You are writing a postmortem for an incident that severely affected users. You want to prevent similar incidents in the future. Which two of the following sections should you include in the postmortem? (Choose two.)

An explanation of the root cause of the incident

A list of action items to prevent a recurrence of the incident

An explanation of the root cause of the incident

A list of employees responsible for causing the incident

A list of action items to prevent a recurrence of the incident

Your opinion of the incident's severity compared to past incidents

Copies of the design documents for all the services impacted by the incident

You are ready to deploy a new feature of a web-based application to production. You want to use Google Kubernetes Engine (GKE) to perform a phased rollout to half of the web server pods.What should you do?

Use a partitioned rolling update.

Use Node taints with NoExecute.

Use a replica set in the deployment specification.

Use a stateful set with parallel pod management policy.

You are responsible for the reliability of a high-volume enterprise application. A large number of users report that an important subset of the application's functionality -- a data intensive reporting feature -- is consistently failing with an HTTP 500 error. When you investigate your application's dashboards, you notice a strong correlation between the failures and a metric that represents the size of an internal queue used for generating reports. You trace the failures to a reporting backend that is experiencing high I/O wait times. You quickly fix the issue by resizing the backend's persistent disk (PD). How you need to create an availability Service Level Indicator (SLI) for the report generation feature. How would you define it?

As the proportion of report generation requests that result in a successful response

As the I/O wait times aggregated across all report generation backends

As the proportion of report generation requests that result in a successful response

As the application's report generation queue size compared to a known-good threshold

As the reporting backend PD throughout capacity compared to a known-good threshold

You have an application running in Google Kubernetes Engine. The application invokes multiple services per request but responds too slowly. You need to identify which downstream service or services are causing the delay. What should you do?

Create a Dataflow pipeline to analyze service metrics in real time.

Analyze VPC flow logs along the path of the request.

Investigate the Liveness and Readiness probes for each service.

Create a Dataflow pipeline to analyze service metrics in real time.

Use a distributed tracing framework such as OpenTelemetry or Stackdriver Trace.

You are creating and assigning action items in a postmodern for an outage. The outage is over, but you need to address the root causes. You want to ensure that your team handles the action items quickly and efficiently. How should you assign owners and collaborators to action items?

Assign one owner for each action item and any necessary collaborators.

Assign multiple owners for each item to guarantee that the team addresses items quickly

Assign collaborators but no individual owners to the items to keep the postmortem blameless.

Assign the team lead as the owner for all action items because they are in charge of the SRE team.

Your development team has created a new version of their service's API. You need to deploy the new versions of the API with the least disruption to third-party developers and end users of third-party installed applications. What should you do?

Introduce the new version of the API. Announce deprecation of the old version of the API. Deprecate the old version of the API. Contact remaining users of the old API. Provide best effort support to users of the old API. Turn down the old version of the API.

Announce deprecation of the old version of the API. Introduce the new version of the API. Contact remaining users on the old API. Deprecate the old version of the API. Turn down the old version of the API. Provide best effort support to users of the old API.

Announce deprecation of the old version of the API. Contact remaining users on the old API. Introduce the new version of the API. Deprecate the old version of the API. Provide best effort support to users of the old API. Turn down the old version of the API.

Introduce the new version of the API. Contact remaining users of the old API. Announce deprecation of the old version of the API. Deprecate the old version of the API. Turn down the old version of the API. Provide best effort support to users of the old API.

You are running an application on Compute Engine and collecting logs through Stackdriver. You discover that some personally identifiable information (PII) is leaking into certain log entry fields. You want to prevent these fields from being written in new log entries as quickly as possible. What should you do?

Use the filter-record-transformer Fluentd filter plugin to remove the fields from the log entries in flight.

Use the fluent-plugin-record-reformer Fluentd output plugin to remove the fields from the log entries in flight.

Wait for the application developers to patch the application, and then verify that the log entries are no longer exposing PII.

Stage log entries to Cloud Storage, and then trigger a Cloud Function to remove the fields and write the entries to Stackdriver via the Stackdriver Logging API.

