Google ACE Planning and configuring a cloud solution Practice Test 3 — 15 Questions

Question 1

A team deploys an application with sensitive internal APIs on GKE. The APIs should be reachable from other GKE services in the cluster and from on-premises systems via VPN, but not from the public internet. Which load balancer configuration meets this?

Accepted Answer

Internal Application Load Balancer with a VPC-private IP. An Internal Application Load Balancer (HTTP/HTTPS) with a VPC-private IP is correct because it exposes the APIs only within the VPC network, making them reachable from other GKE services in the cluster and from on-premises systems via VPN (which extends the VPC), while blocking all public internet traffic by design. This load balancer operates at Layer 7 and uses an internal IP address that is not routable from the internet, satisfying the requirement without relying on additional access controls.

Answer

Global external Application Load Balancer with Cloud Armor blocking non-VPN IPs

Answer

A ClusterIP Service with an external IP range allowlist

Answer

NodePort Service with VPC firewall rules restricting access to VPN IP ranges

Question 2

A startup processes uploaded videos — each video upload triggers transcoding that takes 5–30 minutes. Users should get an immediate response after upload, not wait for transcoding. The transcoding system must handle burst uploads. Which architecture fits?

Accepted Answer

Publish a transcoding job to Cloud Pub/Sub after upload; respond immediately; workers consume and process jobs asynchronously. Option B is correct because it decouples the upload from the transcoding process using Cloud Pub/Sub, allowing the API to respond immediately to the user while workers asynchronously process the transcoding jobs. This pattern handles burst uploads by buffering messages in Pub/Sub and scaling workers independently, ensuring no upload is lost even under high load.

Answer

Upload the video and synchronously wait for transcoding to complete before responding

Answer

Use Cloud Spanner to store video metadata and transcode synchronously in a Cloud SQL stored procedure

Answer

Deploy the transcoding directly in the API server and scale the API server horizontally for bursts

Question 3

A Cloud Run service calls external third-party APIs that have rate limits. Under burst traffic, the service spawns many concurrent instances, each making direct API calls, causing rate limit errors. What GCP pattern reduces API call volume without adding infrastructure?

Accepted Answer

Cache third-party API responses in Cloud Memorystore (Redis) with appropriate TTL. Caching third-party API responses in Cloud Memorystore (Redis) with an appropriate TTL reduces the number of outbound API calls by serving cached data to multiple concurrent Cloud Run instances. This directly addresses rate-limit errors without adding new infrastructure, as Memorystore is a managed in-memory cache that integrates seamlessly with Cloud Run via a VPC connector.

Answer

Set Cloud Run max-concurrency to 1 so each instance handles one request

Answer

Enable Cloud CDN on the Cloud Run service to cache outbound requests

Answer

Migrate to Cloud Functions with a lower default concurrency limit

Question 4

A team is designing a data pipeline: Cloud Storage → Pub/Sub → Dataflow → BigQuery. They expect 50 GB of data per hour. Dataflow jobs must automatically scale workers based on pipeline backlog. Which Dataflow feature provides automatic horizontal scaling of worker VMs?

Accepted Answer

Dataflow Horizontal Autoscaling — automatically adds/removes workers based on pipeline lag. Dataflow Horizontal Autoscaling is the correct feature because it automatically adds or removes worker VMs based on the pipeline's backlog (lag), which directly matches the requirement for automatic horizontal scaling. This feature uses the Cloud Monitoring service to track the number of unprocessed elements and adjusts worker count accordingly, ensuring efficient resource usage without manual intervention.

Answer

Vertical scaling — Dataflow automatically increases worker machine types under load

Answer

GKE cluster autoscaler — Dataflow runs on GKE and inherits its autoscaling

Answer

Cloud Monitoring alerting policy that triggers worker additions via gcloud

Question 5

A financial application requires all database transactions to be durable even if the primary Cloud SQL instance fails mid-transaction. The RPO (Recovery Point Objective) must be near-zero. Which Cloud SQL feature achieves this?

Accepted Answer

Cloud SQL High Availability with synchronous standby replica in a different zone. Cloud SQL High Availability (HA) uses a synchronous standby replica in a different zone to ensure that every write is committed to both the primary and standby before acknowledging the transaction. This provides near-zero RPO because if the primary fails mid-transaction, the standby has the exact same data and can take over without data loss.

