Google PCA Analyze and optimize technical and business processes Practice Test 4 — 15 Questions

Question 1

A company has a multi-region deployment of App Engine and wants to optimize request routing for latency and cost. Which GCP service should they use?

Accepted Answer

Cloud Load Balancing with global anycast.. Cloud Load Balancing with global anycast uses Google's global network and anycast IP addresses to route user traffic to the nearest healthy backend, minimizing latency. It also supports premium tier routing for lower latency and standard tier for lower cost, directly addressing the optimization goals for a multi-region App Engine deployment.

Answer

Cloud Endpoints.

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Cloud DNS with latency-based routing.

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Cloud Traffic Director.

Question 2

Which TWO actions can reduce costs for a Cloud SQL for MySQL instance? (Choose two.)

Accepted Answer

Use committed use discounts.. Committed use discounts (CUDs) provide significant cost savings (up to 57%) for Cloud SQL instances when you commit to a 1- or 3-year term. Resizing to a smaller machine type during off-peak hours directly reduces compute costs by lowering the vCPU and memory allocation when demand is low, and Cloud SQL supports live instance resizing with minimal downtime.

Answer

Use database flags to limit connections.

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Use preemptible instances.

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Use high availability configuration.

Question 3

Which TWO strategies should a company implement to optimize costs for a production GKE cluster? (Choose two.)

Accepted Answer

Enable GKE usage metering.. Option C is correct because GKE usage metering provides detailed cost allocation by breaking down cluster resource consumption (CPU, memory, storage) per Kubernetes namespace or label. This enables teams to track and optimize spending across different projects or departments, directly supporting cost optimization for a production cluster.

Answer

Use Istio for traffic management.

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Use a regional cluster.

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Use node local DNS cache.

Question 4

Which THREE steps can reduce processing costs in a Dataflow streaming pipeline? (Choose three.)

Accepted Answer

Use side inputs instead of a cross join.. Option A is correct because side inputs allow you to broadcast a static or slowly-changing dataset to all workers, avoiding the expensive shuffle and per-element processing required by a cross join. In Dataflow, cross joins in streaming mode require stateful processing and can lead to high data amplification, whereas side inputs are distributed efficiently via the streaming engine. This reduces both CPU and memory costs by eliminating redundant data movement.

Answer

Use a custom runner.

Answer

Increase the number of workers.

Question 5

Refer to the exhibit. The output is from `gcloud compute instances describe instance-1 --format=json`. What can you conclude from this output?

Accepted Answer

The instance is billed based on the n1-standard-2 machine type.. The output from `gcloud compute instances describe instance-1 --format=json` would include a `machineType` field that specifies the full URL of the machine type, such as `https://www.googleapis.com/compute/v1/projects/.../zones/.../machineTypes/n1-standard-2`. This confirms the instance is using the predefined n1-standard-2 machine type, which has 2 vCPUs and 7.5 GB of memory, and billing is based on that predefined type. The absence of a `custom` suffix or custom CPU/memory values in the machine type field indicates it is not a custom machine type.

Answer

The instance is using a custom machine type.

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The instance is using committed use discounts.

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The instance has a GPU attached.

Question 6

Refer to the exhibit. This is an IAM policy for a BigQuery dataset. What does the policy allow?

Accepted Answer

Alice to view data and analysts to run jobs.. The policy grants the `roles/bigquery.dataViewer` role to Alice, which allows her to view dataset metadata and query data, and the `roles/bigquery.jobUser` role to analysts, which allows them to run jobs (queries, load, export) but not view data directly. This combination matches option A.

Answer

Alice and analysts to run jobs.

Answer

Alice to run jobs and analysts to view data.

Answer

Alice and analysts to view data.

Question 7

Refer to the exhibit. The log entry is from Cloud Logging for a VPC subnetwork. What is the most likely cause of this error?

Accepted Answer

A firewall rule blocking ingress on port 80.. The log entry indicates a packet was dropped by a firewall rule. Since the destination is 10.0.0.2 on port 80 (HTTP), the most likely cause is a firewall rule blocking ingress traffic on port 80. In Google Cloud VPC, firewall rules are stateful and evaluated before any routing decisions, so a missing or misconfigured ingress rule for TCP port 80 would cause this drop.

Answer

The subnetwork default has no internet gateway.

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The VM at 10.0.0.2 is not running.

Answer

The packet is malformed.

Question 8

A company runs a web application on Compute Engine instances. The application stores session state in files on local SSD. The company wants to reduce costs without sacrificing performance for a predictable traffic pattern. What should they do?

Accepted Answer

Use preemptible VMs in a managed instance group with autoscaling, and store session state in Redis (Memorystore).. Option A is correct because preemptible VMs reduce compute costs by up to 80%, and using a managed instance group with autoscaling handles the predictable traffic pattern efficiently. Storing session state in Redis (Memorystore) instead of local SSD ensures session data persists across VM preemptions and is shared among instances, which is critical for stateful applications. This combination maintains performance while eliminating the cost of always-on VMs.

Answer

Change the machine type to N2 standard and use committed use discounts.

Answer

Keep local SSDs but use sole-tenant nodes to reduce contention.

Answer

Migrate the session state to Cloud Firestore and use preemptible VMs.

Question 9

You are running a Cloud Run service that experiences occasional cold starts causing latency spikes. You want to minimize cold starts cost-effectively. What should you do?