You support a service that recently had an outage. The outage was caused by a new release that exhausted the service memory resources. You rolled back the release successfully to mitigate the impact on users. You are now in charge of the post-mortem for the outage. You want to follow Site Reliability Engineering practices when developing the post-mortem. What should you do?

Focus on identifying the contributing causes of the incident rather than the individual responsible for the cause.

Focus on developing new features rather than avoiding the outages from recurring.

Focus on identifying the contributing causes of the incident rather than the individual responsible for the cause.

Plan individual meetings with all the engineers involved. Determine who approved and pushed the new release to production.

Use the Git history to find the related code commit. Prevent the engineer who made that commit from working on production services.

You support a user-facing web application. When analyzing the application's error budget over the previous six months, you notice that the application has never consumed more than 5% of its error budget in any given time window. You hold a Service Level Objective (SLO) review with business stakeholders and confirm that the SLO is set appropriately. You want your application's SLO to more closely reflect its observed reliability. What steps can you take to further that goal while balancing velocity, reliability, and business needs? (Choose two.)

Implement and measure additional Service Level Indicators (SLIs) fro the application.

Announce planned downtime to consume more error budget, and ensure that users are not depending on a tighter SLO.

Add more serving capacity to all of your application's zones.

Have more frequent or potentially risky application releases.

Tighten the SLO match the application's observed reliability.

Implement and measure additional Service Level Indicators (SLIs) fro the application.

Announce planned downtime to consume more error budget, and ensure that users are not depending on a tighter SLO.

You support a service with a well-defined Service Level Objective (SLO). Over the previous 6 months, your service has consistently met its SLO and customer satisfaction has been consistently high. Most of your service's operations tasks are automated and few repetitive tasks occur frequently. You want to optimize the balance between reliability and deployment velocity while following site reliability engineering best practices. What should you do? (Choose two.)

Increase the service's deployment velocity and/or risk.

Shift engineering time to other services that need more reliability.

Make the service's SLO more strict.

Increase the service's deployment velocity and/or risk.

Shift engineering time to other services that need more reliability.

Get the product team to prioritize reliability work over new features.

Change the implementation of your Service Level Indicators (SLIs) to increase coverage.

Your organization uses a change advisory board (CAB) to approve all changes to an existing service You want to revise this process to eliminate any negative impact on the software delivery performance What should you do?Choose 2 answers

Move to a peer-review based process for individual changes that is enforced at code check-in time and supported by automated tests

Ensure that the team's development platform enables developers to get fast feedback on the impact of their changes

Replace the CAB with a senior manager to ensure continuous oversight from development to deployment

Let developers merge their own changes but ensure that the team's deployment platform can roll back changes if any issues are discovered

Move to a peer-review based process for individual changes that is enforced at code check-in time and supported by automated tests

Batch changes into larger but less frequent software releases

Ensure that the team's development platform enables developers to get fast feedback on the impact of their changes

Your organization has a containerized web application that runs on-premises As part of the migration plan to Google Cloud you need to select a deployment strategy and platform that meets the following acceptance criteria1 The platform must be able to direct traffic from Android devices to an Android-specific microservice2 The platform must allow for arbitrary percentage-based traffic splitting3 The deployment strategy must allow for continuous testing of multiple versions of any microserviceWhat should you do?

Deploy the canary release to Google Kubernetes Engine with Anthos Sen/ice Mesh Use traffic splitting to direct 10% of user traffic to the new version based on the user-agent header configured in the virtual service

Deploy the canary release of the application to Cloud Run Use traffic splitting to direct 10% of user traffic to the canary release based on the revision tag

Deploy the canary release of the application to App Engine Use traffic splitting to direct a subset of user traffic to the new version based on the IP address

Deploy the canary release of the application to Compute Engine Use Anthos Service Mesh with Compute Engine to direct 10% of user traffic to the canary release by configuring the virtual service.

