Google PCA Ensure solution and operations reliability Practice Test 2 — 15 Questions

Question 1

A company deploys a critical application on Google Kubernetes Engine (GKE) and wants to ensure high availability during cluster upgrades. Which TWO practices should they follow?

Accepted Answer

Use multiple node pools across different zones within the cluster.. Deploying multiple node pools across different zones ensures that if one zone fails or is taken down for maintenance, the application can continue serving from the other zones. This aligns with GKE's best practice for high availability by distributing workloads across failure domains. Option C is correct because PodDisruptionBudgets (PDBs) define the minimum number of pods that must remain available during voluntary disruptions like cluster upgrades, preventing the upgrade from taking down too many replicas at once.

Answer

Use a single-zone node pool with multiple replicas.

Answer

Enable cluster autoscaling to add nodes during upgrades.

Answer

Enable regional clusters for multi-zone control plane.

Question 2

A company runs a multi-tier application on Google Cloud: a frontend on App Engine Standard, a backend on Cloud Run, and a Cloud SQL database. The application experiences intermittent 500 errors when users submit forms. The errors correlate with high CPU usage on the Cloud SQL instance (db-n1-standard-2, 7.5 GB memory). The Cloud Run service has a concurrency setting of 80 and a maximum of 10 instances. The App Engine service uses automatic scaling. The team has verified that the application code is not the issue. They suspect the database is hitting connection limits. Current max_connections on Cloud SQL is 250. The Cloud Run service uses a connection pool of 10 connections per instance. The App Engine service uses a connection pool of 5 connections per instance. They also have a few batch jobs that run occasionally, using up to 10 connections. The team wants to resolve the errors with minimal cost and complexity. Which course of action should they take?

Accepted Answer

Increase the max_connections parameter on Cloud SQL to 500.. The intermittent 500 errors are caused by the Cloud SQL instance hitting its max_connections limit of 250. With Cloud Run using 10 connections per instance and up to 10 instances (100 connections), App Engine using 5 connections per instance (unknown instance count but likely significant), and batch jobs using up to 10 connections, the total can easily exceed 250. Increasing max_connections to 500 directly addresses the connection limit without changing instance size or scaling behavior, which is the simplest and most cost-effective fix.

Answer

Increase the maximum number of Cloud Run instances to 20 to handle more requests.

Answer

Upgrade the Cloud SQL instance to db-n1-standard-4 (15 GB memory) to handle more connections.

Answer

Reduce the concurrency setting on Cloud Run from 80 to 40.

Question 3

A company runs a web application on Google Kubernetes Engine (GKE) with Cluster Autoscaler enabled. During a traffic spike, the application becomes slow and some requests timeout. The cluster has sufficient CPU and memory headroom. What is the most likely cause and solution?

Accepted Answer

Configure Horizontal Pod Autoscaler (HPA) based on CPU utilization or custom metrics.. The cluster has sufficient CPU and memory headroom, indicating that the issue is not about cluster capacity but about pod-level scaling. The Horizontal Pod Autoscaler (HPA) automatically scales the number of pod replicas based on observed CPU utilization or custom metrics, which directly addresses the application slowdown and timeouts during traffic spikes by distributing the load across more pods.

Answer

Increase the node pool's machine type to a larger size.

Answer

Enable Cluster Autoscaler to add more nodes.

Answer

Deploy the application in a regional cluster for higher availability.

Question 4

An organization is migrating a legacy monolithic application to Google Cloud. The application currently runs on a single server with an on-premises database. The application is stateful and requires low-latency access to the database. The migration must minimize downtime and ensure high availability. Which architecture should the company adopt?

Accepted Answer

Deploy on Compute Engine with a regional persistent disk and use Cloud SQL for PostgreSQL with regional high availability.. It combines Compute Engine with a regional persistent disk for synchronous replication across zones, ensuring high availability with minimal downtime during a zonal failure. Cloud SQL for PostgreSQL with regional high availability provides a managed, low-latency database with automatic failover, meeting the stateful application's need for low-latency access and high availability without the complexity of container orchestration.

Answer

Deploy on GKE with StatefulSets and use Cloud Spanner for global consistency.

Answer

Deploy on App Engine Standard Environment and use Cloud Firestore in Datastore mode.

Answer

Deploy on Cloud Run and use Cloud SQL with read replicas.

Question 5

A company uses Cloud SQL for MySQL to host its production database. The database experiences high read traffic. The team wants to improve read performance without modifying the application. What should they do?

Accepted Answer

Add read replicas and configure the application to use them for read queries.. Adding read replicas offloads read queries from the primary Cloud SQL instance, distributing the read load across multiple replicas. This improves read performance without any application code changes, as the application can be configured to direct read queries to the replica endpoints. Cloud SQL for MySQL replicas use asynchronous replication, ensuring near-real-time data consistency for read-heavy workloads.

Answer

Increase the number of CPUs on the primary Cloud SQL instance.

