PCDE Practice Exam 66 — 20 Questions

Question 1

Your team uses Cloud Bigtable for a time-series data analytics platform. You observe that the write throughput has dropped significantly, and Cloud Monitoring shows that most of the CPU usage is concentrated on a few nodes. The remaining nodes have low CPU usage. The data model uses sequential timestamps as row keys, and the application writes data for many different sensors. Each sensor ID is part of the row key. What is the most effective action to resolve this hot spotting?

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

Accepted Answer

Prepend a hash of the sensor ID to the row key to distribute writes evenly.. Hot spotting occurs because sequential timestamps as row keys cause writes to be concentrated on a few nodes. By prepending a hash of the sensor ID to the row key, writes for different sensors are distributed across the entire cluster, eliminating hot spots. Option A (reducing batch size) does not fix the key design issue. Option B (increasing nodes) might help temporarily but the uneven distribution remains. Option C (using a different cluster) is unnecessary and does not address the root cause.

Answer

Reduce the batch size of writes to decrease the load on each node.

Answer

Use a different Bigtable cluster and migrate data.

Answer

Increase the number of nodes in the cluster to provide more CPU capacity.

Question 2

A company uses Cloud SQL for PostgreSQL for its BI database. Queries involving joins on large tables are slow. Which TWO strategies should they implement to improve join performance? (Choose TWO.)

Accepted Answer

Denormalize tables to reduce the number of joins. Denormalizing tables reduces the number of joins required in queries by combining related data into fewer tables. This directly minimizes the computational overhead of join operations in Cloud SQL for PostgreSQL, which is especially beneficial for large BI datasets where join performance is critical.

Answer

Increase the number of CPU cores on the instance

Answer

Create read replicas for the join queries

Answer

Use connection pooling to reduce connection overhead

Question 3

A company uses Cloud Run and wants to deploy a new revision that initially receives 5% of traffic, and only if it's healthy, gradually increase to 100%. Which gcloud command should they use?

Accepted Answer

gcloud run deploy --image ... --traffic=5. The `gcloud run deploy` command with the `--traffic` flag allows you to deploy a new revision and immediately set the percentage of traffic it should receive. By specifying `--traffic=5`, the new revision gets 5% of traffic, while the previous revision keeps the remaining 95%. This initiates a canary deployment. The gradual increase to 100% must be managed separately using `gcloud run services update-traffic` commands or an automated pipeline, but the initial command is correct for starting the canary.

Answer

gcloud run deploy --image ... --canary-percent=5

Answer

gcloud run deploy --image ... --to-revisions=REVISION_1=95,REVISION_2=5

Answer

gcloud run deploy --image ... --min-instances=1 --max-instances=10

Question 4

A retail company uses Cloud Spanner to store product inventory data. The table structure is:

CREATE TABLE Inventory (
  ProductId INT64 NOT NULL,
  WarehouseId INT64 NOT NULL,
  StockLevel INT64 NOT NULL,
  LastUpdated TIMESTAMP NOT NULL OPTIONS (allow_commit_timestamp=true)
) PRIMARY KEY (ProductId, WarehouseId);

The application frequently runs the query: SELECT ProductId, SUM(StockLevel) AS TotalStock FROM Inventory WHERE WarehouseId = 123 GROUP BY ProductId. The query is slow and scans many rows. The index used is:

CREATE INDEX InventoryByWarehouse ON Inventory (WarehouseId);

What is the most effective schema change to improve query performance?

Accepted Answer

Modify the index to INCLUDE StockLevel: CREATE INDEX InventoryByWarehouse ON Inventory (WarehouseId) STORING (StockLevel).. The query needs to read StockLevel for every row matching WarehouseId, but the existing index only covers WarehouseId, forcing a back-join to the base table. By using STORING (StockLevel), the index becomes a covering index that includes the StockLevel column, eliminating the need for the back-join and reducing the number of rows scanned to only those matching the warehouse filter.

Answer

Change the primary key to (WarehouseId, ProductId) so rows are interleaved by warehouse.

Answer

Create a materialized view that pre-aggregates stock by warehouse.

Answer

Add a STORED GENERATED column for total stock per warehouse.

Question 5

A healthcare analytics company uses Cloud Bigtable to store time-series data from medical devices. The table has a row key of 'device_id#timestamp' where timestamp is stored in reverse order (max - timestamp) so that recent data is at the top. Queries that fetch data for a specific device over a date range are very fast. However, analysts also need to run queries that aggregate data across all devices for a specific hour (e.g., count of readings between 2023-01-01 10:00 and 11:00). These queries are extremely slow because they require scanning all rows. The team must redesign the schema to support both access patterns without duplicating data unnecessarily. What is the best approach?