Answer

Cloud SQL read replica with synchronous replication

Answer

Cloud SQL with automated daily backups and point-in-time recovery

Answer

Cloud Spanner — it automatically replicates synchronously across zones

Question 6

A media company needs to serve large video files (average 2 GB) to global users with low latency. The files are stored in Cloud Storage. What combination of services delivers the best streaming performance?

Accepted Answer

Cloud Storage + Cloud CDN via a Global Load Balancer backend bucket. Cloud Storage combined with Cloud CDN via a Global Loader Balancer backend bucket is the best choice because it provides edge-caching of large video files, reducing latency for global users. The Global Load Balancer terminates HTTP(S) traffic at the closest point of presence, and Cloud CDN caches content from the multi-region bucket, minimizing origin load and improving streaming performance.

Answer

Cloud Storage in a multi-region bucket with direct public access

Answer

Upload video files to a Compute Engine VM with nginx serving them directly

Answer

Cloud Filestore with NFS-mounted streaming

Question 7

An e-commerce platform sees a 20x traffic spike every Black Friday. The rest of the year traffic is low and stable. The team wants to minimize costs during normal periods while handling the annual peak without manual intervention. Which architecture achieves this?

Accepted Answer

Managed instance group with autoscaling + scheduled scaling pre-warming before Black Friday. Option B is correct because it combines managed instance group autoscaling for normal low-cost operation with scheduled scaling to pre-warm capacity before the Black Friday spike, ensuring seamless handling of the 20x traffic surge without manual intervention. This approach uses the 'autoscaler' and 'scheduled scaling' features in Google Cloud to dynamically adjust resources based on load, while pre-warming prevents cold-start latency during the peak.

Answer

Pre-provision 20x capacity year-round to guarantee Black Friday performance

Answer

Deploy on Cloud SQL — it scales compute automatically for traffic spikes

Answer

Add 20 manual VMs on Black Friday and delete them afterward each year

Question 8

A team runs Apache Kafka on self-managed VMs for event streaming but wants to reduce operational overhead. Which GCP-native service is the managed alternative to Kafka for pub/sub messaging at scale?

Accepted Answer

Cloud Pub/Sub — Google's managed pub/sub messaging service. Cloud Pub/Sub is the correct answer because it is Google Cloud's fully managed, scalable pub/sub messaging service that provides at-least-once delivery and supports both push and pull subscriptions, making it the direct managed alternative to self-managed Apache Kafka. It eliminates the operational overhead of managing Kafka clusters on VMs while offering similar event streaming capabilities with automatic scaling and global availability.

Answer

Cloud Bigtable — a managed wide-column store for streaming data

Answer

Cloud Dataflow — the GCP managed streaming processing service

Answer

Cloud Storage — use GCS notification events as a message queue

Question 9

A gaming company's GKE cluster uses a mix of node pools: a standard on-demand pool for stateful database pods, and a Spot VM pool for compute-intensive but fault-tolerant game simulation pods. The simulation pods occasionally get preempted. How should the Deployment be configured to route simulation pods to the Spot pool only?

Accepted Answer

Add a nodeSelector: cloud.google.com/gke-spot: 'true' to the simulation Deployment spec. Option B is correct because GKE uses the node label `cloud.google.com/gke-spot` to identify Spot VMs. Adding a `nodeSelector` with that exact key-value pair ensures the simulation Deployment is scheduled exclusively on Spot nodes, which is the intended behavior for fault-tolerant, preemptible workloads.

Answer

Set podAffinity to prefer nodes where Spot pods are running

Answer

Set requests.cpu and requests.memory to very high values — GKE will route them to Spot nodes

Answer

Name the simulation Deployment with a 'spot-' prefix — GKE routes prefixed deployments to Spot pools

Question 10

A team needs to run a simple containerized script that processes a batch of files once per night and exits when done — no HTTP endpoint needed. Which GCP service is most appropriate?

Accepted Answer

Cloud Run Jobs triggered by Cloud Scheduler. Cloud Run Jobs is the correct choice because it is designed for batch workloads that run to completion, with no requirement for an HTTP endpoint. It can handle long-running tasks (up to 24 hours) and can be triggered by Cloud Scheduler for nightly execution, making it ideal for processing files once per night.

Answer

Cloud Run Services with a timeout set to 24 hours

Answer

Cloud Functions with a 540-second maximum timeout

Answer

App Engine Standard with a background service

Question 11

You are designing a solution for a retail application that needs to store customer shopping cart data. The cart data is accessed frequently during active sessions and must survive for at least 30 days even without activity. Each cart entry is small (< 1 KB) and identified by a user ID. The solution must support microsecond read latency and be horizontally scalable. Which GCP storage service best meets these requirements?

