PCDOE Applying site reliability engineering practices Practice Test 6 — 15 Questions

Question 1

Your SRE team is defining service level objectives (SLOs) for a new payment processing API. The product team wants to ensure that the API is highly reliable, but you need to balance reliability with feature velocity. Which SLO definition is most appropriate?

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

Accepted Answer

99.99% of requests complete successfully within 200 ms, measured over a 28-day rolling window.. A well-defined SLO should be achievable, measurable, and include a target, a time window, and a performance threshold. The option that specifies 99.99% success within 200 ms over 28 days provides a clear reliability target that aligns with user expectations and allows for an error budget to drive release decisions. It balances reliability and feature velocity by defining an acceptable failure rate.

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The API must have zero downtime at all times, with no planned maintenance windows.

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All requests must be processed within 100 ms, with 100% availability.

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99.9% of requests complete successfully within 500 ms, measured over a 7-day window.

Question 2

You are an SRE for a global gaming platform that uses Google Kubernetes Engine (GKE). The platform experiences a sudden spike in traffic during a new game launch. Your team wants to ensure that the service remains available and that the error budget is not exhausted. You have defined an SLO of 99.9% availability over a 30-day window. Which of the following actions should you take first to align with SRE best practices?

Accepted Answer

Check the current error budget burn rate and, if it is high, freeze non-critical changes and focus on reliability improvements.. According to SRE principles, the error budget is a key decision-making tool. When the burn rate is high, it indicates that the service is consuming the budget quickly, and the team should prioritize reliability over new features. Checking the burn rate first informs whether to take action such as scaling or freezing changes. This approach ensures that reliability is maintained without unnecessarily halting all work or ignoring the budget.

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Immediately scale up the GKE cluster nodes and pods to handle the traffic, regardless of the error budget.

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Increase the SLO target to 99.99% to ensure higher reliability during the launch.

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Disable the SLO monitoring to prevent alerts from firing during the traffic spike, then scale the cluster.

Question 3

An SRE team wants to reduce alert noise by ensuring alerts are actionable and routed to the correct on-call rotation. They are using Cloud Monitoring with alerting policies. Which configuration should they implement?

Accepted Answer

Create alerting policies with conditions based on symptoms, such as high error rate or latency, and use notification channels that target the appropriate on-call team via email and SMS.. Symptom-based alerts, such as those monitoring error rates or latency, directly reflect user experience and are actionable. Routing them to the correct on-call team through appropriate notification channels ensures rapid response. The other options either generate excessive noise, use unreliable triggers, or suppress alerts in ways that risk missing critical incidents.

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Create alerting policies for every possible metric deviation, such as CPU usage above 60%, and send all alerts to a single distribution list.

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Create alerting policies that trigger only when multiple metrics exceed thresholds simultaneously, and disable notifications during business hours to reduce interruptions.

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Create alerting policies based on log entries containing the word 'error' and use a webhook to create tickets in a ticketing system for all alerts.

Question 4

An SRE team is setting up an alerting policy in Cloud Monitoring for a critical service. They want to be notified when the service's error rate exceeds 1% for at least 5 minutes. They also want to avoid alerting on transient spikes. Which alerting policy configuration should they use?

Accepted Answer

Create an alerting policy with a condition that triggers when the error rate metric exceeds 1% for a duration of 5 minutes, using a rolling window.. An effective alerting policy should balance sensitivity and specificity. The scenario requires alerting when the error rate exceeds 1% for at least 5 minutes, which implies a duration condition. Configuring the policy to trigger only when the condition persists for 5 minutes using a rolling window filters out transient spikes and ensures the alert is actionable, reducing noise while still detecting sustained issues promptly.

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Create an alerting policy that triggers immediately when the error rate metric exceeds 1%, without any duration.

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Create an alerting policy that triggers when the error rate metric exceeds 1% for 1 minute, using a 1-minute alignment period.

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Create an alerting policy that triggers when the error rate metric exceeds 1% for 10 minutes, using a 10-minute alignment period.

Question 5

Your team is adopting SRE practices and wants to implement a robust incident management process. Which two practices should you adopt to ensure effective incident response and learning? (Choose two.)

Accepted Answer

Conduct blameless postmortems after every incident to identify root causes and preventive actions.. The two practices that ensure effective incident response and learning are defining clear incident command roles and conducting blameless postmortems. Clear roles streamline coordination and communication during high-pressure situations, while blameless postmortems uncover systemic causes and drive preventive actions. Together, they form a foundation for reliable incident management and continuous improvement, as advocated by Google SRE.

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Implement strict change management with multiple approval layers to prevent unauthorized changes.

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Avoid documenting incident details to prevent information overload and focus on resolution.