Accepted Answer

Create a second table with row key 'timestamp#device_id' (with timestamp in natural order) to support time-range queries.. Creating a second table with row key 'timestamp#device_id' (with timestamp in natural order) allows efficient range scans for a given time period across all devices, because Bigtable rows are sorted lexicographically by row key. This enables fast aggregation queries without scanning all rows. Option A (using BigQuery external table) would still require scanning the entire Bigtable for each query, and adds latency. Option B (increasing nodes) improves throughput but does not change the need to scan all rows, so it does not address the root cause. Option C (secondary index) is not supported in Bigtable.

Answer

Use BigQuery to query Bigtable via an external table and run the aggregation there.

Answer

Increase the number of Bigtable nodes to improve scan throughput.

Answer

Add a secondary index on the timestamp column.

Question 6

A BigQuery dataset contains a table with a STRUCT column for customer address. The BI team needs to query the city field from the struct. Which two approaches are valid? (Select TWO).

Accepted Answer

SELECT JSON_EXTRACT(TO_JSON(address), '$.city') FROM table. `JSON_EXTRACT(TO_JSON(address), '$.city')` converts the STRUCT to a JSON string and then extracts the `city` field using JSONPath syntax. Option C is correct because BigQuery allows direct field access on a STRUCT column using dot notation (`address.city`), which is the standard SQL syntax for nested fields.

Answer

SELECT UNNEST(address) as city FROM table

Answer

SELECT address['city'] FROM table

Answer

SELECT address.city.standard FROM table

Question 7

A DevOps team is designing a landing zone in Google Cloud. They need to set up a folder structure that supports multiple teams and environments. Which TWO practices should they follow? (Choose 2)

Accepted Answer

Create separate folders for each team (e.g., 'Team-A', 'Team-B') under the environment folders.. Best practices for landing zone design include using environment folders (prod, staging, dev) and team folders for resource isolation. Shared VPC, logging, and security projects are also common.

Answer

Use organization policies at the project level only to enforce compliance.

Answer

Create a flat project structure under the organization node with no folders.

Answer

Place all team projects in a single folder named 'Teams' without further grouping.

Question 8

A company wants to set up cost tracking by project, environment, and team. Which THREE methods should they use? (Choose 3)

Accepted Answer

Set up budget alerts to monitor spending.. Labels and billing export to BigQuery are the primary methods. Budget alerts help manage costs. Tags are for network firewall rules. Folders help organize but not directly track cost. Cloud Monitoring is for metrics.

Answer

Use Cloud Monitoring dashboards for billing.

Answer

Use network tags for cost tracking.

Question 9

A gaming company uses Memorystore for Redis to cache player session data. They need to ensure high availability with automatic failover in case of a zone failure. Which configuration should the Database Engineer choose?

Accepted Answer

Deploy a Standard tier Redis instance with replication across two zones.. Memorystore for Redis Standard tier provides cross-zone replication with automatic failover, ensuring high availability during a zone failure. The Standard tier uses a primary and replica instance in different zones, and if the primary fails, the replica is automatically promoted. This meets the requirement for automatic failover without manual intervention.

Answer

Deploy a Basic tier Redis instance with multiple read replicas.

Answer

Deploy a Memcached cluster with multiple nodes.

Answer

Deploy a Basic tier Redis instance in a single zone.

Question 10

A team uses Cloud Deploy to manage deployments to multiple GKE clusters in different environments. They need to ensure that only a specific service account can promote releases to the production target. What should they configure?

Accepted Answer

Grant the service account the 'roles/clouddeploy.releaser' role on the production target. Cloud Deploy uses IAM roles on targets to control who can promote. By granting the roles/clouddeploy.releaser role to the service account on the production target, only that account can promote releases to that target.

Answer

Restrict the service account's permissions via a VPC Service Controls perimeter

Answer

Grant the service account the 'roles/clouddeploy.operator' role on the delivery pipeline

Answer

Use a manual approval gate for the production stage

Question 11

An engineer is configuring Cloud Build to use a substitution variable for the Docker image tag. They want the tag to be the short commit SHA. Which built-in substitution should they use?

Accepted Answer

$SHORT_SHA

Answer

$TAG_NAME

Answer

$COMMIT_SHA

Answer

$REVISION_ID

Question 12

An organization wants to implement GitOps for their GKE clusters. They need to automatically sync the cluster state with a Git repository. Which Google Cloud service should they use?

Accepted Answer

Config Sync

Answer

Argo CD

Answer

Cloud Build

Answer

Cloud Source Repositories

Question 13

A team wants to reduce toil by automating a manual process that generates a report from Cloud Logging logs and emails it weekly. Which solution is most cost-effective and requires minimal operational overhead?

