PCDE Mock Exam 78 — 25 Questions

Question 1

A team wants to create an SLO for a batch data pipeline that processes files hourly. They want to measure whether each batch completes successfully within the hour. Which type of SLI should they use?

Accepted Answer

Window-based SLI measuring good minutes over total minutes. For batch or sliding window data, a window-based SLI is appropriate: it counts good minutes (or windows) where the pipeline succeeded within the time window, divided by total minutes. Request-based SLIs are for individual request/response pairs.

Answer

Latency-based SLI measuring p99 of file processing time

Answer

Request-based SLI measuring good requests over total requests

Answer

Availability SLI based on successful API calls

Question 2

An SRE team wants to perform fault injection testing on a GKE cluster by injecting network latency into a specific set of pods. Which tool should they use?

Accepted Answer

Chaos Mesh on GKE.. Chaos Mesh is an open-source chaos engineering platform specifically designed for Kubernetes. It can inject faults like network latency into targeted pods.

Answer

Cloud Functions with network disruption script.

Answer

Traffic Director fault injection.

Answer

Google Cloud Armor.

Question 3

An SRE team wants to track the amount of toil each week and ensure it does not exceed 50% of the team's time. Which approach is most aligned with SRE best practices?

Accepted Answer

Have each team member log their time and estimate toil percentage weekly. SRE best practice is to have team members estimate and track toil time weekly, aiming for under 50%. Using a simple spreadsheet is a valid approach to start.

Answer

Use Cloud Monitoring to automatically classify all tasks as toil

Answer

Use Cloud Tasks to queue up toil items and measure completion time

Answer

Set a Cloud Scheduler job to remind team members to automate toil

Question 4

An SRE team implements error budget alerting using Cloud Monitoring. They want to set a 'fast burn' alert that triggers when the error budget burn rate exceeds 14x over a 1-hour window. What is the purpose of this alert?

Accepted Answer

To alert immediately when error budget is being consumed at a rate that would exhaust the budget in approximately 51 hours (14x faster than allowed). Fast burn alerts (e.g., 14x burn rate over 1h) are designed to detect severe, rapid consumption of error budget, prompting immediate investigation. They complement slow burn alerts (5x over 6h) which catch gradual budget erosion.

Answer

To detect gradual, long-term trends in error budget consumption

Answer

To alert when the error budget is completely exhausted

Answer

To trigger a page for on-call engineers when the service is likely to exceed SLO within the next 6 hours

Question 5

During a postmortem, an SRE team identifies several contributing factors. Which THREE items should be included in the action items section of a blameless postmortem?

Accepted Answer

Verification steps to confirm the fix is effective. Action items should be specific, have an owner, and a due date. Assigning blame or vague plans are not appropriate. The items should address systemic issues.

Answer

Generic recommendations like 'improve testing'

Answer

Assign blame to the engineer who caused the incident

Question 6

An SRE team notices that a routine database cleanup task takes 30 minutes of manual effort each week. The task does not add enduring value and scales linearly with the number of databases. How should the team classify this work?

Accepted Answer

Toil.. This work is manual, repetitive, does not add enduring value, and scales with service growth — the classic definition of toil. SREs should automate it and track it against the toil budget.

Answer

Technical debt.

Answer

Operational overhead.

Answer

Engineering project.

Question 7

An application running on Google Kubernetes Engine (GKE) emits structured logs in JSON format. The DevOps team wants to count the number of log entries that contain a specific error code (e.g., 'error_code': 500) in the last hour and use that count to trigger an alert if it exceeds a threshold. What is the most efficient way to achieve this?

Accepted Answer

Create a log-based counter metric in Cloud Logging with the filter jsonPayload.error_code=500, then set up an alerting policy on that metric.. Creating a log-based metric from the logs is the most efficient approach. You can define a counter metric that increments each time a log entry matches the filter (e.g., jsonPayload.error_code=500). Then you can set up an alerting policy on that metric. This avoids scanning logs in real-time and provides a metric that can be used for dashboards and alerts.

Answer

Use Cloud Logging's Logs Explorer to run a query every minute and use Cloud Scheduler to trigger a Cloud Function that checks the count.

Answer

Export logs to BigQuery and run a scheduled query to count error codes, then use the result to trigger an alert via Cloud Monitoring.

Answer

Configure a metric threshold alert directly on the log entries in Cloud Monitoring without creating a metric.

Question 8

You need to set up a notification channel for alerts that sends messages to a custom internal incident management system via a webhook. Which notification channel type should you use?

Accepted Answer

Cloud Pub/Sub. Cloud Monitoring supports webhooks via Pub/Sub. You can create a Cloud Pub/Sub notification channel and subscribe with a webhook endpoint. Other channels like email, SMS, and PagerDuty are pre-defined but not customizable for webhooks.