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Ensure that only senior engineers are on-call to handle incidents, as they have the most experience.

Question 6

Your team is implementing a new monitoring strategy for a critical service on Google Cloud. You want to create an alert that notifies the on-call engineer only when the service's latency is consistently above the SLO threshold for at least 10 minutes, to avoid false positives. Which Cloud Monitoring alerting policy configuration should you use?

Accepted Answer

Create an alerting policy with a condition that triggers when the latency metric exceeds the threshold for a duration of 10 minutes.. Cloud Monitoring alerting policies allow you to specify a duration for which the condition must be met before the alert fires. This is known as the 'for' duration. By setting it to 10 minutes, you ensure that only sustained latency above the threshold triggers an alert, filtering out brief spikes. This directly addresses the need to avoid false positives from transient latency increases.

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Create an alerting policy with a condition that triggers immediately when latency exceeds the threshold, and then use a notification channel with a 10-minute delay.

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Use an uptime check with a 10-minute timeout to monitor the service latency, and configure the check to alert if it times out.

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Create a log-based metric that counts the number of requests exceeding the latency threshold, and set an alert if the count is greater than zero over a 10-minute window.

Question 7

A service has an SLO of 99.9% availability over a 30-day window. The error budget is 43.2 minutes. The service has already consumed 40 minutes of the error budget due to recent outages. A new feature deployment is planned. According to SRE best practices, what should the team do?

Accepted Answer

Deploy the new feature using a canary release and closely monitor the error rate, rolling back if the error budget is further consumed.. When the error budget is nearly exhausted, the team should take a cautious approach. A canary release allows testing the new feature on a small subset of users, with close monitoring and quick rollback if issues arise. This respects the error budget while still enabling progress. Halting all changes or proceeding blindly are extremes that do not align with SRE best practices.

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Halt all changes to the service until the error budget is replenished in the next 30-day window.

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Proceed with the deployment as planned, because the error budget is not yet fully exhausted.

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Increase the SLO to 99.95% to allow more error budget for the deployment.

Question 8

You are an SRE for a high-traffic e-commerce platform running on Google Kubernetes Engine (GKE). The platform experiences a sudden surge in traffic during a flash sale. To maintain reliability, you must implement an SRE practice that automatically adjusts resources based on demand while preserving the error budget. Which approach best meets these requirements?

Accepted Answer

Configure Horizontal Pod Autoscaler (HPA) with custom metrics based on request latency and CPU utilization, and set appropriate min and max replicas.. To handle sudden traffic surges while preserving the error budget, the platform needs automatic, demand-driven scaling. Horizontal Pod Autoscaler with custom metrics such as request latency and CPU utilization enables responsive scaling that aligns with actual user experience. Setting min and max replicas ensures availability and cost control. This approach maintains reliability by preventing resource exhaustion and keeping latency within SLO thresholds.

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Manually increase the number of replicas in the deployment to a fixed higher number before the sale begins.

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Use Vertical Pod Autoscaler (VPA) to automatically increase the CPU and memory requests of existing pods during the surge.

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Set up a Cluster Autoscaler to add nodes when pods are pending, and rely on the default HPA configuration based on CPU only.

Question 9

You are an SRE at a fintech company using Google Cloud. A recent incident caused a 45-minute outage of a payment processing service. The postmortem team is analyzing the incident and wants to ensure that the action items are effective. According to Google SRE best practices, which two of the following are key characteristics of effective postmortem action items? (Choose two.)

Accepted Answer

They are assigned to specific individuals with clear deadlines.. Effective postmortem action items are specific, assigned to owners with deadlines, and address both prevention and detection. Blamelessness is fundamental, and action items should not be vague. They are created for any incident that provides learning opportunities, not only when the error budget is exceeded. These characteristics ensure that the postmortem leads to real improvements in reliability.

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They are only created for incidents that exceed the error budget.

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They focus on blaming the individual who caused the outage.

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They are kept vague to allow flexibility in implementation.

Question 10

You are an SRE for a service that uses a 99.9% availability SLO over a 30-day window. The service has consumed 100% of its error budget with 10 days remaining in the window. According to Google SRE best practices, what should you do?

Accepted Answer

Halt all changes that could impact reliability and focus on reliability improvements, while allowing low-risk changes with approvals.. The correct action is to halt risky changes and focus on reliability improvements, while permitting low-risk changes that enhance reliability. This aligns with the error budget policy: when the budget is exhausted, the team must prioritize reliability over new features. It is not a complete freeze; critical fixes and reliability enhancements can proceed with oversight. This approach protects users and allows the team to recover budget in the next window.

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Increase the SLO target to 99.95% to allow more error budget.

