PCDE Practice Exam 58 — 20 Questions

Question 1

Which TWO statements correctly describe characteristics of toil in SRE? (Choose 2 answers)

Accepted Answer

Toil is repetitive and manually performed.. Option B is correct because toil is defined in SRE as work that is manual, repetitive, and tactical, such as manually restarting processes or handling the same alert repeatedly. Option E is correct because toil is characterized by providing no enduring value to the service — once the task is done, the service is no better off than before, unlike engineering work that produces lasting improvements. Options A, C, and D are incorrect: toil is not always automatable (some tasks resist automation), toil typically grows as a service scales rather than decreases, and toil by definition lacks enduring value, so it cannot add it.

Answer

Toil is always automatable.

Answer

Toil decreases as the service scales.

Answer

Toil adds enduring value to the service.

Question 2

Which TWO metrics are appropriate for defining a request-based SLI for a web service? (Choose 2)

Accepted Answer

Latency: proportion of requests under a threshold. Option A (Latency: proportion of requests under a threshold) is correct because a request-based SLI measures the quality of individual requests, and expressing latency as the fraction of requests served faster than a target (e.g., 95% of requests < 300 ms) is a standard request-based SLI. Option D (Availability: successful requests / total requests) is correct because it is a ratio of good requests to total requests, which is the canonical request-based SLI for a web service. Option B is not appropriate because throughput (requests per second) is a demand/capacity metric, not a measure of request quality or success. Option C is not appropriate because a raw count of 5xx responses is not normalized to total requests, so it cannot serve as a ratio-based SLI. Option E is not appropriate because uptime in minutes is a time-based (resource) metric, not a request-based SLI.

Answer

Throughput: requests per second

Answer

Error count: number of 5xx responses

Answer

Uptime: minutes service is up

Question 3

A team wants to use Cloud Profiler to identify CPU hot functions in a production service. Which TWO statements about Cloud Profiler are correct? (Choose 2)

Accepted Answer

It provides flame graphs to visualize function call stacks. Option A is correct because Cloud Profiler collects stack traces and renders them as flame graphs, which visualize function call stacks and make it easy to spot CPU hot functions in a production service. Option C is correct because Cloud Profiler is designed for continuous production profiling with low overhead, typically around 0.5% of CPU, so it can run alongside the service without materially affecting performance. Option B is wrong because Cloud Profiler supports multiple languages, including Java, Go, Python, Node.js, and C#, not Java alone. Option D is wrong because Cloud Profiler uses agents and libraries that generally require no explicit profiling calls in application code. Option E is wrong because profiling is not automatic for all functions without configuration; you must enable the profiler and may configure settings such as profiling frequency and target.

Answer

It can profile only Java applications

Answer

It requires modifying application code to add profiling calls

Answer

It profiles all functions by default with no configuration

Question 4

A team manages a Cloud Spanner database and needs to perform a schema change to add a new column to an existing table and create a secondary index. They want to avoid downtime and ensure the changes are applied without blocking reads or writes. Which two statements are correct about making these changes in Spanner? (Choose TWO.)

Accepted Answer

The ALTER TABLE statement to add a column is non-blocking and can be executed using gcloud spanner databases ddl update. Option C is correct because adding a column via ALTER TABLE in Cloud Spanner is an online, non-blocking schema change that does not require downtime, and it can be applied with the gcloud spanner databases ddl update command (or equivalent DDL API). Option D is correct because Spanner supports submitting multiple DDL statements, including ALTER TABLE and CREATE INDEX, together in a single DDL batch, which applies them atomically and avoids intermediate schema states. Option A is incorrect because CREATE INDEX in Spanner is designed to build the index online without blocking reads or writes on the base table. Option B is incorrect because Spanner supports both unique and non-unique secondary indexes. Option E is incorrect because creating an index does not require exporting and re-importing data; Spanner builds the index from existing data automatically.

Answer

The CREATE INDEX statement will block reads on the table during index creation

Answer

Indexes can only be created as unique indexes

Answer

To create an index, you must first export and re-import the data

Question 5

A team is planning a migration from Oracle to PostgreSQL on Cloud SQL. They use Ora2Pg to convert the schema. Which THREE Oracle data types require special attention for correct mapping to avoid data loss or precision issues? (Choose 3 correct answers.)

