PCD Practice Test 33 — 15 Questions

Question 1

A company runs a microservices architecture on Cloud Run. They want to measure the error budget for a critical service using a custom SLI based on the ratio of successful requests (HTTP 200-499) to total requests. They have set an SLO of 99.9% over a 30-day window. Which Cloud Monitoring feature should they use to track this?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Service Level Objectives (SLOs) with a custom SLI metric.. Cloud Monitoring's Service Level Objectives (SLOs) feature natively supports custom SLI metrics, allowing you to define a ratio of successful requests (HTTP 200-499) to total requests as a custom SLI. This directly enables tracking the error budget against the 99.9% SLO over a 30-day window, without needing to build external dashboards or rely on latency or uptime checks.

Answer

Cloud Trace spans to calculate latency-based SLIs.

Answer

Uptime checks with a custom status code classifier.

Answer

Log-based metrics to count requests and errors, then create a custom dashboard.

Question 2

Which service provides serverless change data capture (CDC) from MySQL and PostgreSQL to BigQuery or Cloud Storage without writing code?

Accepted Answer

Datastream. Datastream is a serverless CDC service that can stream changes to BigQuery, Cloud Storage, or Pub/Sub.

Answer

BigQuery Data Transfer Service

Answer

Cloud Functions

Answer

Dataflow

Question 3

A team wants to monitor a web application's uptime from multiple locations. Which THREE Google Cloud monitoring features should they use?

Accepted Answer

Uptime checks. Uptime checks are the correct service for monitoring web application availability from multiple locations. They allow you to configure HTTP, HTTPS, or TCP checks from Google Cloud's global vantage points, verifying that the application responds correctly and within specified timeouts. This directly addresses the requirement to monitor uptime from multiple geographic locations.

Answer

Log-based metrics

Answer

Error Reporting

Question 4

An organization has multiple Google Cloud projects for different environments (dev, staging, prod). They want to create a single Cloud Monitoring dashboard that shows metrics from all projects. What is the correct approach?

Accepted Answer

Create a dashboard in a shared project and use metric scopes to include data from other projects. Metric scopes in Cloud Monitoring allow you to view metrics from multiple Google Cloud projects within a single dashboard. By creating a dashboard in a shared (host) project and adding other projects as monitored projects via metric scopes, you can aggregate metrics from dev, staging, and prod environments without duplicating dashboards or exporting data.

Answer

Use a custom metrics export to a central project via log sinks

Answer

Create a separate dashboard in each project and use dashboard sharing

Answer

Use the Monitoring API to aggregate metrics in a single chart

Question 5

An organization has a Cloud SQL for MySQL instance with 500 GB of data. They want to offload reporting queries that scan large portions of the database without impacting the primary instance's performance. Which solution should they implement?

Accepted Answer

Create a cross-region Cloud SQL read replica and direct reporting queries to it. Creating a cross-region read replica distributes read traffic and isolates reporting workloads from the primary. Cloud SQL read replicas are asynchronous and can be promoted if needed. For read-only queries, this is the correct approach.

Answer

Use Cloud SQL connection pooling to share connections

Answer

Upgrade the primary instance to a high-memory machine type

Answer

Enable automatic storage increase on the primary instance

Question 6

A company uses Memorystore for Redis as a session store. They observe that sessions are evicted before their TTL expires, causing users to be logged out prematurely. Which action should they take?

Accepted Answer

Increase the memory size of the instance. Memorystore evicts keys when memory is full. Increasing memory size allows more keys to be stored without eviction. Changing eviction policy to 'allkeys-lru' might help but could still evict sessions. Increasing memory is the direct solution.

Answer

Enable persistence (RDB/AOF)

Answer

Change the eviction policy to volatile-ttl

Answer

Increase the maxmemory-policy to allkeys-lru

Question 7

A startup has deployed a Python web application on Compute Engine. They have installed the Cloud Monitoring agent and can see basic system metrics like CPU and disk usage. However, they want to track custom application metrics, such as number of active users and request latency, to monitor performance. They have added OpenCensus code to export metrics but notice that custom metrics are not appearing in Cloud Monitoring. The application runs under a custom service account with the 'Monitoring Metric Writer' role assigned. What is the most likely cause?

Accepted Answer

The OpenCensus exporter is not configured to send to the Cloud Monitoring endpoint.. OpenCensus requires explicit configuration to export metrics to a specific backend. Even though the service account has the 'Monitoring Metric Writer' role, the OpenCensus exporter must be configured with the correct Cloud Monitoring endpoint (e.g., 'monitoring.googleapis.com') and project ID. Without this configuration, the metrics are collected by OpenCensus but never sent to Cloud Monitoring.

Answer

The Cloud Monitoring agent needs to be restarted after adding OpenCensus.

Answer

The service account has not been granted the 'Monitoring Viewer' role.

Answer

The application is not exporting metrics to the correct Cloud Monitoring project.

Question 8

A company is using Database Migration Service to continuously migrate data from an on-premises PostgreSQL database to Cloud SQL for PostgreSQL. The source database is behind a firewall. Which two steps are required to establish connectivity? (Choose two.)

Accepted Answer

Install Cloud SQL Auth Proxy on the source database server. Cloud SQL Auth Proxy provides a secure way to connect to Cloud SQL from on-premises without requiring a public IP or firewall rules for the Cloud SQL instance. It uses a TLS tunnel to the Cloud SQL instance, which is ideal when the source database is behind a firewall and you need to establish outbound connectivity from the on-premises environment to Cloud SQL. This avoids exposing the Cloud SQL instance to the public internet. Option D is correct because VPC peering allows the customer's VPC to communicate with the Cloud SQL VPC privately, enabling Database Migration Service to access the Cloud SQL instance without traversing the public internet. This is a common configuration when using private IP for Cloud SQL.

