PCDOE Optimizing service performance Practice Test 4 — 15 Questions

Question 1

A company's Cloud SQL for PostgreSQL instance is experiencing performance degradation. They observe a high number of idle connections and slow transaction commit times. Which combination of actions will most effectively address this issue?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Configure statement timeout and use PgBouncer for connection pooling.. The high number of idle connections and slow transaction commit times indicate connection management and resource contention issues. PgBouncer reduces overhead by pooling and reusing database connections, while statement timeout prevents long-running queries from holding locks and consuming resources, directly addressing both symptoms.

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Add a read replica and route read-only queries to it.

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Increase the storage size and enable automatic backup.

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Drop unused indexes and run VACUUM.

Question 2

A web application serves static assets (images, CSS, JavaScript) from Compute Engine instances. Users in different geographic regions report slow page loads. Which Google Cloud service can be used to improve performance for these users?

Accepted Answer

Cloud CDN. Cloud CDN (Content Delivery Network) caches static assets at Google's globally distributed edge points of presence (PoPs). When users request images, CSS, or JavaScript, the content is served from the nearest edge cache rather than the origin Compute Engine instances, reducing latency and improving page load times for geographically distributed users.

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VPC Network Peering

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Cloud Load Balancing

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Cloud NAT

Question 3

A company is migrating a batch processing workload to Google Cloud. The workload is CPU-intensive and runs for a few hours each day. Which Compute Engine machine family should they choose to optimize performance and cost?

Accepted Answer

Compute-optimized (C2/C2D). A is correct because the workload is CPU-intensive and runs for a few hours each day, which is a sustained, compute-bound task. Compute-optimized machines (C2/C2D) are designed specifically for high-performance computing (HPC) and batch processing, offering the highest ratio of vCPU to memory and the fastest single-threaded performance on Google Cloud. This minimizes runtime and cost per job compared to general-purpose or burstable families.

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Burstable (T2D)

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GPU-accelerated (A2)

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Memory-optimized (M2)

Question 4

A Cloud Run service experiences high latency during cold starts. The service is memory-intensive. Which configuration change will most effectively reduce cold start latency?

Accepted Answer

Set a minimum number of instances.. Setting a minimum number of instances ensures that a baseline of pre-warmed instances is always running, eliminating cold starts for the initial requests. For a memory-intensive service, this avoids the latency penalty of loading large libraries or datasets into memory on first invocation. This is the most direct and effective configuration change to reduce cold start latency.

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Decrease the container concurrency setting.

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Increase the max instances limit.

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Enable CPU boost for the service.

Question 5

A DevOps team wants to serve static content from a Cloud Storage bucket with low latency globally. They also need TLS termination. Which load balancer type should they use?

Accepted Answer

External HTTP(S) Load Balancer. External HTTP(S) Load Balancer is the correct choice because it provides global anycast IP addresses, TLS termination at the Google Front End (GFE), and integrates directly with Cloud Storage buckets as a backend. This enables low-latency content delivery worldwide while offloading SSL decryption to the load balancer.

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External Network Load Balancer

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SSL Proxy Load Balancer

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Internal HTTP(S) Load Balancer

Question 6

An application on GKE frequently reads the same data from a Cloud Storage bucket. The data changes rarely. Which solution will best improve read performance and reduce costs?

Accepted Answer

Deploy a sidecar container that caches the data in an emptyDir volume.. Deploying a sidecar container with an emptyDir volume caches frequently accessed, rarely changing data locally within the pod. This reduces latency by avoiding repeated network calls to Cloud Storage and eliminates egress and operation costs for those reads. emptyDir volumes are ephemeral and tied to the pod's lifecycle, making them ideal for caching read-heavy, static data without incurring persistent storage costs.

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Configure a Cloud SQL read replica for the data.

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Increase the number of nodes in the cluster.

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Use a StatefulSet with a persistent volume claim to store the data.

Question 7

A company is transferring large datasets from on-premises to Google Cloud using a VPN. They notice high latency due to packet loss. What is the most effective way to improve throughput?

Accepted Answer

Set up Dedicated Interconnect for a more reliable connection.. Dedicated Interconnect provides a direct, private physical connection between on-premises and Google Cloud, bypassing the public internet entirely. This eliminates the packet loss and high latency inherent in VPN tunnels over the internet, offering consistent throughput and lower latency for large dataset transfers.