Accepted Answer

DATE. Option A (DATE) is correct because Oracle DATE stores both date and time (down to the second), whereas PostgreSQL DATE stores only the date; Ora2Pg must map it to TIMESTAMP (or TIMESTAMPTZ) to avoid losing the time component. Option B (NUMBER(10,2)) is correct because Oracle NUMBER is a variable-precision type, and mapping it to PostgreSQL requires choosing NUMERIC(p,s) with matching precision/scale (or BIGINT for scale 0) to prevent rounding or overflow issues. Option D (CLOB) is correct because Oracle CLOB must be mapped to PostgreSQL TEXT (or BYTEA for BLOB), and Ora2Pg needs special handling for large-object storage and encoding to avoid truncation or data loss. Option C (FLOAT) is not among the marked answers because Oracle FLOAT is essentially a NUMBER subtype that maps predictably to PostgreSQL DOUBLE PRECISION or NUMERIC, so it does not require the same special attention. Option E (VARCHAR2) is not marked because it maps straightforwardly to PostgreSQL VARCHAR/TEXT, with only length semantics (byte vs. character) needing routine adjustment rather than special precision handling.

Answer

FLOAT

Answer

VARCHAR2

Question 6

A team needs to automate the reduction of toil in their operations. Which THREE of the following are valid strategies to reduce toil according to SRE principles?

Accepted Answer

Automating repetitive manual tasks using Cloud Functions. Option A is correct because SRE defines toil as manual, repetitive, automatable work tied to running a service, and replacing such tasks with automation such as Cloud Functions (event-driven, serverless compute) directly eliminates that toil. Option C is correct because Workflows orchestrates multi-step operational processes end-to-end, removing the need for engineers to manually chain and execute each step, which is a core toil-reduction strategy. Option D is correct because self-service tooling shifts routine deployment and operational actions to developers, reducing the number of repetitive requests and manual interventions the SRE/ops team must perform. Option B is not a valid strategy because adding headcount to absorb manual work scales the toil rather than eliminating it, which contradicts SRE principles. Option E is not a valid strategy because SRE guidance caps toil at roughly 50% of each engineer's time as a ceiling to preserve engineering work, not as a target or a mechanism that reduces toil itself.

Answer

Scaling the operations team to handle more manual work

Answer

Setting a toil budget that limits toil to 50% of the team's time

Question 7

An organization wants to use Cloud Build to automatically build and test code changes when a developer pushes to any branch in a Cloud Source Repositories repository. Which two configurations are needed?

Accepted Answer

A cloudbuild.yaml file in the repository. Option B is correct because Cloud Build requires a build configuration file, typically cloudbuild.yaml, in the repository to define the build and test steps that execute when the trigger fires. Option E is correct because a push trigger configured with a branch regex of '.*' matches any branch, satisfying the requirement to build on pushes to any branch in the Cloud Source Repositories repo. Option A is incorrect because a pull request trigger only fires on PR events, not on direct pushes to branches. Option C is incorrect because a scheduled trigger with cron runs on a time schedule rather than on developer pushes. Option D is incorrect because a manual trigger with webhook requires explicit invocation and does not automatically respond to branch pushes.

Answer

A pull request trigger

Answer

A scheduled trigger with cron

Answer

A manual trigger with webhook

Question 8

You need to monitor the replication lag between a Cloud SQL for MySQL primary instance and its read replica. Which metric should you use to set up an alert?

Accepted Answer

cloudsql.googleapis.com/database/replication/replication_lag. Cloud SQL exposes a metric 'replication/replication_lag' (or 'cloudsql.googleapis.com/database/replication/replication_lag') that measures the lag in seconds between the primary and replica. This is the correct metric for alerting.