Deploy the canary release to Google Kubernetes Engine with Anthos Sen/ice Mesh Use traffic splitting to direct 10% of user traffic to the new version based on the user-agent header configured in the virtual service

Your team is running microservices in Google Kubernetes Engine (GKE) You want to detect consumption of an error budget to protect customers and define release policies What should you do?

Create a SLO Create an Alert Policy on select_slo_bum_rate

Create SLIs from metrics Enable Alert Policies if the services do not pass

Use the metrics from Anthos Service Mesh to measure the health of the microservices

Create a SLO Create an Alert Policy on select_slo_bum_rate

Create a SLO and configure uptime checks for your services Enable Alert Policies if the services do not pass

Your organization wants to collect system logs that will be used to generate dashboards in Cloud Operations for their Google Cloud project. You need to configure all current and future Compute Engine instances to collect the system logs and you must ensure that the Ops Agent remains up to date. What should you do?

Use the gcloud CLI to create an Agent Policy.

Use the gcloud CLI to install the Ops Agent on each VM listed in the Cloud Asset Inventory

Select all VMs with an Agent status of Not detected on the Cloud Operations VMs dashboard Then select Install agents

Use the gcloud CLI to create an Agent Policy.

Install the Ops Agent on the Compute Engine image by using a startup script

Your company has a Google Cloud resource hierarchy with folders for production test and development Your cyber security team needs to review your company's Google Cloud security posture to accelerate security issue identification and resolution You need to centralize the logs generated by Google Cloud services from all projects only inside your production folder to allow for alerting and near-real time analysis. What should you do?

Create an aggregated log sink associated with the production folder that uses a Cloud Logging bucket as the destination

Enable the Workflows API and route all the logs to Cloud Logging

Create a central Cloud Monitoring workspace and attach all related projects

Create an aggregated log sink associated with the production folder that uses a Pub Sub topic as the destination

Create an aggregated log sink associated with the production folder that uses a Cloud Logging bucket as the destination

You are configuring the frontend tier of an application deployed in Google Cloud The frontend tier is hosted in ngmx and deployed using a managed instance group with an Envoy-based external HTTP(S) load balancer in front The application is deployed entirely within the europe-west2 region: and only serves users based in the United Kingdom. You need to choose the most cost-effective network tier and load balancing configuration What should you use?

Premium Tier with a regional load balancer

Premium Tier with a global load balancer

Premium Tier with a regional load balancer

Standard Tier with a global load balancer

Standard Tier with a regional load balancer

You recently deployed your application in Google Kubernetes Engine (GKE) and now need to release a new version of the application You need the ability to instantly roll back to the previous version of the application in case there are issues with the new version Which deployment model should you use?

Perform a blue/green deployment and test your new application after the deployment is complete

Perform a rolling deployment and test your new application after the deployment is complete

Perform A. B testing, and test your application periodically after the deployment is complete

Perform a canary deployment, and test your new application periodically after the new version is deployed

Perform a blue/green deployment and test your new application after the deployment is complete

You are building and deploying a microservice on Cloud Run for your organization Your service is used by many applications internally You are deploying a new release, and you need to test the new version extensively in the staging and production environments You must minimize user and developer impact. What should you do?

Deploy the new version of the service to the staging environment with a new-release tag without serving traffic Test the new-release version If the test passes; gradually roll out this tagged version Repeat for the production environment

Deploy the new version of the service to the staging environment Split the traffic, and allow 1 % of traffic through to the latest version Test the latest version If the test passes gradually roll out the latest version to the staging and production environments

Deploy the new version of the service to the staging environment Split the traffic, and allow 50% of traffic through to the latest version Test the latest version If the test passes, send all traffic to the latest version Repeat for the production environment

Deploy the new version of the service to the staging environment with a new-release tag without serving traffic Test the new-release version If the test passes; gradually roll out this tagged version Repeat for the production environment

Deploy a new environment with the green tag to use as the staging environment Deploy the new version of the service to the green environment and test the new version If the tests pass, send all traffic to the green environment and delete the existing staging environment Repeat for the production environment

You work for a global organization and run a service with an availability target of 99% with limited engineering resources. For the current calendar month you noticed that the service has 99 5% availability. You must ensure that your service meets the defined availability goals and can react to business changes including the upcoming launch of new features You also need to reduce technical debt while minimizing operational costs You want to follow Google-recommended practices What should you do?

