Google PCA Manage implementation of cloud architecture — 15 Questions

Question 1

Your team has deployed a microservices application on Google Kubernetes Engine (GKE) with multiple services communicating via internal ClusterIP services. You notice that some requests between services are failing intermittently with 'connection refused' errors. The services are defined with readiness probes. What is the most likely cause?

Accepted Answer

The readiness probes are not passing, causing the service endpoints to be removed.. The 'connection refused' error indicates that the client is attempting to connect to a port on which no process is listening. In GKE, when a readiness probe fails, Kubernetes removes the pod's IP from the corresponding ClusterIP service's endpoints. If all pods for a service fail their readiness probes, the service has no healthy endpoints, and any request to the ClusterIP will be refused because there is no backend to accept the connection. This matches the intermittent nature of the issue, as pods may temporarily fail the probe and then recover.

Answer

The services are not exposed via a VPC peering connection to the client's VPC.

Answer

The services are using NodePort instead of LoadBalancer type, causing port conflicts.

Answer

The services are not associated with an Ingress resource.

Question 2

An organization is running a stateful workload on Compute Engine with a single persistent disk. They want to migrate to a regional persistent disk for higher availability. The disk is 500 GB and currently 80% full. They need zero downtime during the migration. What is the recommended approach?

Accepted Answer

Create a snapshot of the disk, then create a new regional persistent disk from that snapshot, and attach it to the instance.. Option B is correct because creating a snapshot of the existing persistent disk and then creating a new regional persistent disk from that snapshot allows you to attach the new disk to the instance with zero downtime. The snapshot captures the disk state at a point in time, and the regional disk is created asynchronously; once available, you can detach the original disk and attach the regional disk without stopping the instance, as Compute Engine supports live disk attachment/detachment.

Answer

Attach a new regional disk to the instance and use RAID 1 mirroring.

Answer

Use rsync to copy data to a new regional disk while the instance is running.

Answer

Use gcloud compute disks resize to change the disk type to regional.

Question 3

A company is planning to deploy a global web application on Google Cloud. They expect low latency for users worldwide and need to serve static content (images, CSS) as well as dynamic API responses. Which architecture should they use?

Accepted Answer

Use Cloud CDN in front of an external HTTPS Load Balancer with backend services in multiple regions.. Cloud CDN in front of an external HTTPS Load Balancer with backend services in multiple regions is correct because it provides global anycast IP termination, low-latency content delivery via Google's edge cache for static content, and dynamic API requests are forwarded to the nearest healthy backend in the closest region. This architecture meets both the low-latency requirement for users worldwide and the need to serve both static and dynamic content efficiently.

Answer

Use Cloud NAT to allow egress traffic from instances and distribute static content via a shared VPC.

Answer

Use Cloud DNS with geo-routing to direct users to the closest regional Cloud Run service.

Answer

Use VPC Network Peering to connect multiple regional VPCs and serve content from a central location.

Question 4

You are designing a CI/CD pipeline for a containerized application on Google Cloud. The application is built with Cloud Build, stored in Container Registry, and deployed to GKE. The team wants to ensure that only images that pass vulnerability scanning are deployed. What should you do?

Accepted Answer

Add a step in Cloud Build that runs a vulnerability scanner on the image and fails the build if vulnerabilities exceed a threshold.. Option A is correct because Cloud Build can include a custom step that runs a vulnerability scanner (e.g., using the Google Cloud `gcloud container images list-tags` with the `--show-occurrences-from` flag or a third-party tool like Trivy) and then evaluates the results against a threshold. If the scan finds vulnerabilities exceeding the defined threshold, the build step exits with a non-zero status, causing the Cloud Build pipeline to fail and preventing the image from being pushed to Container Registry or deployed. This directly enforces the requirement that only images passing vulnerability scanning proceed in the CI/CD pipeline.

Answer

Configure Container Analysis to automatically scan images in Container Registry and block deployment via a webhook.

Answer

Enable Binary Authorization on the GKE cluster and configure a policy to require an attestation from a trusted authority.

Answer

Use Security Command Center to detect vulnerabilities and alert the team to manually block deployments.

Question 5

A company runs a data analytics platform on Google Cloud using BigQuery, Dataflow, and Cloud Storage. They notice that Dataflow jobs are failing with 'out of memory' errors for certain large pipelines. The pipelines process variable amounts of data, sometimes spiking 10x normal. Which strategy should they use to handle these spikes cost-effectively?