Answer

cloudsql.googleapis.com/database/replication/replica_count

Answer

cloudsql.googleapis.com/database/cpu/utilization

Answer

cloudsql.googleapis.com/database/memory/utilization

Question 9

A data engineering team needs to run complex analytical queries on terabytes of data stored in Cloud Storage. The queries are ad-hoc and require scanning large portions of the dataset. The team needs a serverless solution that optimizes for cost by charging only for the data processed. Which Google Cloud service should they use?

Accepted Answer

BigQuery. BigQuery is a serverless data warehouse that uses columnar storage and charges for the data scanned by queries. It is ideal for ad-hoc analytical queries on large datasets.

Answer

Dataproc

Answer

Cloud SQL

Answer

Cloud Spanner

Question 10

Which TWO are effective strategies to control costs when running BI queries on BigQuery? (Choose two.)

Accepted Answer

Set a maximum bytes billed limit for user projects.. Setting a maximum bytes billed limit for user projects in BigQuery allows you to cap the amount of data processed per query, preventing runaway costs from accidental or inefficient queries. This is a direct cost control mechanism that enforces a hard stop on query bytes processed, ensuring that users cannot exceed a predefined budget.

Answer

Create materialized copies of tables for each dashboard.

Answer

Schedule queries to run every minute to keep the cache warm.

Answer

Enable BI Engine for all tables to speed up queries.

Question 11

Refer to the exhibit. Which BigQuery SQL query correctly flattens the items into rows?

Accepted Answer

SELECT * FROM orders CROSS JOIN UNNEST(items) AS items. `CROSS JOIN UNNEST(items)` is the standard BigQuery syntax to flatten a repeated (array) column into individual rows. The `UNNEST` operator expands each array element into a separate row, and `CROSS JOIN` ensures that all non-array columns from the `orders` table are preserved alongside each element. This is the only option that correctly transforms the nested `items` array into a normalized row-per-item structure.

Answer

SELECT * FROM orders WHERE items IS NOT NULL

Answer

SELECT * FROM orders, UNNEST(items) AS items

Answer

SELECT * FROM orders INNER JOIN items ON true

Question 12

Which TWO are best practices for designing a star schema in BigQuery for BI? (Choose two.)

Accepted Answer

Store dimension attributes in a single denormalized dimension table instead of multiple normalized tables.. In BigQuery, storing dimension attributes in a single denormalized dimension table (star schema) reduces the number of joins required in BI queries, improving query performance and simplifying SQL. BigQuery's columnar storage and distributed architecture handle denormalized dimensions efficiently, avoiding the overhead of multiple normalized tables that would require complex joins and slow down analytical queries.

Answer

Partition fact tables by low-cardinality columns like gender.

Answer

Pre-aggregate all measures at every possible grain in the fact table.

Answer

Avoid using joins entirely by storing all data in one wide table.

Question 13

A Cloud SQL instance stores financial data. They need to meet a 1-hour RPO and 30-minute RTO. What backup configuration should they use?

Accepted Answer

Automatic backups plus binary logging to enable point-in-time recovery (PITR).. Automatic backups combined with binary logging enable point-in-time recovery (PITR), which allows restoring the database to any point within the backup retention period. This configuration meets the 1-hour RPO by recovering transactions committed within the last hour, and the 30-minute RTO by using the most recent full backup plus binary logs to restore quickly.

Answer

Export once a day to Cloud Storage.

Answer

Enable high availability.

Answer

Automatic backups with a schedule of 1 hour.

Question 14

A team manages Terraform state for multiple projects using a single GCS bucket. They need to ensure that state operations are not concurrent to avoid corruption. What should they do?

Accepted Answer

Configure the GCS backend with `prefix` per project and rely on Terraform's built-in state locking via GCS.. Terraform's GCS backend natively supports state locking using the GCS object's generation number. By configuring a unique `prefix` per project, each project's state is stored in a separate object within the same bucket. Terraform automatically acquires a lock by creating a temporary lock file in GCS before any state operation, and releases it afterward, preventing concurrent modifications and state corruption.

Answer

Store state in a single file and use IAM to allow only one user at a time.

Answer

Use `terraform force_unlock` before each run.

Answer

Enable object versioning on the GCS bucket.

Question 15

Your team is designing a schema for Cloud SQL (MySQL) for a content management system. You need to implement full-text search on article content. Which TWO schema design choices are appropriate? (Choose two.)

