PCDE Practice Exam 52 — 20 Questions

Question 1

Which of the following is an example of toil according to SRE principles?

Accepted Answer

Manually restarting failed pods in a Kubernetes cluster. Toil is manual, repetitive, automatable work with no enduring value. Manually restarting failed pods is a classic example.

Answer

Reviewing code from a junior developer

Answer

Writing a new feature for the application

Answer

Designing a new microservice architecture

Question 2

A team wants to implement Chaos Engineering on GKE to test the resilience of their microservices by randomly killing pods and injecting network latency. Which tool is specifically designed for this purpose on GKE?

Accepted Answer

Chaos Mesh. Chaos Mesh is an open-source chaos engineering platform for Kubernetes. It provides fault injection (pod kill, network latency, etc.) and integrates with GKE.

Answer

Cloud Armor

Answer

Cloud Shell

Answer

Traffic Director

Question 3

Which of the following is NOT a characteristic of toil as defined by SRE?

Accepted Answer

Requires complex problem-solving. Toil is manual, repetitive, automatable, and has no enduring value. Complex design work is the opposite.

Answer

No enduring value

Answer

Repetitive

Answer

Manual

Question 4

A team has an SLO of 99.9% availability over a 30-day period. How many minutes of downtime does the error budget allow per month?

Accepted Answer

43 minutes. Error budget = 100% - SLO target = 0.1% of total time. 30 days = 43,200 minutes. 0.1% of 43,200 = 43.2 minutes. Rounding gives 43 minutes.

Answer

4.32 minutes

Answer

432 minutes

Answer

4,320 minutes

Question 5

An SRE team uses PagerDuty for on-call rotation. They receive a critical alert at 2 AM. According to incident management best practices, what should the on-call engineer do first?

Accepted Answer

Acknowledge the alert and begin triage according to the runbook. The first step is to acknowledge the alert to signal that someone is responding, then assess severity and begin response per the runbook.

Answer

Ignore it until morning because it's off-hours

Answer

Start a postmortem immediately

Answer

Immediately escalate to the incident commander

Question 6

An SRE team has defined a service's availability SLI as the proportion of successful requests over a 5-minute window. They set an SLO of 99.9% over 30 days. What is the error budget for a 30-day period?

Accepted Answer

43 minutes 12 seconds. Error budget = (100% - SLO) * total time. For 30 days (43200 minutes), 0.1% of that is 43.2 minutes. The closest option is 43 minutes 12 seconds.

Answer

4 hours 19 minutes

Answer

7 minutes 12 seconds

Answer

43 minutes 12 seconds per week

Question 7

A company's application using Cloud Bigtable is experiencing high read latency. The row keys are based on a timestamp prefix. Which design change is most likely to improve performance?

Accepted Answer

Reverse the timestamp in row keys to distribute writes.. In Cloud Bigtable, monotonically increasing row keys (like timestamps) cause all writes to hit a single tablet server, creating a hotspot that degrades read and write performance. Reversing the timestamp (e.g., using `Long.MAX_VALUE - timestamp`) distributes writes across the key space, preventing hotspots and reducing read latency by balancing load across nodes.

Answer

Increase the number of column families.

Answer

Use a single node cluster.

Answer

Use monotonically increasing row keys.

Question 8

A company needs to store time-series sensor data with high write throughput (millions of writes per second) and low latency reads. Which database service should they choose?

Accepted Answer

Cloud Bigtable. Cloud Bigtable is a fully managed, scalable NoSQL database designed for large analytical and operational workloads, handling millions of writes per second with consistent low-latency reads. It uses a distributed, replicated SSTable storage engine and is optimized for time-series data, making it ideal for high-throughput sensor ingestion.

Answer

Cloud SQL

Answer

Firestore

Answer

Cloud Spanner

Question 9

You are managing a Cloud Spanner instance that supports a global e-commerce application. Queries that join two large tables (Orders and OrderItems) have high latency. The tables use the CustomerID as the primary key prefix. The join condition is on OrderID, which is the second part of the primary key in both tables. What should you do to improve performance?

