PCDE Practice Test 43 — 15 Questions

Question 1

An SRE team is conducting a blameless postmortem after an outage. Which THREE elements should be included in the postmortem document? (Choose 3 answers)

Accepted Answer

Contributing factors (e.g., why the failure happened).. Option A (Contributing factors) is correct because a blameless postmortem focuses on the systemic and environmental conditions that enabled the failure, such as configuration drift, missing safeguards, or ambiguous alerts, rather than blaming an individual. Option D (Action items with owners and due dates) is correct because postmortems must produce concrete, trackable remediation work; assigning a named owner and a due date ensures follow-through and prevents recurrence. Option E (Timeline of events) is correct because an accurate chronological record of detection, escalation, mitigation, and recovery provides the factual basis for analyzing contributing factors and validating action items. Option B (Identification of the person responsible) is not appropriate because blameless postmortems deliberately avoid individual blame to encourage honest reporting. Option C (Single root cause) is not appropriate because complex distributed systems typically fail due to multiple interacting contributing factors, and insisting on one root cause oversimplifies the incident and can hide systemic weaknesses.

Answer

Identification of the person responsible.

Answer

Single root cause.

Question 2

A financial company uses Cloud SQL for PostgreSQL to store transaction data. They need to create a materialized view that aggregates daily sales for a BI dashboard. The underlying transaction table is updated continuously. Which approach ensures the materialized view remains up to date without manual intervention?

Accepted Answer

Schedule a Cloud Function via Cloud Scheduler to run REFRESH MATERIALIZED VIEW periodically. Cloud SQL for PostgreSQL does not support automatic materialized view refresh. The only way to keep a materialized view up to date without manual intervention is to schedule a periodic refresh using Cloud Scheduler to invoke a Cloud Function that executes the REFRESH MATERIALIZED VIEW command. This approach balances freshness with resource cost, as refreshing on every transaction would be too expensive.

Answer

Use BigQuery federated query to directly query the Cloud SQL table

Answer

Use a Cloud SQL read replica and create the materialized view on the replica

Answer

Add a trigger on the base table to refresh the materialized view on each update

Question 3

Which TWO statements are true about designing a star schema for BI reporting?

Accepted Answer

Dimension tables are denormalized to reduce the number of joins. Dimension tables in a star schema are intentionally denormalized to reduce the number of joins required for BI queries. This denormalization improves query performance by allowing fact tables to join directly to dimension tables without traversing multiple normalized tables, which is a key design principle for OLAP reporting.

Answer

Fact tables store descriptive attributes like product names

Answer

Fact tables use natural keys to enforce referential integrity

Answer

Dimension tables are normalized to minimize redundancy

Question 4

A company wants to migrate a 100 GB MySQL database to Cloud SQL with minimal application changes. Which migration tool should they use?

Accepted Answer

Database Migration Service. Database Migration Service (DMS) is the correct tool because it is designed specifically for migrating databases to Cloud SQL with minimal downtime and minimal application changes. DMS uses a combination of initial snapshot and continuous change data capture (CDC) to replicate the source MySQL database to Cloud SQL, allowing the application to point to the new database with only a connection string update.

Answer

mysqldump

Answer

BigQuery Data Transfer Service

Answer

Storage Transfer Service

Question 5

Arrange the steps to import data from Cloud Storage into Cloud Firestore using a managed import.

Accepted Answer

First, run the gcloud firestore import command specifying the Cloud Storage URI. Second, monitor the import operation using gcloud firestore operations describe. Third, verify the imported data in Cloud Firestore.. Import needs properly formatted files; use gcloud command, then monitor and verify.

Answer

First, monitor the import operation using gcloud firestore operations describe. Second, run the gcloud firestore import command. Third, verify the imported data in Cloud Firestore.

Answer

First, verify the imported data in Cloud Firestore. Second, run the gcloud firestore import command. Third, monitor the import operation.

Answer

First, run the gcloud firestore import command. Second, verify the imported data in Cloud Firestore. Third, monitor the import operation.