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Enable compression on the VPN tunnel.

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Increase the number of VPN tunnels and use BGP multipath.

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Use a multi-region GCP endpoint and distribute traffic.

Question 8

Which TWO practices should be implemented to optimize query performance in Cloud Spanner?

Accepted Answer

Use interleaved tables to co-locate related rows.. Interleaved tables in Cloud Spanner physically co-locate parent and child rows on the same split, reducing cross-node round trips and improving join performance. This design leverages Spanner's hierarchical storage model to minimize latency for queries that access related data together.

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Split large tables into multiple smaller tables to distribute load.

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Create as many indexes as possible on all columns.

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Use globally distributed interleaving across regions.

Question 9

Which THREE strategies can reduce API latency in Apigee?

Accepted Answer

Enable response compression in the API proxy.. Enabling response compression (e.g., gzip) reduces the size of payloads transferred over the network, directly lowering latency by decreasing transmission time. Apigee supports automatic compression via the AssignMessage policy or by setting the Accept-Encoding header, which is especially effective for text-based responses like JSON or XML.

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Disable TLS termination to reduce overhead.

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Increase the analytics data collection frequency.

Question 10

Which TWO actions can reduce startup latency for a Cloud Run service?

Accepted Answer

Optimize the container image to reduce size.. A smaller container image reduces the time required to pull the image from the registry to the compute node during cold starts. Cloud Run's startup latency is dominated by image download and filesystem extraction; optimizing the image (e.g., using distroless base images, multi-stage builds, or removing unnecessary layers) directly shortens this critical path.

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Use a regional Cloud Run with separate service per region.

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Increase the maximum instances limit.

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Increase the container concurrency setting.

Question 11

Refer to the exhibit. A DevOps engineer notices that instance-1 runs on older CPU platform. The application is sensitive to CPU features that are only available on Skylake or newer. Which action should be taken to optimize performance?

Accepted Answer

Stop instance-1 and update the minimum CPU platform to Skylake.. Stopping the instance and updating the minimum CPU platform to Skylake ensures that the instance is rescheduled onto a host that meets the required CPU feature set. This action directly addresses the application's sensitivity to CPU features available only on Skylake or newer, without requiring a full recreation or risking compatibility issues during live migration.

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Live migrate instance-1 to a different host.

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Use Terraform to add a lifecycle rule to ignore changes.

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Terminate instance-1 and recreate it with a newer machine type.

Question 12

Refer to the exhibit. After applying the shown firewall rule, users report increased latency to a web application. What is the most likely cause?

Accepted Answer

The rule contains both allow and deny for the same traffic, creating a conflict.. In Google Cloud VPC firewall rules, a single rule cannot specify both allow and deny actions. The rule shown is invalid because it combines both actions for the same traffic, which can lead to undefined behavior. This misconfiguration can cause the firewall to improperly deny traffic that should be allowed, resulting in connectivity issues and increased latency due to retries or timeouts. Option B correctly identifies this conflict. Option A is wrong because priority 1000 is not low (lower number higher priority); logging alone does not cause significant latency. Option C is wrong because a broad source range does not inherently cause latency. Option D is wrong because the rule's priority is not the issue here.

Answer

The rule priority is set to 1000, which is too low.

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The source range covers all IPs, causing excessive traffic.

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The firewall rule has logging enabled, which adds overhead.

Question 13

Refer to the exhibit. What does the alert condition indicate?

Accepted Answer

It alerts for any Cloud Run revision that has more than 1000 requests in a 1-minute window.. The alert condition in the exhibit uses a per-revision metric (e.g., `run.googleapis.com/request_count`) with a threshold of 1000 and a 1-minute window. This means the alert fires for any individual Cloud Run revision that exceeds 1000 requests within that window, not for the aggregate across all revisions. Option B correctly identifies this per-revision behavior.

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It alerts when the request count drops below 1000 for 1 minute.

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It alerts when the average request count across all revisions exceeds 1000 over 1 minute.

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It alerts when the total request count across all revisions exceeds 1000 per minute.

Question 14

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.

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Cloud DNS

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Cloud NAT

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Cloud Armor

Question 15

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.

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Enable concurrent requests

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Increase the function timeout

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Reduce the container image size