Accepted Answer

Use Cloud SQL's built-in full-text search feature.. Cloud SQL for MySQL provides built-in full-text search capabilities that allow efficient searching of text data. Adding a FULLTEXT index on the content column enables the use of MATCH...AGAINST queries, which are optimized for natural language search and are far more performant than LIKE operations. This is the correct approach because it leverages the database engine's native indexing and search algorithms.

Answer

Use the LIKE operator with wildcards for pattern matching.

Answer

Store article content in a Cloud Storage bucket and query metadata.

Answer

Normalize content into a separate table and use joins.

Question 16

You need to set up a Cloud Monitoring alert for a Cloud Spanner instance to notify when the CPU utilization exceeds a threshold that could indicate performance degradation. What is the recommended CPU utilization threshold for Cloud Spanner?

Accepted Answer

65%. The recommended CPU utilization threshold for Cloud Spanner is 65%. This value is based on Google's best practices, as sustained CPU usage above 65% can lead to increased latency and performance degradation due to queuing and contention. Setting the alert at 65% provides a proactive warning before the instance reaches a critical state, allowing time for scaling or optimization.

Answer

90%

Answer

40%

Answer

80%

Question 17

When designing a schema for a data warehouse in BigQuery, which table type is most cost-effective for storing raw event data that will be queried by date range filters?

Accepted Answer

A partitioned table partitioned by date column. Partitioned tables in BigQuery allow you to divide a table into segments based on a date, timestamp, or integer column. When querying with a date range filter, BigQuery can prune partitions, scanning only the relevant data rather than the entire table. This dramatically reduces the amount of data processed, lowering query costs and improving performance, making it the most cost-effective choice for storing raw event data that is frequently queried by date.

Answer

A table with integer range partitioning on an ID column

Answer

A regular table with no partitioning

Answer

A regular table clustered on timestamp

Question 18

A company uses Firestore in Datastore mode. They need to create a composite index for a query that filters on two properties. The query is already running and returning an error that an index is required. What is the correct way to create this index?

Accepted Answer

Create the index using the gcloud datastore indexes create command with a YAML file.. In Firestore (Datastore mode), composite indexes must be explicitly created before they can be used by queries that filter on multiple properties. The `gcloud datastore indexes create` command with a YAML file is the standard method to define and deploy these indexes, as the Datastore mode does not automatically create composite indexes from query patterns.

Answer

Modify the query to use a single filter to avoid needing a composite index.

Answer

Enable the 'auto-index' feature in the Datastore console.

Answer

The index will be created automatically based on the query pattern.

Question 19

A company stores user events in BigQuery as nested repeated fields. They want to use Looker to build dashboards on individual events. Which SQL pattern should they use in a derived table to flatten the data?

Accepted Answer

SELECT fields FROM table, UNNEST(events) AS event. UNNEST(events) in BigQuery SQL flattens the nested repeated field 'events' into individual rows, enabling Looker to treat each event as a separate record for dashboarding. This is the standard pattern for denormalizing arrays in BigQuery derived tables, as it converts each array element into its own row while preserving the parent record's fields.

Answer

SELECT fields FROM table WHERE events IS NOT NULL

Answer

SELECT ARRAY_AGG(events) FROM table

Answer

SELECT events.* FROM table

Question 20

A team is designing a Cloud SQL for PostgreSQL schema for a multi-tenant SaaS application. They need to isolate tenant data while maintaining query performance and manageability. Which two approaches are appropriate? (Choose two.)

Accepted Answer

Use a single schema with a tenant_id column on every table and row-level security.. Using a single schema with a tenant_id column and row-level security (RLS) in PostgreSQL allows tenant data isolation at the row level while maintaining a single database and schema. RLS policies automatically filter rows based on the current session's tenant context, ensuring performance is optimized through standard indexing on tenant_id and avoiding the overhead of multiple databases or schemas.

Answer

Use separate databases per tenant.

Answer

Use a single table for all tenants with no tenant identifier.

Answer

Use a separate Cloud SQL instance per tenant.