Accepted Answer

Configure the Dataflow pipeline to use autoscaling with a higher maximum number of workers and use preemptible VMs for cost savings.. Option C is correct because Dataflow's autoscaling can dynamically add workers to handle sudden data spikes, and using preemptible VMs significantly reduces cost for batch pipelines that can tolerate interruptions. This approach avoids manual intervention and over-provisioning, making it cost-effective for variable workloads.

Answer

Manually monitor the job and increase the number of workers when a spike is detected.

Answer

Increase the machine type of the workers to a high-memory type and disable autoscaling.

Answer

Use Dataflow Streaming Engine to offload state to persistent storage and reduce memory usage.

Question 6

A startup wants to deploy a web application on Google Cloud with a MySQL database. They anticipate low traffic initially but want the ability to scale seamlessly. They also want to minimize operational overhead. Which combination of services should they choose?

Accepted Answer

App Engine Standard Environment with Cloud SQL.. App Engine Standard Environment provides a fully managed, autoscaling platform for web applications, while Cloud SQL offers a managed MySQL database with automatic replication and backups. This combination minimizes operational overhead because Google handles infrastructure provisioning, patching, and scaling, and Cloud SQL integrates natively with App Engine via the Cloud SQL proxy or Unix socket, requiring no manual configuration for connectivity.

Answer

Compute Engine with a self-managed MySQL instance.

Answer

Cloud Run with Cloud Spanner.

Answer

Google Kubernetes Engine (GKE) with Cloud SQL.

Question 7

Your organization has a policy that all Compute Engine instances must have specific labels (env, team, cost-center) applied. You want to enforce this automatically when instances are created. What should you do?

Accepted Answer

Use the Organization Policy service with a custom constraint to require labels on Compute Engine instances.. Option D is correct because Organization Policy Service with a custom constraint allows you to enforce that all Compute Engine instances must have specific labels (env, team, cost-center) at creation time. This is a preventive control that blocks creation of non-compliant instances, unlike reactive or permission-based approaches. Custom constraints use the `compute.googleapis.com/instance` resource type and can require label keys or values using CEL (Common Expression Language) syntax.

Answer

Enable Cloud Audit Logs and set up a metric-based alert to detect instances without labels.

Answer

Create a Cloud Function that listens for instance creation events and adds labels automatically.

Answer

Assign a custom IAM role that includes permission to label instances, and remove the default compute.instances.create permission.

Question 8

Which TWO statements are true about Google Cloud HTTPS Load Balancers?

Accepted Answer

They can forward traffic to backends in multiple regions, including instances in different VPC networks.. Option C is correct because Google Cloud HTTPS Load Balancers are global external load balancers that can distribute traffic to backends across multiple regions, and they support cross-VPC connectivity via Shared VPC or VPC Network Peering, allowing instances in different VPC networks to serve as backends.

Answer

They support only external backends, such as internet-facing instances.

Answer

They support only IPv4 traffic.

Answer

They can be used to load balance internal HTTP(S) traffic within a VPC.

Question 9

Which THREE actions can help reduce costs for a BigQuery workload that runs frequent, ad-hoc analytical queries on a large dataset?

Accepted Answer

Partition the table by a date or timestamp column.. Partitioning the table by a date or timestamp column (Option B) reduces the amount of data scanned by BigQuery for queries that filter on that column, directly lowering query costs (pay-per-byte model). It also improves performance by pruning irrelevant partitions, making it a core cost-saving technique for ad-hoc analytical workloads.

Answer

Enable automatic schema detection to avoid manual schema definition.

Answer

Use flat-rate pricing with reserved slots.

Question 10

An engineer runs the command above. A few days later, the instance becomes unresponsive. Upon investigation, you find that the boot disk is 100 GB and 95% full. The data disk is 500 GB and only 20% full. What is the most likely cause of the unresponsiveness?

Accepted Answer

The boot disk is too small and has run out of space.. The boot disk is 95% full, which leaves insufficient free space for the operating system to write temporary files, logs, or perform essential system operations. When a Linux or Windows boot disk runs out of space, the OS can become unresponsive because critical processes (e.g., systemd, journald, or the Windows Registry) cannot write to disk. In Google Cloud, the boot disk is the root device (typically /dev/sda1), and filling it to 95% on a 100 GB disk means only 5 GB remains, which is easily exhausted by normal system activity.

Answer

The data disk is pd-standard, which is causing I/O bottlenecks for the OS.

Answer

The boot disk is pd-ssd, which is too slow for the workload.

Answer

The instance has run out of IOPS on the boot disk.