Question 6

Which THREE methods are effective for improving query performance in BigQuery for BI workloads?

Accepted Answer

Clustering on frequently filtered columns. Clustering on frequently filtered columns physically co-locates related data within blocks, significantly reducing the amount of data scanned for queries with filter predicates. This is especially effective for BI workloads that often filter on high-cardinality columns like customer ID or transaction type, as it avoids full table scans and improves query performance without additional storage costs.

Answer

Replacing joins with subqueries

Answer

Using SELECT * in queries

Question 7

A company uses Cloud Spanner and needs to capture real-time changes from a table for downstream processing. They want to avoid writing custom application code to track changes. Which THREE components should they use? (Choose three.)

Accepted Answer

Pub/Sub. Change Streams (C) is the native Cloud Spanner feature that captures inserts, updates, and deletes on a table in real time without requiring custom application code, which directly satisfies the requirement to avoid writing change-tracking logic. Pub/Sub (B) is the messaging service used to receive and fan out those change records to downstream consumers reliably and asynchronously. Dataflow (E) is the managed pipeline service that reads the Change Streams output and processes/transforms it for downstream systems, completing the serverless change-data-capture flow. Cloud Bigtable (A) is a wide-column NoSQL datastore, not a change-capture or messaging component, so it does not fit this architecture. The Cloud Spanner API (D) is the low-level interface for reading and writing data, and using it to track changes would require exactly the custom application code the company wants to avoid.

Answer

Cloud Bigtable

Answer

Cloud Spanner API

Question 8

Which Google Cloud database service is designed for hybrid transactional and analytical processing (HTAP) with a built-in columnar engine?

Accepted Answer

AlloyDB for PostgreSQL. AlloyDB for PostgreSQL is Google Cloud's fully managed PostgreSQL-compatible database designed for HTAP workloads. It includes a built-in columnar engine that accelerates analytical queries by up to 100x without requiring a separate analytical database, while still supporting transactional workloads. This makes it the correct choice for hybrid transactional and analytical processing.

Answer

BigQuery

Answer

Cloud SQL

Answer

Cloud Spanner

Question 9

A small e-commerce company runs a MySQL database on Cloud SQL. They need to add a read replica to offload reporting queries from the primary instance. The reporting queries are read-only and can tolerate slight replication lag. Which Cloud SQL feature should they use?

Accepted Answer

Create a read replica in the same region.. Read replicas in Cloud SQL are designed to offload read-only workloads from the primary instance. They replicate asynchronously, so they can tolerate replication lag, which is acceptable for reporting queries. This is the simplest and most cost-effective solution for the given scenario.

Answer

Enable high availability (HA) configuration.

Answer

Migrate to Cloud Spanner for read scaling.

Answer

Use Cloud SQL federated queries to query an external replica.

Question 10

An organization uses Terraform to manage infrastructure across multiple projects. They want to use a single shared Terraform state file for their production environment but isolate state for development environments. The team uses Terraform Cloud workspaces. Which state management approach is most appropriate?

Accepted Answer

Create separate Terraform Cloud workspaces for production and development environments.. Terraform Cloud workspaces each maintain their own independent state file, so creating separate workspaces for production and development naturally isolates state while allowing production to use a single shared state within its own workspace. This is the idiomatic Terraform Cloud pattern for environment separation.

Answer

Use Terraform Enterprise instead of Terraform Cloud because it supports state isolation.

Answer

Use a single GCS bucket as the backend and store all states in the same prefix.

Answer

Use a single Terraform workspace for all environments, with separate state files via the -state flag.

Question 11

A company uses Bigtable for time-series data with a row key format: 'deviceID#timestamp'. They notice write hotspotting on a few devices that generate high volumes of data. How should they redesign the row key to distribute writes evenly?