Answer

Open firewall ports for DMS public IPs

Answer

Use Cloud Interconnect

Answer

Configure a Cloud VPN tunnel to the source database

Question 9

A DevOps team is migrating an on-premises monitoring solution to Google Cloud. They need to collect custom application metrics from a batch processing job running on Compute Engine. Which two services can ingest custom metrics into Cloud Monitoring? (Choose two.)

Accepted Answer

Cloud Logging with log-based metrics. Cloud Logging can ingest any log entry, and log-based metrics allow you to extract numeric values from log content to create custom metrics that appear in Cloud Monitoring. Option E is correct because the Cloud Monitoring API lets you define custom metric descriptors and then write time-series data directly to those metrics, bypassing any agent or log pipeline.

Answer

Cloud Profiler API

Answer

Stackdriver Monitoring agent with custom plugin

Answer

Cloud Trace API

Question 10

A company runs a stateful application on Compute Engine. They need to achieve an RPO of less than 15 minutes and an RTO of less than 30 minutes for a regional disaster. Which three steps should they include in their disaster recovery plan? (Select exactly 3.)

Accepted Answer

Develop custom scripts to replicate application data asynchronously to another region. Asynchronous replication of application data to another region can achieve an RPO of less than 15 minutes and an RTO of less than 30 minutes, as it allows the application to fail over to a secondary region with minimal data loss. Custom scripts can control replication frequency and ensure data consistency, meeting the strict RPO requirement.

Answer

Use a managed instance group in multiple zones within the same region

Answer

Use regional persistent disks to replicate data within the region

Question 11

A team plans to migrate an Oracle database to Cloud SQL for PostgreSQL. They have identified complex PL/SQL packages that need conversion. Which open-source tool is specifically designed to assist with schema conversion from Oracle to PostgreSQL?

Accepted Answer

Ora2Pg. Ora2Pg is an open-source tool specifically designed to automate the migration of Oracle databases to PostgreSQL. It converts Oracle PL/SQL code, including complex packages, procedures, and functions, into PostgreSQL-compatible PL/pgSQL, and also handles schema objects like tables, views, sequences, and indexes. This makes it the correct choice for the team's need to convert complex PL/SQL packages.

Answer

Database Migration Service

Answer

pgloader

Answer

Liquibase

Question 12

A team is investigating increased latency in a web application deployed on Google Kubernetes Engine (GKE). They want to identify which specific service calls are slow. Which Google Cloud tool should they use?

Accepted Answer

Cloud Trace. Cloud Trace is the correct tool because it provides end-to-end latency tracking for requests in distributed systems, including GKE. It captures detailed spans for each service call, allowing the team to pinpoint which specific microservice or API call is causing the increased latency. This aligns directly with the need to identify slow service calls in a web application.

Answer

Cloud Monitoring dashboards

Answer

Cloud Profiler

Answer

Cloud Logging

Question 13

A company has a Cloud Run service that uses Cloud SQL. They notice that the number of database connections is increasing over time, causing connection pool exhaustion. They have enabled Cloud Monitoring and see a custom metric for active DB connections. To proactively alert when the connection count exceeds 80% of the maximum pool size (which is 100), which alerting approach is most efficient?

Accepted Answer

Create a ratio alert using an MQL query that divides the active connections by the max connections and alerts when > 0.8.. It creates a ratio alert using MQL to divide the active connections by the maximum pool size (100), triggering when the ratio exceeds 0.8 (80%). This directly measures the utilization of the connection pool, which is the most efficient way to alert on impending exhaustion. It avoids hardcoding a static threshold that would break if the pool size changes, and it uses the custom metric already being monitored.

Answer

Create a metric threshold alert on the custom metric with condition > 80.

Answer

Create a forecast alert to predict when connections will exceed 80.

Answer

Create an alert on the Cloud SQL system metric for 'cloudsql.googleapis.com/database/connections/num_failed_reserved'.

Question 14

A startup wants to use Firestore for a mobile app. They need to restrict access so that users can only read and write their own data. Which Firestore security rule feature should they use?

Accepted Answer

Use request.auth to get the user's UID and compare it to the document's owner field.. Firestore security rules use `request.auth` to identify the authenticated user and `resource.data` to access document fields. Combining these allows rules to compare the user ID in the request with the document’s owner field. `get()` and `exists()` are functions for cross-document validation, not for user identity.

Answer

Use Firebase Authentication and enable anonymous sign-in.

Answer

Set up IAM roles for each user.

Answer

Use the get() function to retrieve the user's document each time.

Question 15

A development team uses Cloud Build for CI/CD with a monorepo containing multiple microservices. They want to implement a strategy where only the services affected by a commit are built and deployed. Which approach best achieves this?

Accepted Answer

Use multiple Cloud Build triggers, one per service, each with a path filter for its directory. Cloud Build triggers support path filters that allow you to specify which directories or files should initiate a build. By creating one trigger per microservice directory, only the service whose code has changed will be built and deployed, which is the most efficient and native approach for a monorepo with multiple services.

Answer

Use a single Cloud Build trigger with a condition to check changed files

Answer

Use Cloud Functions to detect changes and trigger builds

Answer

Use a single Cloud Build trigger with a bash script to detect changes