Accepted Answer

Change the primary key of both tables to start with OrderID, then CustomerID.. By making OrderID the first part of the primary key, the join becomes a local join within the same split, reducing cross-node communication. Option A is wrong because increasing nodes may not fix the join strategy and costs more. Option B is wrong because secondary indexes do not help with joins across tables. Option D is wrong because interleaving tables requires a parent-child relationship by primary key, which is not the case here (OrderID is not a prefix of the parent's primary key).

Answer

Increase the number of nodes to handle the load.

Answer

Create a secondary index on OrderID in both tables.

Answer

Recreate the tables as interleaved tables with Orders as parent.

Question 10

A company uses Argo CD on GKE for GitOps deployments. They want to ensure that when a developer pushes a change to a Kubernetes manifest, Argo CD automatically syncs the cluster. What must be configured?

Accepted Answer

Configure a webhook in the git repository that notifies Argo CD of changes. Argo CD can be configured to automatically sync a cluster when a developer pushes a change to a Kubernetes manifest by setting up a webhook in the Git repository. The webhook notifies Argo CD of the push event, triggering a sync operation without manual intervention or polling. This is the standard GitOps pattern for event-driven synchronization.

Answer

Use a Cloud Build trigger to run `argocd app sync`

Answer

Set the sync policy to Automatic with Prune

Answer

Enable Config Sync instead of Argo CD for automatic sync

Question 11

What is the most likely cause of the high execution time?

Accepted Answer

Missing index on status column. The execution plan shows a full table scan. Since the query filters on the status column, an index on that column would allow direct lookup instead of scanning all rows. The high execution time is most likely due to the missing index on the status column. Therefore, option B is correct. Options A, C, D, and E are not the primary cause: string comparison (A) does not inherently cause high execution time; selecting two columns (C) is not inefficient; insufficient instance nodes (D) would affect overall performance but not specifically this query; not filtering on primary key (E) is not a problem if other columns are indexed appropriately.

Answer

The WHERE clause uses a string comparison

Answer

The query selects two columns causing inefficiency

Answer

The instance has insufficient nodes

Answer

The query does not filter on primary key

Question 12

A company wants to run complex analytical queries on terabytes of data with sub-second response times. The data is structured and stored in Cloud Storage as Parquet files. They need a serverless solution that can query the data directly without loading it into a database. Which service should they use?

Accepted Answer

BigQuery. BigQuery is the correct choice because it is a serverless, fully managed data warehouse that supports querying structured data directly from Cloud Storage using external tables, without requiring data loading. It can handle terabytes of data with sub-second response times via its columnar storage, automatic scaling, and BI Engine for acceleration.

Answer

Cloud Dataproc

Answer

Cloud Bigtable

Answer

Cloud SQL

Question 13

Your Cloud Bigtable instance is experiencing hot spots, causing performance degradation. You want to identify the specific row keys causing the hot spots. Which tool should you use?

Accepted Answer

Key Visualiser. Key Visualiser is a Cloud Bigtable tool that visualises read/write traffic across the row key space, helping identify hot spots (rows with disproportionate traffic). Cloud Monitoring provides overall metrics but not row-level detail. Cloud Logging logs queries but not aggregated heat maps. cbt is the command-line tool for administrative tasks but does not provide visualisation.

Answer

Cloud Monitoring dashboard

Answer

cbt command-line tool

Answer

Cloud Logging

Question 14

An analyst writes a SQL query that joins a fact table with multiple dimension tables. The query runs slowly due to shuffling. Which optimization technique should be applied?

