PCD Practice Test 18 — 15 Questions

Question 1

A mobile app developer wants a serverless NoSQL database that automatically syncs data offline and provides security rules for access control. Which Google Cloud database should they choose?

Accepted Answer

Firestore. Firestore is the correct choice: it is serverless, document-based, provides offline sync for mobile apps, and has Security Rules for access control.

Answer

Cloud Bigtable

Answer

Cloud Spanner

Answer

Memorystore for Redis

Question 2

A company is deploying a microservices-based application on Google Kubernetes Engine (GKE). The application consists of several stateless services that experience unpredictable traffic spikes. The team wants to ensure high availability and scalability while minimizing costs. Which design should they implement?

Accepted Answer

Deploy a Regional GKE cluster with cluster autoscaling and Horizontal Pod Autoscaler for each deployment.. A Regional GKE cluster provides multi-zone high availability, cluster autoscaling dynamically adjusts node pool size to handle unpredictable traffic spikes, and Horizontal Pod Autoscaler (HPA) scales individual pod replicas based on CPU/memory or custom metrics. This combination ensures both scalability and cost efficiency by only provisioning resources when needed.

Answer

Deploy a Regional GKE cluster with node auto-provisioning and a fixed number of replicas per service.

Answer

Use a Regional GKE cluster with preemptible VMs and static pod counts.

Answer

Use a single-zone GKE cluster with a large fixed node pool to handle peak load.

Question 3

You need to migrate a large on-premises PostgreSQL database to AlloyDB with minimal downtime. The database is 2 TB. Which migration strategy should you use?

Accepted Answer

Use Database Migration Service to migrate with continuous replication. Database Migration Service (DMS) supports continuous replication from on-premises PostgreSQL to AlloyDB, allowing the source to remain live while data is copied and changes are streamed. This minimizes downtime because the cutover is a brief final sync rather than a full offline export/import. For a 2 TB database, this is the only strategy that meets the minimal-downtime requirement.

Answer

Use BigQuery Data Transfer Service

Answer

Export the database as SQL files and import into AlloyDB using pg_restore

Answer

Use gsutil to copy data files and restore

Question 4

You are designing a monitoring strategy for a microservices architecture running on GKE. Each service emits custom business metrics (e.g., order processing time). You want to create a dashboard that shows the 99th percentile latency for each service over the last 7 days. Which approach should you take?

Accepted Answer

Write custom metrics to Cloud Monitoring and create a dashboard with the 99th percentile aligner.. Cloud Monitoring supports custom metrics and provides built-in aligners, including a 99th percentile aligner, which can be applied directly in a dashboard chart. This allows you to compute the 99th percentile latency for each service over the last 7 days without manual calculation or exporting logs. Custom metrics are the appropriate mechanism for business metrics like order processing time, as they are designed for numeric time-series data.

Answer

Export logs to Cloud Logging and use Log Analytics to compute percentiles.

Answer

Use Metrics Explorer to view the metrics and manually compute percentiles.

Answer

Use Prometheus monitoring built into GKE and query the avg() function.

Question 5

A DevOps team wants to set up custom metrics for a serverless application running on Cloud Run. The application emits metrics using OpenTelemetry. They need to collect these metrics and create an alerting policy that triggers when the 99th percentile latency exceeds 500ms for 5 minutes. Which TWO actions must they take? (Choose two.)

Accepted Answer

Create a custom distribution metric for the latency data and set up a metric threshold alert using the 99th percentile value.. To alert on the 99th percentile of latency, you must create a custom distribution metric, which stores a histogram of values and allows percentile calculations. A metric-threshold alert policy can then be configured to evaluate the 99th percentile value against the 500ms threshold over a 5-minute window.

Answer

Install the Cloud Monitoring agent on the Cloud Run instance to collect custom metrics.

Answer

Define a log-based metric from the application logs that captures latency entries.

Answer

Configure the Cloud Monitoring dashboard to query the metrics using PromQL.

Question 6

A developer deployed the above Cloud Run service YAML. The service deploys successfully but any request fails with a 503 error. What is the most likely cause?

Accepted Answer

The container is not listening on the expected port.. A 503 error from Cloud Run indicates that the service is failing to respond to health checks or requests. The most common cause is that the container is not listening on the port specified in the `containerPort` field of the YAML (default 8080). Cloud Run sends requests to that port, and if the application is bound to a different port (e.g., 3000 or 80), the request never reaches the application, resulting in a 503.

Answer

The service has no ingress setting.

Answer

The container image has a different entrypoint.

Answer

containerConcurrency is set too high.

Question 7

Which Google Cloud service would you use to cache session data for a web application to reduce database load? The cache must support pub/sub messaging and have sub-millisecond latency.

Accepted Answer

Memorystore for Redis. Memorystore for Redis is the correct choice because it is a fully managed in-memory data store that supports sub-millisecond latency and includes native Pub/Sub messaging capabilities. Redis's Pub/Sub allows real-time messaging between application components, which is ideal for session caching and reducing database load. The other options either lack sub-millisecond latency or do not support Pub/Sub natively.

Answer

Memorystore for Memcached

Answer

Bigtable

Answer

Firestore

Question 8

An e-commerce platform uses Cloud SQL for PostgreSQL for its inventory database. To meet a higher availability requirement, they decide to enable the HA configuration. What is the expected recovery point objective (RPO) with Cloud SQL HA?