Answer

PagerDuty

Answer

Email

Answer

SMS

Question 9

A BI report requires a running total of sales over the last 30 days for each product. The data is in a BigQuery table with columns: sale_date, product_id, amount. Which SQL window function is most efficient?

Accepted Answer

Use SUM(amount) OVER (ORDER BY sale_date ROWS BETWEEN 30 PRECEDING AND CURRENT ROW). The most efficient among the given choices for a 30-day rolling sum, because it uses a window function with `ROWS BETWEEN 30 PRECEDING AND CURRENT ROW` to limit the sum to the last 30 rows. Although a true time-based window would require `RANGE BETWEEN INTERVAL 29 DAY PRECEDING AND CURRENT ROW` with `PARTITION BY product_id`, that is not offered. Option C gives a cumulative sum (unbounded) which is not a 30-day total. Options A and D are set-based or inefficient. Thus B is the best available.

Answer

Use GROUP BY with SUM(amount)

Answer

Use SUM(amount) OVER (ORDER BY sale_date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW)

Answer

Use a correlated subquery to sum over previous dates

Question 10

An SRE team wants to track the amount of toil their team performs each week and set a goal to keep it under 50% of working time. Which approach should they use?

Accepted Answer

Use Cloud Monitoring to automatically detect and log toil activities based on predefined patterns. Toil tracking is essential for SRE teams to ensure that time spent on repetitive, manual tasks does not exceed 50%. While manual methods like spreadsheets are possible, the best practice is to automate detection using monitoring tools. Cloud Monitoring can be configured with custom metrics and alerting policies to identify patterns indicative of toil (e.g., repeated manual interventions, high alert fatigue). By defining patterns that correlate with toil, the team can automatically log and track the time spent on such activities, enabling objective measurement against the 50% target. This approach is more reliable and scalable than self-reported estimates at stand-ups, which are subjective and prone to bias. Therefore, option A is correct as it uses Cloud Monitoring to automate toil detection.

Answer

Ask team members to estimate toil as a percentage in daily stand-ups

Answer

Ignore toil tracking; focus only on SLOs

Answer

Use Cloud Tasks to record toil

Question 11

A company runs a BigQuery data warehouse with many scheduled queries and materialized views. They notice that materialized view refreshes are taking longer than expected, causing delays in downstream reports. What is the most effective optimization?

Accepted Answer

Partition and cluster the base table on columns used in the materialized view. Partitioning and clustering the base table on columns used in the materialized view (D) is the most effective optimization because it allows BigQuery to perform incremental refreshes using only the changed partitions, significantly reducing scan and recomputation overhead. Without proper partitioning, the materialized view refresh must scan the entire base table, which becomes increasingly costly as data grows. Clustering further improves efficiency by co-locating related data, minimizing the data processed during aggregation or join operations in the refresh.

Answer

Manually refresh materialized views outside peak hours

Answer

Increase the refresh interval to reduce frequency

Answer

Disable automatic refresh and use scheduled queries to rebuild the materialized view

Question 12

A service has an SLO of 99.99% availability over 28 days. The team wants to set up a slow burn alert that will notify them within 6 hours if error budget consumption is at 5x the budgeted rate. How much error budget has been consumed after 6 hours at this rate? The total error budget for 28 days is 4 minutes and 2 seconds (242 seconds).

Accepted Answer

10.8 seconds. The total error budget is 242 seconds over 28 days (672 hours). The budgeted error rate is 242 seconds / 672 hours ≈ 0.3601 seconds per hour. At a 5x burn rate, the consumption rate is 5 × 0.3601 ≈ 1.8005 seconds per hour. Over 6 hours, consumption = 1.8005 × 6 ≈ 10.8 seconds. Therefore, 10.8 seconds of error budget have been consumed, which corresponds to option A.

Answer

7.2 seconds

Answer

2.4 seconds

Answer

4.8 seconds

Question 13

You need to create an alerting policy in Cloud Monitoring for a custom metric. Which THREE components must be defined? (Select 3)

Accepted Answer

Conditions. An alerting policy consists of conditions (which specify when to trigger), notification channels (how to notify), and documentation (optional but recommended). Duration is part of a condition.

Answer

Log sink

Answer

Dashboard

Question 14

Your Cloud SQL for PostgreSQL database is experiencing slow query performance. You want to identify and optimize the slowest queries. Which TWO actions should you take? (Choose two)

Accepted Answer

Enable the slow query log by setting the log_min_duration_statement flag.. To identify slow queries, enable the slow query log (via database flags) and use EXPLAIN ANALYZE to analyze query plans. Right-sizing the instance can help after identifying queries, but identifying them first requires logging and analysis. Connection pooling does not help identify slow queries.