Accepted Answer

Cluster the fact table on the dimension join keys.. Shuffling occurs when data must be redistributed across nodes during joins, often because the join keys are not co-located. Clustering the fact table on the dimension join keys physically co-locates rows with the same join key values, minimizing data movement during the join. This is a direct optimization for shuffle-heavy workloads in distributed SQL engines like Spark SQL or Hive.

Answer

Use a subquery in the FROM clause to pre-aggregate.

Answer

Use a LIMIT clause to restrict rows.

Answer

Use a window function to precompute values.

Question 15

Match each database migration term to its description.

Accepted Answer

Homogeneous migration: Migrating a database from one source engine to the same target engine.. The correct matches are: Homogeneous migration = same engine, Heterogeneous migration = different engine, Database Migration Service = Google Cloud's database migration tool. Common confusions involve swapping the definitions of homogeneous and heterogeneous, or misattributing DMS to application migration.

Answer

Homogeneous migration: Migrating a database to a different database engine.

Answer

Heterogeneous migration: Migrating a database to the same database engine.

Answer

Database Migration Service (DMS): A tool for migrating applications to compute engines.

Question 16

You are a database engineer for an e-commerce platform running on Cloud SQL for PostgreSQL. The application team reports that a critical report query taking 5 seconds last week now takes over 30 seconds. The database CPU usage has increased from 40% to 85%. The query plan shows a sequential scan on the orders table. Which action should you take first to diagnose the problem?

Accepted Answer

Enable pg_stat_statements and check the query's execution statistics.. Enabling pg_stat_statements provides detailed execution statistics (e.g., total time, calls, rows, I/O) for each query, allowing you to identify the root cause of the performance regression without making speculative changes. Since the query plan shows a sequential scan and CPU is high, pg_stat_statements can reveal if the query is now reading more rows due to data growth or plan changes, guiding the next action (e.g., adding an index or tuning parameters).

Answer

Migrate the database to Cloud Spanner for better scaling.

Answer

Add a composite index on the orders table based on the query's WHERE clause.

Answer

Increase the machine type to add more vCPUs.

Question 17

An engineer uses Cloud Build with a private pool to build an application that needs to connect to a Cloud SQL database. The build step fails with a connection timeout. What is the most likely cause?

Accepted Answer

The private pool is not peered with the VPC that contains the Cloud SQL instance. A private Cloud Build pool runs in a customer-managed VPC, so it must be peered with the VPC hosting the Cloud SQL instance to establish network connectivity. Without VPC peering, the build step cannot reach the Cloud SQL private IP, resulting in a connection timeout. This is the most likely cause because the error is a timeout, not an authentication or configuration issue.

Answer

The Cloud Build service account lacks permissions to connect to Cloud SQL

Answer

The database name is incorrect

Answer

The Cloud SQL instance requires SSL

Question 18

An e-commerce platform wants to implement chaos engineering on its Google Kubernetes Engine cluster to test resilience against network latency. Which tool is specifically designed for this purpose on GKE?

Accepted Answer

Chaos Mesh. Chaos Mesh is an open-source chaos engineering platform for Kubernetes. It can inject various faults including network latency, and is available on GKE. Traffic Director fault injection is for service mesh, not directly for GKE pods. Cloud Functions is not for Kubernetes.

Answer

Traffic Director fault injection

Answer

Cloud Functions

Answer

Cloud Build

Question 19

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 20

A BI team uses a complex SQL query with multiple Common Table Expressions (CTEs) that are referenced several times within the main query. The query performs poorly. What is the best optimization strategy?

Accepted Answer

Use temporary tables or table snapshots to materialize the CTE results. CTEs are not materialized by default; they are re-evaluated each time they are referenced, leading to repeated execution of the same logic. By using temporary tables or table snapshots, you materialize the intermediate result set once, which avoids redundant scans and significantly improves performance for complex queries with multiple CTE references.

Answer

Add indexes on the tables used in the CTEs

Answer

Reuse the same CTE names as often as possible in the query

Answer

Replace CTEs with derived tables in the FROM clause