Accepted Answer

Cloud Bigtable. Cloud Bigtable is correct because it is a fully managed, scalable NoSQL database designed for large analytical and operational workloads, offering consistent sub-10ms latency and horizontal scaling. For small (<1 KB) entries accessed with microsecond read latency, Bigtable's key-value model and high throughput make it ideal, and its data persists indefinitely (beyond 30 days) with no automatic expiration. It supports high-frequency access patterns typical of active shopping cart sessions.

Answer

Cloud Firestore in Datastore mode

Answer

Cloud SQL (PostgreSQL)

Answer

Cloud Memorystore (Redis)

Question 12

A financial services company needs to run analytics queries on transaction data that arrives in real-time. The queries must return results within 2 seconds and the dataset grows by ~100 GB per day. The company also needs to retain all data for 7 years for regulatory compliance. Which architecture best satisfies these requirements?

Accepted Answer

Stream transactions through Pub/Sub → Dataflow → BigQuery; run analytics on BigQuery.. Option B is correct because it uses Pub/Sub for real-time ingestion, Dataflow for stream processing, and BigQuery for analytics, which can handle 100 GB/day growth and return queries within 2 seconds using BigQuery's columnar storage and automatic sharding. BigQuery's 7-year retention is supported by its time-based partitioning and long-term storage at reduced cost, meeting regulatory compliance without manual intervention.

Answer

Write transactions to Cloud Spanner; run analytics queries directly against Spanner.

Answer

Store transactions in Cloud Bigtable and use Dataproc/Spark for analytics queries.

Answer

Use Cloud SQL for storage and Cloud Dataprep for analytics transformations.

Question 13

Your team is planning a GKE cluster for a microservices application. Some services process sensitive payment data and must run on dedicated nodes that no other workloads can access. The rest of the application can share nodes. How should you configure the cluster?

Accepted Answer

Apply taints to the dedicated node pool and tolerations to payment service pod specs.. Option B is correct because taints on dedicated node pools prevent pods without matching tolerations from being scheduled on those nodes, ensuring that only payment service pods (which include the corresponding tolerations) can run on the dedicated nodes. This isolates sensitive workloads at the node level without requiring separate clusters, which would add operational overhead and complexity.

Answer

Use separate GKE clusters: one for payment services and one for everything else.

Answer

Use Kubernetes NetworkPolicy to restrict network access between payment pods and other pods.

Answer

Set resource requests and limits so payment services consume all resources on their nodes.

Question 14

You need to design a solution where a Cloud Function is triggered by HTTP requests from the internet, but it must also privately access a Cloud SQL instance that has no public IP. The Cloud Function should not expose the Cloud SQL instance to public traffic. Which configuration enables this?

Accepted Answer

Configure a Serverless VPC Access connector and attach it to the Cloud Function to access Cloud SQL via private IP.. Option B is correct because a Serverless VPC Access connector allows a Cloud Function to connect to a Cloud SQL instance via its private IP, enabling private network communication without exposing the database to the internet. The connector bridges the serverless environment to a VPC, and the Cloud SQL instance must have private IP enabled. This satisfies the requirement of private access while the function itself remains publicly triggerable via HTTP.

Answer

Enable a public IP on the Cloud SQL instance and restrict access using Cloud SQL authorized networks.

Answer

Use Cloud SQL Auth Proxy on a Compute Engine VM as a jump host between the function and the database.

Answer

Deploy the Cloud Function in the same project as Cloud SQL; same-project resources can access each other privately by default.

Question 15

You are designing an application that needs to process exactly once each message published to a topic, even if the consumer fails partway through and restarts. Which GCP service provides built-in exactly-once processing semantics with Pub/Sub?

Accepted Answer

Dataflow with Pub/Sub as the source using the Beam SDK.. Dataflow with Pub/Sub as the source using the Beam SDK provides built-in exactly-once processing semantics because it leverages the Beam engine's checkpointing and the Pub/Sub source's snapshot-based deduplication. Dataflow tracks each message's unique ID and ensures that even if a worker fails and restarts, the message is not reprocessed, guaranteeing exactly-once delivery within the pipeline.

Answer

Cloud Functions subscribed to the Pub/Sub topic with idempotent logic.

Answer

BigQuery Subscriptions connected directly to the Pub/Sub topic.

Answer

Cloud Run with a Pub/Sub push subscription and database deduplication table.