Google ACE Ensuring successful operation of a cloud solution Practice Test 4 — 15 Questions

Question 1

You need to monitor a Cloud Run service for errors and receive a PagerDuty notification when the number of 5xx errors exceeds 10 in any 5-minute window. Which Cloud Monitoring feature should you use?

Accepted Answer

Create a log-based metric on Cloud Run error logs, then create an alerting policy on that metric with a PagerDuty notification channel.. A log-based metric extracts a numeric counter from Cloud Run error logs (e.g., HTTP 5xx status codes). An alerting policy can then evaluate that metric over a sliding 5-minute window, triggering a PagerDuty notification via a configured notification channel when the count exceeds 10. This is the native, serverless approach that requires no additional infrastructure.

Answer

Configure Cloud Run to send error emails directly to the PagerDuty email integration.

Answer

Use Cloud Pub/Sub to stream Cloud Run logs to a custom application that pages PagerDuty.

Answer

Enable Cloud Run's built-in alerting feature in the service configuration.

Question 2

Your Dataflow streaming pipeline is consuming messages from Pub/Sub but the pipeline's throughput has dropped significantly. Cloud Monitoring shows the `pubsub/subscription/oldest_unacked_message_age` metric is growing. The pipeline has enough workers. What is the most likely bottleneck, and how should you address it?

Accepted Answer

Inspect Dataflow job graph metrics to identify the slow stage, then optimize that stage's logic or address data skew.. The growing `oldest_unacked_message_age` metric indicates that messages are not being processed and acknowledged quickly enough, even though the pipeline has enough workers. This points to a bottleneck within a specific stage of the Dataflow pipeline, such as a transformation or grouping operation that is slow or suffering from data skew. Option B is correct because inspecting the job graph metrics (e.g., wall time, backlog, and throughput per stage) allows you to identify the slow stage and then optimize its logic or address data skew, which directly resolves the processing delay.

Answer

Increase the number of Dataflow workers to process messages faster.

Answer

Increase the Pub/Sub subscription's ack deadline to 600 seconds.

Answer

Switch from Dataflow to Pub/Sub Lite for lower cost and higher throughput.

Question 3

A GKE pod's container is frequently crashing and restarting. You need to view the logs from the previous container instance (before the last crash) to diagnose the crash cause. Which command retrieves these logs?

Accepted Answer

`kubectl logs POD_NAME --previous`. Option B is correct because the `--previous` flag in `kubectl logs` retrieves logs from the previous instance of a container in a pod, which is exactly what you need when the current container has crashed and restarted. This allows you to see the logs that led to the crash, even though the container is now running a new instance.

Answer

`kubectl logs POD_NAME`

Answer

`kubectl describe pod POD_NAME`

Answer

`kubectl get events --field-selector reason=OOMKilled`

Question 4

Your organization uses Cloud Storage for storing backups. You want to automatically delete backup objects that are older than 30 days to control costs. You also want objects between 7 and 30 days old to use Nearline storage class for lower cost. Which Cloud Storage feature manages both requirements in a single configuration?

Accepted Answer

Configure Object Lifecycle Management rules on the bucket with `SetStorageClass` and `Delete` actions.. Option B is correct because Object Lifecycle Management rules in Cloud Storage allow you to define conditions (e.g., object age) and actions (e.g., SetStorageClass to Nearline, Delete) in a single configuration. This automates both the transition of objects aged 7–30 days to Nearline storage and the deletion of objects older than 30 days, without custom code or manual intervention.

Answer

Write a Cloud Function that runs daily, lists objects, and deletes or moves old ones.

Answer

Set a bucket-level retention policy of 30 days and manually change storage classes.

Answer

Use Cloud Scheduler to trigger `gsutil` commands that move and delete old objects.

Question 5

You are managing a GKE cluster that runs a mixed workload: latency-sensitive web services and batch data processing jobs. The batch jobs run for hours and consume significant CPU/memory. During batch peaks, the web services experience CPU throttling. What is the best configuration to prevent batch jobs from impacting web service latency?

Accepted Answer

Assign web service pods a higher PriorityClass and run batch jobs on a separate node pool with taints.. Option B is correct because it uses PriorityClass to ensure web service pods are scheduled and maintained over batch pods during resource contention, while placing batch jobs on a separate node pool with taints isolates their resource consumption. This prevents batch jobs from causing CPU throttling on latency-sensitive web services by guaranteeing that web pods have priority access to CPU cycles and that batch workloads do not share nodes with web pods.

Answer

Set CPU requests and limits on batch job pods to be lower than web service pods.

Answer

Use Horizontal Pod Autoscaler for batch jobs so they scale down during peak web traffic.