Answer

Set up connection pooling using Cloud SQL Auth Proxy and PgBouncer.

Answer

Create read replicas to offload read traffic.

Answer

Increase the instance memory to the next tier.

Question 15

A DevOps engineer is setting up a GKE cluster for a batch processing job that can tolerate interruptions. The job runs for a few hours daily. To optimize cost, they want to use preemptible VMs. What must they configure to ensure the job completes despite node preemptions?

Accepted Answer

Set the cluster autoscaler min nodes low and max nodes high to allow replacement. To ensure the batch job completes despite node preemptions, the cluster autoscaler must be able to replace preempted nodes. Option D sets the minimum nodes low (to avoid unnecessary cost) and maximum nodes high (to allow scaling up when nodes are preempted). This allows the autoscaler to launch new preemptible nodes as replacements. The job itself must be fault-tolerant and handle restarts, but the autoscaler configuration is what enables node replacement. Option A disables autoscaling, preventing replacement. Option B is unrelated to node replacement. Option C prevents scaling, so preempted nodes cannot be replaced.

Answer

Disable cluster autoscaler to avoid node churn

Answer

Use a stateful workload with persistent volumes

Answer

Set the cluster autoscaler min and max nodes to the same value

Question 16

You have a Cloud Monitoring alerting policy that triggers when CPU usage exceeds 80% for 5 minutes. You want to add documentation to the alert that includes a link to a runbook and labels indicating the affected service. How can you achieve this?

Accepted Answer

Edit the alerting policy and add documentation with the runbook URL and labels under the 'Documentation' section.. Cloud Monitoring alerting policies support documentation fields where you can provide markdown text including links and labels. This is done when creating or editing the policy in the console or via API. Labels can be attached to the alert policy to help with filtering and routing.

Answer

Create a separate Cloud Storage bucket and reference it in the alert.

Answer

Use Cloud Logging to store runbook URLs and attach them to alerts via log-based metrics.

Answer

Use Cloud Monitoring's notification channel to include a link in the email body.

Question 17

A DevOps team needs to set up alerting for a critical application that runs on Compute Engine. They want to be notified if the application process crashes (i.e., stops sending heartbeats) for more than 5 minutes. The application emits a custom metric 'app_heartbeat' as a GAUGE with value 1 every 60 seconds. Which TWO configurations should they use? (Choose 2)

Accepted Answer

Duration: 5 minutes. To detect a crash, you need a metric absent condition (no data for 5 minutes) because the gauge value will stop reporting. Setting the duration to 5 minutes ensures timely notification. A threshold condition on the gauge value would not trigger if the value stays at 1. The alignment period and reducer are not relevant for absent conditions.

Answer

Alignment period: 60 seconds

Answer

Metric threshold condition: threshold < 1

Answer

Reducer: MEAN

Question 18

You are setting up structured logging for an application running on Compute Engine. Your logs should include trace context and severity. Which TWO fields should you include in the JSON payload to enable correlation with Cloud Trace? (Select 2)

Accepted Answer

spanId. To correlate logs with traces, you include the trace field (trace ID) and optionally spanId. The severity field is for log level, not correlation.

Answer

httpRequest

Answer

message

Answer

severity

Question 19

Your team has an alerting policy that fires frequently but the on-call engineer has difficulty understanding the impact. You want to add contextual information such as a runbook URL and severity label. What should you do?

Accepted Answer

Edit the alert policy documentation field to include a runbook URL and labels. Alert policy documentation allows you to add plain text, including markdown, which can contain links to runbooks and other info. You can also add labels to the policy. Adding labels to the metric or using notification channel descriptions does not attach documentation to the alert.

Answer

Set a description on the notification channel

Answer

Create a separate alert policy for each severity level

Answer

Add labels to the metric descriptor used in the condition

Question 20

Your application runs on Google Kubernetes Engine (GKE) and emits traces using the OpenTelemetry SDK. You want to export these traces to Cloud Trace. Which configuration is required?

Accepted Answer

Configure the OpenTelemetry SDK to use the Google Cloud Trace exporter and set the GOOGLE_CLOUD_PROJECT environment variable.. To export OpenTelemetry traces to Cloud Trace, you need to configure the OpenTelemetry exporter to use the Google Cloud Trace exporter, and set the GCP project ID.

Answer

Use the Cloud Monitoring API to ingest traces directly.

Answer

Deploy the Cloud Trace agent as a DaemonSet on your GKE cluster.

Answer

Set up a Pub/Sub topic and subscription to forward traces to Cloud Trace.