Accepted Answer

Add a random salt prefix to the row key: 'random_number#deviceID#timestamp'. Bigtable row keys are sorted lexicographically, so a row key starting with 'deviceID' causes all writes for a hot device to land on the same tablet, creating a hotspot. Adding a random salt prefix (e.g., a random number) distributes those writes across multiple tablets, spreading the load. This is the canonical Bigtable recommendation for write-heavy time-series workloads with hot keys.

Answer

Reverse the timestamp: 'deviceID#reverse_timestamp'

Answer

Use a monotonically increasing integer for the row key.

Answer

Store all data in a single column family and use column qualifiers for timestamps.

Question 12

A healthcare company stores patient records in Cloud SQL for PostgreSQL. The database schema includes a `patients` table with a `patient_id` primary key and a `visits` table that references `patients` via a foreign key. The application frequently runs a query that retrieves a patient's details along with all their visits. The team notices that these queries are slow and wants to optimize the schema. What should they do?

Accepted Answer

Add an index on the `patient_id` column in the `visits` table.. The most effective and standard optimization is to add an index on the foreign key column `patient_id` in the `visits` table. This allows PostgreSQL to efficiently retrieve all visits for a given patient, significantly speeding up the join query. Other options either introduce data integrity risks, add write overhead, or do not directly address the join performance issue.

Answer

Partition the `visits` table by `patient_id` to improve query performance.

Answer

Create a materialized view that joins `patients` and `visits` and refresh it on every write.

Answer

Denormalize the schema by storing patient details directly in the `visits` table.

Question 13

An organization is moving to a GitOps model for managing both application deployments and GCP infrastructure. They want to use a single tool to sync Kubernetes manifests and manage GCP resources like Cloud SQL and Pub/Sub. Which two Google Cloud services should they combine?

Accepted Answer

Config Sync. Config Sync (D) is correct because it continuously reconciles the state of Kubernetes resources in a cluster with manifests stored in a Git repository, enabling a GitOps workflow for application deployments. Config Connector (E) is correct because it allows managing GCP resources (e.g., Cloud SQL, Pub/Sub) declaratively using Kubernetes custom resource definitions (CRDs), which can also be synced via Config Sync. Together, they provide a single Git-based toolchain for both Kubernetes and GCP infrastructure.

Answer

Deployment Manager

Answer

Cloud Build

Answer

Cloud Deploy

Question 14

A company wants to use Cloud SQL for MySQL to serve a read-heavy application. They need to ensure high availability and offload read traffic. Which TWO steps should they take? (Choose two.)

Accepted Answer

Create a same-region read replica. Option E is correct because enabling high availability (HA) on the primary Cloud SQL for MySQL instance provisions a standby replica in a different zone within the same region, providing automatic failover and meeting the high-availability requirement. Option C is correct because a same-region read replica serves read traffic from a separate instance, offloading the primary and improving read scalability while keeping latency low. Option A is incorrect because daily on-demand backups provide data protection and point-in-time recovery, not high availability or read offloading. Option B is incorrect because a cross-region read replica is primarily for disaster recovery and read scaling across regions, and it is not the standard way to achieve HA for the primary instance. Option D is incorrect because auto-storage increase only handles disk growth automatically and does not address availability or read traffic.

Answer

Schedule on-demand backups daily

Answer

Create a cross-region read replica

Answer

Enable auto-storage increase

Question 15

A gaming company uses Cloud Spanner to store player profiles and game state. The database has a table 'Players' with a monotonically increasing integer primary key. During a global launch event, write latency spikes and throughput drops. The issue is traced to hotspotting. Which schema change should the team implement to mitigate this?

Accepted Answer

Add a hash prefix to the primary key by salting the player ID.. Adding a hash prefix to the monotonically increasing integer primary key distributes writes across multiple Cloud Spanner splits, preventing hotspotting. Without this, sequential player IDs cause all new inserts to target the same split, leading to write contention and throughput drops during high-volume events like a global launch.

Answer

Change primary key to use a combination of timestamp and player ID.

Answer

Convert the primary key to a UUID stored as bytes.

Answer

Create a parent-child interleaved table structure.