Accepted Answer

0 (zero). Cloud SQL for PostgreSQL HA uses synchronous replication to a standby instance in a different zone within the same region. This ensures that every write transaction is committed on both the primary and standby before acknowledging the client, resulting in zero data loss upon failover. Therefore, the RPO is 0 (zero).

Answer

Depends on the replication lag

Answer

Up to 5 minutes

Answer

Up to 1 minute

Question 9

During a rolling update, the new pods are failing to start because they require more memory than available on nodes. What is the most likely cause?

Accepted Answer

The resource requests and limits are misconfigured.. The most likely cause of pods failing to start due to insufficient memory is misconfigured resource requests and limits. If the memory request (spec.containers[].resources.requests.memory) is set too high, the scheduler cannot find a node with enough allocatable memory, leaving pods in a Pending state. Similarly, if the limit is set too low, the pod may be OOMKilled after starting, but the question specifically states 'failing to start,' pointing to a scheduling failure due to requests exceeding node capacity.

Answer

The maxSurge value is too low.

Answer

The replicas count is too high.

Answer

The strategy type is wrong.

Question 10

A company is designing a global e-commerce platform on Google Cloud. The application requires low-latency access for users worldwide and must be highly available. Which load balancing solution should they use?

Accepted Answer

External HTTP(S) Load Balancer. The External HTTP(S) Load Balancer is the correct choice because it is a global, proxy-based Layer 7 load balancer that terminates HTTP/HTTPS traffic at Google's edge points of presence (PoPs) and routes requests to the nearest healthy backend. This provides low-latency access for users worldwide by leveraging Google's global network and anycast IPs, while also offering built-in high availability, SSL offloading, and content-based routing.

Answer

External TCP/UDP Network Load Balancer

Answer

Cloud CDN

Answer

Internal TCP/UDP Load Balancer

Question 11

A company has a multi-region deployment on GKE and needs to route traffic to the closest regional cluster based on user location. They want to minimize latency. Which approach should they use?

Accepted Answer

Use a global external HTTP(S) Load Balancer with backend services pointing to NEGs in each region.. A global external HTTP(S) Load Balancer uses Anycast IP addresses and is backed by backend services that reference Network Endpoint Groups (NEGs) in each regional GKE cluster. This allows the load balancer to direct traffic to the closest healthy backend based on the user's geographic location and the load balancer's proximity algorithm, minimizing latency without requiring DNS-based routing.

Answer

Create separate internal load balancers in each region and use Cloud DNS geo-routing.

Answer

Configure an external TCP/UDP Network Load Balancer in each region and use Cloud DNS geo-routing.

Answer

Deploy a single regional cluster and use Cloud CDN to cache content globally.

Question 12

A company wants to send events from a custom application to Cloud Pub/Sub, then process them with a Cloud Run service. The application runs on Compute Engine. What is the simplest way for the application to authenticate to Pub/Sub?

Accepted Answer

Attach a service account to the Compute Engine instance with necessary Pub/Sub roles.. The simplest and most secure way for an application on Compute Engine to authenticate to Pub/Sub is to attach a service account to the instance. This leverages the metadata server to automatically provide credentials to the application without embedding any secrets. The service account can be granted the necessary Pub/Sub roles (e.g., Pub/Sub Publisher) to allow publishing events. This approach eliminates key management overhead and follows Google Cloud best practices for authentication.

Answer

Use an API key for the Pub/Sub API.

Answer

Embed a service account JSON key in the application code.

Answer

Set up Cloud Endpoints to proxy the Pub/Sub requests.

Question 13

A team is using Cloud Monitoring to set up an alerting policy for a Compute Engine instance that runs a web server. The team wants to be notified if the instance's CPU utilization exceeds 80% for 5 minutes. Which threshold type should they use?

Accepted Answer

Metric threshold. A metric threshold alerting policy directly monitors a numeric metric (e.g., CPU utilization) and triggers when the value exceeds a defined threshold (80%) for a specified duration (5 minutes). This is the standard approach for simple threshold-based alerts on a single metric in Cloud Monitoring.

Answer

Ratio threshold

Answer

MQL (Monitoring Query Language)

Answer

Forecast threshold

Question 14

A company is migrating a monolithic application to microservices on Google Cloud. They have strict requirements for service-to-service communication: requests must be authenticated, authorized, and encrypted in transit. They also need to enforce fine-grained access control based on the requesting service identity. Which Google Cloud service should they use to achieve these goals?

Accepted Answer

Cloud Service Mesh (Anthos Service Mesh). Cloud Service Mesh (Anthos Service Mesh) provides mutual TLS for encryption in transit, service identity-based authentication and authorization, and fine-grained access control policies between services. It is purpose-built for service-to-service security in microservices architectures on Google Cloud. The other options address ingress, edge protection, or API key management, not workload identity-based service mesh security.

Answer

Cloud Run with ingress control

Answer

Cloud Armor with IAM

Answer

Cloud Endpoints with API keys

Question 15

An application deployed on Google Kubernetes Engine (GKE) is experiencing intermittent high latency. The operations team wants to quickly identify which specific code path is causing the delay. What should they use?

Accepted Answer

Enable Cloud Trace and analyze trace spans.. Cloud Trace is designed specifically for latency analysis in distributed systems like GKE. It captures end-to-end request latency and breaks it down into individual spans, each representing a specific code path or service call. By analyzing these spans, the operations team can pinpoint which exact code path (e.g., a database query, external API call, or internal function) is causing the intermittent high latency.

Answer

Use Cloud Profiler to identify memory leaks.

Answer

Set up a Cloud Monitoring uptime check.

Answer

Review Cloud Logging logs to find error messages.