Accepted Answer

Set min-instances to 1 to keep at least one instance always warm.. Setting min-instances to 1 ensures that at least one instance of your Cloud Run service is always kept warm, meaning it is initialized and ready to handle requests immediately. This eliminates cold starts for the first request after a period of inactivity, reducing latency spikes without requiring over-provisioning of resources. It is cost-effective because you only pay for the idle instance when it is not serving traffic, and you avoid the higher costs of larger machine types or excessive concurrent instances.

Answer

Increase the max-instances setting to allow more concurrent requests.

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Set concurrency to 1 to ensure each instance handles one request at a time.

Answer

Use a larger machine type (e.g., 2 vCPU) to reduce startup time.

Question 10

A company runs batch processing jobs on a GKE cluster using preemptible node pools. The jobs are fault-tolerant and can be interrupted. However, the cluster is experiencing high costs due to underutilized nodes. The batch jobs run for 2-3 hours each. What is the most cost-effective optimization?

Accepted Answer

Create multiple node pools with different machine types and use node auto-provisioning with preemptible nodes and custom machine types.. Option D is the most cost-effective because it leverages node auto-provisioning with preemptible nodes and custom machine types, which dynamically creates node pools tailored to the specific resource requirements of each batch job. This eliminates waste from over-provisioned nodes while maintaining fault tolerance for interruptible workloads. Combined with preemptible instances (up to 60-80% cheaper than regular VMs), this approach minimizes cost without sacrificing job completion, as the jobs are already designed to handle interruptions.

Answer

Switch to compute-optimized (C2) machine types for faster job completion.

Answer

Use regional persistent disks for stateful workloads to improve performance.

Answer

Reduce the number of min-nodes in the node pool to zero during idle times and use cluster autoscaler.

Question 11

A team uses Cloud Build for CI/CD. The builds are taking longer than expected due to dependency downloads. What is the best practice to speed up builds?

Accepted Answer

Use Docker layer caching with Cloud Build by specifying a cache image or using Kaniko cache.. Option B is correct because Docker layer caching allows Cloud Build to reuse previously built layers, significantly reducing the time spent re-downloading and re-installing dependencies. By specifying a cache image or using Kaniko's built-in cache, only changed layers are rebuilt, while unchanged dependency layers are pulled from the cache instead of being fetched from the internet each time.

Answer

Increase the machine type to e2-highcpu-32 to speed up compilation.

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Use Artifact Registry to store built packages and pull them during build.

Answer

Store dependencies in Cloud Source Repositories and fetch them during build.

Question 12

A company has an on-premises data center connected to GCP via Dedicated Interconnect. They run latency-sensitive applications on GCE and use Cloud Storage for backups. The backup traffic is causing congestion on the Interconnect link. How should they optimize costs and performance?

Accepted Answer

Route backup traffic through a separate VPN tunnel over the internet to reduce congestion on the Interconnect.. Option D is correct because routing backup traffic over a separate VPN tunnel using the internet offloads non-latency-sensitive backup data from the Dedicated Interconnect link, reducing congestion without incurring additional costs for increased bandwidth. This approach preserves the low-latency path for critical application traffic while using a cost-effective, encrypted internet-based connection for backups, optimizing both performance and cost.

Answer

Increase the Dedicated Interconnect bandwidth to accommodate both traffic types.

Answer

Move backup storage to a different region to reduce data transfer costs.

Answer

Use Cloud Interconnect to connect directly to Cloud Storage for backup traffic.

Question 13

A Cloud Spanner instance is experiencing high latency for point reads. The instance has 5 nodes and the read throughput is moderate. The table has a primary key with monotonically increasing values. What is the most likely cause and optimization?

Accepted Answer

The primary key design causes hotspotting; use a hash prefix or add a leading random value.. The monotonically increasing primary key causes all writes to be directed to the last tablet (splitting point), creating a hotspot on one node. This hotspot leads to high latency for point reads because that node becomes a bottleneck. Adding a hash prefix or a leading random value distributes writes and reads evenly across all nodes, resolving the hotspotting issue.

Answer

Use interleaved tables to reduce the number of index lookups.

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The instance is underprovisioned; add more nodes.

Answer

The instance has too many nodes causing transaction conflicts; reduce nodes.

Question 14

A company commits to using Compute Engine for 3 years and wants the maximum discount. Which purchasing option should they use?

Accepted Answer

3-year committed use discount.. A 3-year committed use discount (CUD) offers the highest discount rate (up to 57% for most machine types) compared to 1-year CUDs (up to 37%) or pay-as-you-go pricing. By committing to a consistent resource usage for the full 3-year term, the company maximizes the discount on Compute Engine costs.

Answer

Pay-as-you-go pricing.

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Sustained use discounts.

Answer

1-year committed use discount.

Question 15

A company uses BigQuery for analytics and has a large number of ad-hoc queries from different teams. Costs are rising unpredictably. They want to control costs while maintaining query performance. What should they do?

Accepted Answer

Purchase flat-rate slots and assign them to a reservation for each team.. Option D is correct because purchasing flat-rate slots and assigning them to a reservation for each team provides predictable, fixed-cost capacity for BigQuery. This eliminates the unpredictability of on-demand pricing while allowing teams to share a dedicated pool of slots, ensuring consistent query performance without unexpected cost spikes.

Answer

Use partitioning and clustering to reduce data scanned.

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Reduce the number of slots available to each team.

Answer

Require each team to include a cost code in their queries.