Answer

Use Cloud SQL Proxy with connection pooling.

Answer

Enable automatic storage increase to allow more data.

Question 6

A company is running a critical application on Compute Engine. The application writes logs to a local persistent disk. The operations team wants to ensure logs are not lost if the VM fails. What should they do?

Accepted Answer

Configure the application to write logs to Cloud Logging using the Logging agent.. Cloud Logging with the Logging agent provides a centralized, durable, and managed log storage solution. The agent streams logs from the VM to Cloud Logging in near real-time, ensuring logs are preserved even if the VM or its local persistent disk fails. This decouples log storage from the VM's lifecycle, meeting the operations team's requirement for log durability.

Answer

Use a regional persistent disk to replicate data across zones.

Answer

Schedule persistent disk snapshots every 5 minutes.

Answer

Create a script to copy logs to a Cloud Storage bucket every minute.

Question 7

Which TWO options are best practices for ensuring high availability of an application running on Google Kubernetes Engine (GKE)?

Accepted Answer

Use pod anti-affinity to spread pods across multiple zones.. Pod anti-affinity ensures that pods from the same application are scheduled on different nodes across multiple zones, reducing the blast radius of a zonal failure. This is a key pattern for achieving high availability in GKE, as it prevents a single zone outage from taking down all replicas of your application.

Answer

Deploy all nodes in the same zone to simplify networking.

Answer

Prefer using preemptible VMs for cost savings.

Answer

Use a single zonal cluster to avoid cross-zone latency.

Question 8

Which THREE options are valid strategies for disaster recovery (DR) in Google Cloud?

Accepted Answer

Deploy a mirrored environment in another region and use Traffic Director to fail over.. Traffic Director, based on the xDS API (Envoy), can manage traffic routing across regions. By deploying a mirrored environment in another region and configuring Traffic Director with failover policies, you can redirect traffic to the secondary region if the primary fails, enabling a robust active-passive or active-active DR strategy.

Answer

Store hourly snapshots of Compute Engine disks in the same region.

Answer

Enable Cloud CDN to cache static content from multiple origins.

Question 9

A company runs a batch processing workload on Compute Engine that processes financial transactions. The workload runs daily and must complete within a 4-hour window. The application reads input data from Cloud Storage, processes it, and writes output to another Cloud Storage bucket. The current implementation uses a single VM with a 500 GB persistent disk. Recently, the data volume has increased, and the job is now taking over 6 hours, exceeding the SLA. The team is tasked with redesigning the solution to be faster and more reliable. They want to minimize costs and operational overhead. The data is critical and must not be lost. Which approach should they take?

Accepted Answer

Use Cloud Dataflow with autoscaling to process the data in parallel.. Cloud Dataflow with autoscaling is the correct choice because it provides a fully managed, serverless service for parallel data processing that can automatically scale resources based on the volume of data. This directly addresses the need to complete the batch workload within the 4-hour SLA, as Dataflow can distribute the processing across many workers, significantly reducing execution time. It also ensures reliability and data durability through checkpointing and exactly-once processing semantics, meeting the critical data loss prevention requirement.

Answer

Use a managed instance group with a startup script that processes data, and use Cloud Pub/Sub to coordinate.

Answer

Increase the VM to a high-CPU machine type with a regional persistent disk for HA.

Answer

Deploy the processing logic in Cloud Functions and trigger from Cloud Storage events.

Question 10

A company has deployed a critical application on Google Kubernetes Engine (GKE) with a Regional cluster (us-central1). The application uses a Cloud SQL for PostgreSQL database with a cross-region replica for disaster recovery. The SRE team needs to ensure that the application can survive a regional outage with minimal data loss. Which TWO actions should the team take to improve the reliability of the solution?

Accepted Answer

Configure the application to automatically promote the Cloud SQL cross-region replica to a primary instance when the primary region is unavailable.. To survive a regional outage with minimal data loss, two key actions are needed: (1) Automate promotion of the Cloud SQL cross-region replica to primary when the primary region fails (Option A) – this is the standard Cloud SQL DR procedure; automation via Cloud Functions/Cloud Run reduces RTO. Note that cross-region replication is asynchronous, so some data loss (replication lag) is possible. (2) Deploy a multi-region GKE cluster pair (primary and secondary) and use an external HTTP(S) load balancer with a backend service pointing to both clusters, combined with a DNS failover policy (Option C) – this allows the load balancer to detect primary region health and route traffic to the secondary region if needed. Options B is wrong because cross-region replication cannot be synchronous. Option D is wrong because a secondary cluster in the same region does not help during a regional outage. Option E is wrong because a TCP/UDP load balancer with latency-based routing does not provide failover based on region health.

Answer

Configure Cloud SQL cross-region replication to be synchronous to ensure zero data loss during failover.

Answer

Deploy a secondary GKE cluster in the same region as the primary to provide a hot standby that can take over immediately.