Question 11

You are reviewing an IAM policy for a Cloud Storage bucket. Alice is a member of the data-team group. What level of access does Alice have to objects in this bucket?

Accepted Answer

Read and write access (admin).. Option C is correct because the IAM policy grants the data-team group the roles/storage.objectAdmin role, which provides full read, write, and delete access to objects in the bucket. Alice, as a member of the data-team group, inherits this role and therefore has read and write (admin) access to the objects.

Answer

Read-only access.

Answer

No access, because the group policy overrides the individual policy.

Answer

Write-only access.

Question 12

Your company runs a critical application on Google Kubernetes Engine (GKE) in us-central1. The application consists of a frontend deployment with 3 replicas and a backend statefulset with 5 replicas using persistent volumes (SSD). Recently, the team noticed that during a regional outage in us-central1, the application became completely unavailable. They want to design a multi-region architecture that can survive a regional failure with RPO of 1 hour and RTO of 30 minutes. The application is stateless on the frontend but the backend stores critical data on persistent disks. The backend can operate in a read-only mode from a secondary region if needed. They have a limited budget and want to minimize ongoing costs. Which approach should they take?

Accepted Answer

Deploy the frontend and backend in a regional GKE cluster across us-central1, and use a CronJob to take snapshots of persistent volumes every hour and copy them to a secondary region. In disaster, restore the snapshots to a new cluster in the secondary region.. Option D meets the RPO of 1 hour by using a CronJob to take hourly snapshots of PersistentVolume data and copy them to a secondary region. In a disaster, you restore those snapshots to a new GKE cluster in the secondary region, achieving an RTO of 30 minutes by automating the restore process. This approach minimizes ongoing costs because snapshots are incremental and you only pay for storage in the secondary region when needed, while the frontend remains stateless and can be redeployed quickly.

Answer

Migrate the backend to Cloud SQL for MySQL with cross-region replication, and keep the frontend on GKE with multi-region ingress.

Answer

Deploy the frontend and backend in a regional GKE cluster and use regional persistent disks for the statefulset, replicating data synchronously across zones.

Answer

Deploy the frontend and backend in a single zonal cluster in us-central1-a, and use scheduled snapshots of persistent disks to a different region.

Question 13

A company is migrating a monolithic application to Google Kubernetes Engine (GKE). The application currently runs on a single Compute Engine instance and stores session state in local memory. The migration must support horizontal scaling and high availability. What should the company do to manage session state in the new architecture?

Accepted Answer

Refactor the application to store session state in Cloud Memorystore for Redis and make the application stateless.. Option A is correct because migrating to a stateless architecture with Cloud Memorystore for Redis allows the application to scale horizontally without session state being tied to any single pod. By externalizing session state to a managed, highly available Redis service, any pod can handle any request, which is essential for high availability and autoscaling in GKE.

Answer

Use a StatefulSet with a headless service to assign stable network identities to pods.

Answer

Use GKE Ingress with session affinity (sticky sessions) to route requests to the same pod.

Answer

Store session state in Cloud SQL using a replicated database.

Question 14

A company runs a batch processing workload on Compute Engine instances in a managed instance group (MIG). The job is CPU-intensive and takes approximately 4 hours to complete. The company wants to reduce costs without sacrificing performance. Which action should they take?

Accepted Answer

Use preemptible VMs for the MIG and implement a checkpointing mechanism to handle interruptions.. Preemptible VMs are significantly cheaper than standard VMs but can be terminated at any time. For a batch processing workload that is CPU-intensive and runs for 4 hours, using preemptible VMs in a MIG with a checkpointing mechanism allows the job to resume from the last saved state after an interruption, thus reducing costs without sacrificing performance.

Answer

Purchase committed use discounts for the instance type.

Answer

Change the machine series to a smaller machine type.

Answer

Provision additional reserved VMs to ensure capacity.

Question 15

An organization has deployed a multi-region Cloud Spanner instance for a global application. The application is experiencing high latency for read requests from a specific region. The team has verified that the application is using stale reads and the data distribution is even. What is the most likely cause of the high latency?

Accepted Answer

The Spanner instance does not have a read replica in a location close to the clients.. Option D is correct because Cloud Spanner uses a single global configuration with regional read replicas. If the instance does not have a read replica in the region where the clients are located, read requests must traverse the network to a replica in another region, causing higher latency. Even with stale reads, the physical distance to the nearest replica directly impacts read latency.

Answer

The number of read replicas in the region is insufficient to handle the read volume.

Answer

The Spanner instance has too few nodes, causing contention.

Answer

The application is using read-write transactions instead of read-only transactions.