memorystore for Redis. Caching the frequently read reference data in Memorystore for Redis offloads repeated reads from Cloud SQL, dramatically reducing database load and improving response times. Reference data is typically read-heavy and changes infrequently, making it an ideal caching candidate. This is the most direct design change to address the bottleneck.

Answer

Increase Cloud SQL machine size

Answer

Add a read replica

Answer

Use Cloud Spanner for higher throughput