Answer

Use a TCP/UDP load balancer to route traffic to both regions based on latency.

Question 11

You are investigating a Vertex AI Workbench instance (instance-2) that is showing UNHEALTHY status. Based on the exhibit, what is the most likely cause of the issue?

Accepted Answer

The container image gcr.io/my-project/my-image:latest does not exist, or the service account used by the Workbench instance does not have storage.objectViewer access to the container registry.. The UNHEALTHY status in Vertex AI Workbench typically occurs when the instance fails to start its container. Option A is correct because the most likely cause is that the specified container image (gcr.io/my-project/my-image:latest) does not exist in Container Registry, or the service account attached to the instance lacks the storage.objectViewer role on the registry bucket. Without this permission, the instance cannot pull the image, leading to a container creation failure and an UNHEALTHY state. Options B, C, and D are less likely given the focus on the container image in the exhibit.

Answer

The container registry endpoint is blocked by a firewall rule that does not allow egress to gcr.io.

Answer

The instance's underlying Compute Engine resources are exhausted, causing the container creation to timeout.

Answer

The Workbench instance is using an outdated custom image that is not compatible with the latest runtime version.

Question 12

Your company runs an e-commerce platform on Google Cloud. The application is deployed on Compute Engine instances in a managed instance group (MIG) with autoscaling based on CPU utilization. The database uses Cloud SQL for MySQL with a single instance. During a recent flash sale, traffic spiked and the application became slow, resulting in a poor user experience. After analyzing the incident, you discovered that the MIG scaled up but the Cloud SQL instance reached its maximum connections limit, causing some requests to fail. You need to recommend a solution to improve the reliability of the application for future traffic spikes. What should you do?

Accepted Answer

Deploy the Cloud SQL Proxy on each Compute Engine instance to manage database connections more efficiently, and configure a connection pool size that matches the maximum connections of the Cloud SQL instance.. Deploying the Cloud SQL Proxy on each Compute Engine instance provides a secure, efficient way to manage database connections. The proxy can be configured with a connection pool size that matches the Cloud SQL instance's maximum connections, preventing the application from exhausting the database's connection limit. This approach also reduces the overhead of establishing new connections and improves connection reuse, directly addressing the bottleneck during traffic spikes.

Answer

Increase the maximum connections setting on the Cloud SQL instance and also increase the instance's tier to handle more concurrent connections.

Answer

Migrate the database to Cloud Spanner to provide unlimited scalability and automatic sharding.

Answer

Implement a connection pooling library in the application code to reuse database connections and reduce the number of new connections.

Question 13

Which TWO actions should you take to improve the reliability of a stateful application deployed on Compute Engine with regional persistent disks?

Accepted Answer

Use a regional persistent disk to replicate data across two zones.. Regional persistent disks (RPDs) synchronously replicate data between two zones within a region, ensuring that if one zone fails, the data remains available in the other zone without data loss. This directly improves the reliability of a stateful application by providing a durable, zone-failure-tolerant storage layer that maintains data consistency across zones.

Answer

Use preemptible VMs to reduce costs.

Answer

Place an HTTP(S) load balancer in front of the application.

Answer

Schedule regular snapshots of the persistent disk to Cloud Storage.

Question 14

You are running a Kubernetes cluster in GKE with the default node pool configuration shown in the exhibit. Your application requires high disk I/O performance. You notice that the application is experiencing high latency for disk operations. What is the most likely cause?

Accepted Answer

The default node pool uses pd-standard disks, which have low IOPS.. The default node pool in GKE uses pd-standard (standard persistent disk) which provides lower IOPS compared to pd-ssd. For applications requiring high disk I/O performance, pd-standard disks become a bottleneck, causing high latency. Upgrading to pd-ssd or using local SSDs would resolve this issue.

Answer

Node auto-repair is causing disk contention.

Answer

The OAuth scopes restrict disk access, causing high latency.

Answer

The machine type n1-standard-2 does not have enough CPU.

Question 15

Your company runs a critical application on Google Kubernetes Engine (GKE) with 5 nodes. The application experiences intermittent high latency every Friday afternoon. The team has ruled out infrastructure issues and suspects the application logic. You need to instrument the application to identify the root cause. Which approach should you take?

Accepted Answer

Use Cloud Monitoring to create custom metrics for application performance and investigate recent code changes.. The team has already ruled out infrastructure issues and suspects application logic. Creating custom metrics in Cloud Monitoring allows you to instrument the application with key performance indicators (e.g., request latency, error rates) and correlate them with recent code changes to pinpoint the root cause of intermittent high latency. This approach directly addresses the need to monitor application-level behavior rather than infrastructure metrics.

Answer

Increase the number of nodes in the GKE cluster to handle the load.

Answer

Enable Cloud Logging and analyze logs for error messages during the latency periods.

Answer

Configure GKE usage metering to track resource consumption by namespace.