Answer

Enable Cluster Autoscaler so new nodes are added when batch jobs demand more resources.

Question 6

You notice that your Cloud SQL for PostgreSQL instance's `pg_stat_activity` shows many connections in `idle in transaction` state, and the connection count is near the max_connections limit. Application threads are blocking waiting for connections. What is the most effective solution to manage database connections for a GKE-hosted application?

Accepted Answer

Deploy PgBouncer as a sidecar or deployment to pool connections to Cloud SQL in transaction mode.. PgBouncer is a lightweight connection pooler that can be deployed as a sidecar or separate deployment in GKE to manage connections to Cloud SQL for PostgreSQL. By operating in transaction mode, it holds database connections only for the duration of a transaction, not for the entire client session, which drastically reduces the number of concurrent connections to the database. This directly addresses the `idle in transaction` connections and the near-max_connections issue without requiring application code changes.

Answer

Increase `max_connections` in the Cloud SQL PostgreSQL instance flags.

Answer

Switch from Cloud SQL to Cloud Spanner, which has no connection limits.

Answer

Restart the Cloud SQL instance to clear idle connections.

Question 7

Your application is deployed on GKE and experiencing increased latency. You suspect a memory leak causing the JVM to run frequent garbage collection cycles. Cloud Monitoring shows high memory usage but you need to understand the garbage collection behavior over time. Which GCP tool provides JVM-level profiling including memory allocation data?

Accepted Answer

Cloud Profiler with heap profiling enabled for the JVM application.. Cloud Profiler with heap profiling enabled captures JVM-level memory allocation data and garbage collection behavior over time, allowing you to identify memory leaks and GC frequency. Unlike generic memory monitoring, it provides per-method allocation snapshots and GC pause analysis specific to the JVM.

Answer

Cloud Trace

Answer

Cloud Monitoring with JVM MBeans metrics exported via the Ops Agent.

Answer

Error Reporting filtered for OutOfMemoryError exceptions.

Question 8

A Compute Engine VM's boot disk is nearly full and the application is failing. You want to snapshot the disk first (for safety), then resize it online. What is the correct sequence of gcloud commands?

Accepted Answer

Snapshot the disk, resize the disk with `gcloud compute disks resize`, then grow the filesystem within the VM.. Option B is correct because you must snapshot the disk first to ensure data safety before making changes, then resize the disk using `gcloud compute disks resize` (which works on a running VM with live resize enabled), and finally grow the filesystem inside the VM to utilize the additional space. This sequence avoids downtime and preserves a recovery point.

Answer

Stop the VM, resize the disk, take a snapshot, restart the VM.

Answer

Resize the disk with `gcloud compute instances set-disk-auto-delete` to automatically expand the disk.

Answer

Create a new larger disk, attach it as a secondary disk, and move data using rsync.

Question 9

Your Cloud SQL for MySQL primary instance in `us-central1` has failed. Cloud SQL HA automatically fails over to the standby. After the failover, your application is experiencing intermittent connection errors. What is the most likely cause and solution?

Accepted Answer

Application connection pools hold stale connections to the failed primary; configure pools to validate connections and reconnect after failure.. Option B is correct because after a Cloud SQL HA failover, the standby instance becomes the new primary with the same IP address, but existing application connections that were established to the old primary are now broken. Connection pools that do not validate connections before reuse will attempt to use these stale connections, causing intermittent errors. Configuring the pool to test connections (e.g., via `SELECT 1` or JDBC `connectionTestQuery`) and automatically reconnect resolves this by discarding dead connections and establishing fresh ones to the new primary.

Answer

The standby instance has a different IP address; update the connection string.

Answer

The standby replica must be manually promoted before it can accept connections.

Answer

The MySQL binary log is incomplete after failover; run `mysqlcheck` to repair tables.

Question 10

You need to transfer 50 TB of data from an AWS S3 bucket to Cloud Storage. The data must be transferred within 48 hours, and the network bandwidth between AWS and GCP is limited to 1 Gbps. Which GCP service manages this transfer efficiently?

Accepted Answer

Use Storage Transfer Service to set up an S3-to-GCS transfer job.. Storage Transfer Service is the correct choice because it is a managed service designed specifically for moving large datasets from external cloud providers (like AWS S3) to Google Cloud Storage. It handles the transfer asynchronously, can parallelize connections to maximize throughput, and is ideal for the 50 TB / 48-hour constraint given a 1 Gbps link (theoretical max ~5.4 TB/day, but with parallelism and retries, STS can approach line rate). It eliminates the need for an intermediate VM or manual scripting.

Answer

Use `gsutil -m cp` from a Compute Engine VM in the same region as the destination bucket.