Accepted Answer

Cloud Scheduler + Cloud Functions. Cloud Scheduler triggers a Cloud Function or runs a query in BigQuery, but the most straightforward serverless option is a Cloud Function triggered by Cloud Scheduler. Cloud Composer is heavy for a simple report. Cloud Run requires containerization. Cloud Build is for CI/CD.

Answer

Cloud Run job manually started

Answer

Cloud Build trigger on schedule

Answer

Cloud Composer (Airflow) DAG

Question 14

A BI analyst wants to create a report that displays total revenue by product category and month, with ability to drill down to individual products. Which schema design supports this in BigQuery?

Accepted Answer

Star schema with fact table and dimension tables. A star schema with a central fact table (containing revenue measures) and separate dimension tables (for product category, month, and product) is the optimal design for BI reporting in BigQuery. This schema enables efficient aggregation by product category and month, while supporting drill-down to individual products via joins on the product dimension key. BigQuery's columnar storage and query engine are optimized for star schema joins, making this both performant and cost-effective.

Answer

Denormalized table with repeated fields

Answer

Single wide table with all dimensions and measures

Answer

Snowflake schema with normalized dimensions

Question 15

An engineer wants to deploy a set of GCP resources (e.g., Cloud SQL, Pub/Sub topics) alongside their Kubernetes workloads using a GitOps approach with Config Connector. What is the primary benefit of using Config Connector over deploying these resources manually?

Accepted Answer

It allows managing GCP resources using Kubernetes-style YAML, enabling version control and CI/CD for infrastructure.. Config Connector allows you to manage GCP resources (e.g., Cloud SQL, Pub/Sub topics) using Kubernetes-style YAML manifests. This enables GitOps workflows where infrastructure definitions are stored in a Git repository, version-controlled, and automatically applied via CI/CD pipelines, ensuring consistency and auditability.

Answer

It automatically scales GCP resources based on load.

Answer

It provides a graphical UI for managing GCP resources.

Answer

It reduces the cost of GCP resources by using committed use discounts.

Question 16

What is the primary purpose of including a runbook URL in an alert policy's documentation?

Accepted Answer

To give responders immediate access to troubleshooting steps and escalation procedures

Answer

To link to a dashboard that shows the alert's metric

Answer

To automatically trigger a Cloud Function when the alert fires

Answer

To provide a direct link to the source code repository

Question 17

A team wants to reduce toil by automating a recurring cloud resource update. Which THREE Google Cloud services can be used together to build an automated pipeline? (Choose 3 answers)

Accepted Answer

Cloud Scheduler. Cloud Build can run automation scripts, Cloud Functions can be triggered by events, and Cloud Scheduler can trigger periodic jobs. Together they can form a pipeline. Pub/Sub and Deployment Manager are also possible but the question asks for THREE from the given set that are commonly used together.

Answer

Cloud Pub/Sub

Answer

Cloud Deployment Manager

Question 18

Which of the following is a key benefit of using structured logging in Cloud Logging?

Accepted Answer

It enables automatic parsing of log fields for easier querying and correlation with traces.

Answer

It reduces log storage costs by compressing data.

Answer

It automatically creates log-based metrics from the log entries.

Answer

It allows logs to be shipped to BigQuery in real-time.

Question 19

A DevOps team wants to alert when a Compute Engine instance is unreachable for 5 minutes. Which alerting condition type should be used?

Accepted Answer

Absent condition

Answer

Metric threshold condition

Answer

Logs-based alerting

Answer

Forecast condition

Question 20

Your team is migrating a 5 TB MySQL database from on-premises to Cloud SQL. The database receives 2,000 writes per second and the network link has 500 Mbps bandwidth. You need to minimize migration time with zero data loss. What should you do?

Accepted Answer

Configure Database Migration Service with a connectivity test and start continuous replication.. Database Migration Service (DMS) with continuous replication is the correct choice because it supports live migration with minimal downtime and zero data loss for large databases like 5 TB. DMS uses MySQL binlog-based replication to synchronize changes from the on-premises source to Cloud SQL while the source remains operational, then performs a cutover with only seconds of downtime. This approach handles the 2,000 writes/second load and 500 Mbps bandwidth efficiently by streaming incremental changes rather than transferring the entire 5 TB in one shot.

Answer

Export the database using mysqldump and import into Cloud SQL using the console.

Answer

Use gcloud sql import with a compressed CSV export from on-premises.

Answer

Set up a VPN, then use mysqldump with --master-data and pipe to mysql on Cloud SQL.