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Freeze all changes to the service until the next SLO window begins.

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Ignore the error budget exhaustion because there are still 10 days left in the window.

Question 11

An SRE team is conducting a postmortem for a recent outage. They want to follow Google SRE best practices for blameless postmortems. Which two actions should they take? (Choose two.)

Accepted Answer

Document the incident timeline, impact, and action items in a shared postmortem document.. Blameless postmortems focus on learning from incidents without assigning blame. Two key actions are identifying systemic causes and documenting the incident thoroughly. These practices encourage transparency, help prevent recurrence by addressing root causes, and share knowledge across the organization. They align with Google SRE principles of continuous improvement and psychological safety.

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Immediately implement punitive measures for the team responsible for the outage.

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Keep the postmortem findings confidential to avoid reputational damage.

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Assign blame to the engineer who deployed the faulty change to ensure accountability.

Question 12

An SRE team is implementing a postmortem process for a recent outage. They want to ensure the postmortem is blameless and focuses on systemic improvements. Which TWO practices should they follow? (Choose two.)

Accepted Answer

Document the timeline of events, including what was known and decided at each step, to understand how the incident unfolded.. Blameless postmortems focus on systemic analysis and learning. Documenting a timeline provides a factual basis, and identifying contributing causes leads to systemic improvements. Assigning blame, limiting participation, or focusing on individual accountability undermines the blameless culture and reduces the effectiveness of the postmortem.

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Ensure the postmortem includes a section for assigning blame to the responsible party to hold them accountable.

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Limit the postmortem to the immediate team involved to keep the discussion focused and avoid outside interference.

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Focus on identifying the root cause and assigning action items to the individual who made the change that triggered the outage.

Question 13

You are an SRE for a service running on Google Kubernetes Engine (GKE). You want to implement a canary deployment strategy to reduce risk when releasing a new version. You have deployed a canary version alongside the stable version. Which approach should you use to route a small percentage of traffic to the canary and monitor its performance before full rollout?

Accepted Answer

Use Istio to configure a VirtualService with weighted routing, sending 5% of traffic to the canary and 95% to the stable version.. The correct approach is to use Istio's VirtualService with weighted routing to send a small percentage of traffic to the canary. This allows you to monitor the canary's performance and gradually increase traffic if it is healthy. Istio provides the necessary traffic management and observability. Other options do not provide controlled traffic splitting or are not designed for canary deployments.

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Use a Horizontal Pod Autoscaler to scale the canary based on CPU usage, thereby controlling traffic.

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Use a NetworkPolicy to allow only a subset of source IPs to reach the canary.

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Use Kubernetes Service with session affinity to direct a fixed set of users to the canary.

Question 14

You are a DevOps engineer at a retail company that uses Google Cloud. The SRE team wants to reduce toil by automating the response to a common alert: 'CPU utilization on instance group X exceeds 80% for 5 minutes.' Which Google Cloud tool should you use to automatically resize the instance group based on this metric?

Accepted Answer

Compute Engine autoscaling policy based on CPU utilization.. Compute Engine autoscaling policies are designed to automatically adjust the number of instances in an instance group based on metrics such as CPU utilization. This is a fully managed feature that eliminates the need for custom automation. By configuring an autoscaling policy with a target CPU utilization, the instance group will scale out when CPU exceeds the threshold and scale in when it drops, directly addressing the requirement to reduce toil.

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Cloud Load Balancing with a custom health check that triggers instance group resizing.

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Cloud Scheduler job that runs a script every 5 minutes to check CPU and resize if needed.

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Cloud Monitoring alerting policy with a webhook to a Cloud Function that calls the Compute Engine API to resize the instance group.

Question 15

You are an SRE for a microservices-based application on Google Cloud. The team wants to reduce toil by automating the deployment and rollback of services. They decide to implement a canary release strategy. Which Google Cloud tool or feature is most suitable for automating canary deployments with automatic rollback based on SLO violations?

Accepted Answer

Cloud Deploy with canary deployment strategy and automated rollback based on Cloud Monitoring metrics.. Cloud Deploy is a Google Cloud service designed to automate deployments to GKE, Cloud Run, and Anthos. It supports canary deployment strategies and can be configured to automatically roll back if certain metrics, such as error rate or latency, exceed thresholds defined in Cloud Monitoring. This makes it the most suitable tool for automating canary releases with automatic rollback based on SLO violations, reducing toil and improving reliability.

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Cloud Build with a custom script that deploys to a canary and manually checks metrics before promoting.

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GKE with Istio service mesh and Flagger for canary deployments and automated rollback.

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Terraform with a canary module and a CI/CD pipeline that triggers rollback via Cloud Functions.