Answer

Download from S3 and re-upload to GCS using a local machine with high bandwidth.

Answer

Use BigQuery Data Transfer Service to move S3 data to GCS.

Question 11

Your GKE cluster nodes are running an older kernel version with a known vulnerability. You need to update all nodes to use the latest node image with the patched kernel without any downtime. The cluster has a Surge Upgrade configuration of `max-surge: 1, max-unavailable: 0`. What happens during the node upgrade?

Accepted Answer

GKE provisions one new node, drains one old node, deletes it, and repeats — zero downtime.. Option B is correct because the surge upgrade configuration `max-surge: 1, max-unavailable: 0` ensures that GKE first provisions one new node (the surge node) before draining and deleting an old node. This rolling update process maintains the desired capacity at all times, resulting in zero downtime for applications.

Answer

GKE terminates all nodes simultaneously and creates new ones — brief downtime occurs.

Answer

GKE upgrades nodes in-place by applying a kernel patch without rescheduling pods.

Answer

Two nodes are upgraded simultaneously (one being the surge node and one old node going offline).

Question 12

You need to verify that a Compute Engine VM in `us-central1` can reach an on-premises server at IP `10.1.2.3` over a Cloud VPN connection. The VPN tunnel appears UP but you're unsure if routing is correct. Which GCP tool can test this connectivity?

Accepted Answer

Use Network Intelligence Center Connectivity Tests to analyze the path from the VM to the on-premises IP.. B is correct because Network Intelligence Center Connectivity Tests can analyze the path from a specific source (the Compute Engine VM) to a destination (the on-premises server IP 10.1.2.3) across hybrid connectivity like Cloud VPN. It validates routing, firewall rules, and tunnel health without requiring you to SSH into the VM or run live traffic, making it ideal for diagnosing routing issues when the VPN tunnel is UP but connectivity is uncertain.

Answer

SSH into the VM and run `ping 10.1.2.3` to test connectivity.

Answer

Review Cloud VPN tunnel metrics in Cloud Monitoring for packet loss.

Answer

Run `gcloud compute routes list` to verify the route to 10.1.2.3 exists.

Question 13

A managed instance group (MIG) is configured with autohealing using a health check. During a rolling update, several VMs become unhealthy before the new application version starts responding to health checks. The MIG deletes and recreates these VMs repeatedly, causing a deployment loop. How should you fix this?

Accepted Answer

Increase the `initialDelaySec` in the autohealing policy to give VMs time to start before health checks are evaluated.. Option B is correct because increasing `initialDelaySec` in the autohealing policy gives the new application version sufficient time to start and become healthy before the health check begins evaluating the VM. This prevents the MIG from prematurely marking VMs as unhealthy during the rolling update, breaking the deployment loop where VMs are repeatedly deleted and recreated.

Answer

Disable autohealing during rolling updates by removing the health check.

Answer

Switch from rolling update to canary update to reduce the number of affected VMs.

Answer

Reduce the health check interval and timeout to detect unhealthy VMs faster.

Question 14

Your application writes structured JSON logs to stdout from a Cloud Run service. You want to query logs in Cloud Logging to find all requests where the `user_id` field equals `12345`. Which log query syntax finds these entries?

Accepted Answer

`jsonPayload.user_id="12345"`. Option B is correct because Cloud Logging uses the `jsonPayload` field to access structured JSON fields in log entries. When your application writes structured JSON logs to stdout, Cloud Run automatically parses them and stores the fields under `jsonPayload`. The query `jsonPayload.user_id="12345"` directly matches the `user_id` field within that JSON payload.

Answer

`textPayload:"user_id:12345"`

Answer

`resource.labels.user_id="12345"`

Answer

`labels.user_id="12345"`

Question 15

You need to create a dashboard in Cloud Monitoring that shows: (1) Cloud Run request count per second, (2) Cloud Run p99 latency, (3) GKE pod CPU utilization, and (4) Cloud SQL query duration — all on a single screen. Which Cloud Monitoring feature enables this multi-service overview?

Accepted Answer

Create a Cloud Monitoring custom dashboard with chart widgets for each metric across the different services.. Option B is correct because Cloud Monitoring custom dashboards allow you to combine chart widgets from multiple monitored services (Cloud Run, GKE, Cloud SQL) into a single screen. This feature supports heterogeneous metric queries using the Monitoring Query Language (MQL) or metric selectors, enabling a unified view without needing separate tools or exports.

Answer

Create four separate alerting policies and pin them to a shared alerting page.

Answer

Use BigQuery to query the metrics export and build a Looker Studio dashboard.

Answer

Use Cloud Logging to create a log-based dashboard with all four metrics.