Define an error budget for your service level availability and minimize the remaining error budget

Add N+1 redundancy to your service by adding additional compute resources to the service

Identify, measure and eliminate toil by automating repetitive tasks

Define an error budget for your service level availability and minimize the remaining error budget

Allocate available engineers to the feature backlog while you ensure that the sen/ice remains within the availability target

You are developing the deployment and testing strategies for your CI/CD pipeline in Google Cloud You must be able to* Reduce the complexity of release deployments and minimize the duration of deployment rollbacks* Test real production traffic with a gradual increase in the number of affected usersYou want to select a deployment and testing strategy that meets your requirements What should you do?

Blue/green deployment and canary testing

Recreate deployment and canary testing

Blue/green deployment and canary testing

Rolling update deployment and A/B testing

Rolling update deployment and shadow testing

You support a user-facing web application When analyzing the application's error budget over the previous six months you notice that the application never consumed more than 5% of its error budget You hold a SLO review with business stakeholders and confirm that the SLO is set appropriately You want your application's reliability to more closely reflect its SLO What steps can you take to further that goal while balancing velocity, reliability, and business needs?Choose 2 answers

Have more frequent or potentially risky application releases

Tighten the SLO to match the application's observed reliability

Add more serving capacity to all of your application's zones

Implement and measure all other available SLIs for the application

Announce planned downtime to consume more error budget and ensure that users are not depending on a tighter SLO

Have more frequent or potentially risky application releases

Tighten the SLO to match the application's observed reliability

Your company runs an ecommerce website built with JVM-based applications and microservice architecture in Google Kubernetes Engine (GKE) The application load increases during the day and decreases during the night Your operations team has configured the application to run enough Pods to handle the evening peak load You want to automate scaling by only running enough Pods and nodes for the load What should you do?

Configure the Horizontal Pod Autoscaler and enable the cluster autoscaler

Configure the Vertical Pod Autoscaler but keep the node pool size static

Configure the Vertical Pod Autoscaler and enable the cluster autoscaler

Configure the Horizontal Pod Autoscaler but keep the node pool size static

Configure the Horizontal Pod Autoscaler and enable the cluster autoscaler

Your organization wants to increase the availability target of an application from 99 9% to 99 99% for an investment of $2 000 The application's current revenue is S1,000,000 You need to determine whether the increase in availability is worth the investment for a single year of usage What should you do?

Calculate the value of improved availability to be $900, and determine that the increase in availability is not worth the investment

Calculate the value of improved availability to be $1 000 and determine that the increase in availability is not worth the investment

Calculate the value of improved availability to be $1 000 and determine that the increase in availability is worth the investment

Calculate the value of improved availability to be $9,000. and determine that the increase in availability is worth the investment

A third-party application needs to have a service account key to work properly When you try to export the key from your cloud project you receive an error 'The organization policy constraint larn.disableServiceAccountKeyCreation is enforcedM You need to make the third-party application work while following Google-recommended security practices What should you do?

Add a rule to set the iam.disableServiceAccountKeyCreation policy to off in your project and create a key.

Enable the default service account key. and download the key

Remove the iam.disableServiceAccountKeyCreation policy at the organization level, and create a key.

Disable the service account key creation policy at the project's folder, and download the default key

Add a rule to set the iam.disableServiceAccountKeyCreation policy to off in your project and create a key.

Your team is writing a postmortem after an incident on your external facing application Your team wants to improve the postmortem policy to include triggers that indicate whether an incident requires a postmortem Based on Site Reliability Engineenng (SRE) practices, what triggers should be defined in the postmortem policy?Choose 2 answers

An external stakeholder asks for a postmortem

An internal stakeholder requests a postmortem

An external stakeholder asks for a postmortem

Data is lost due to an incident

An internal stakeholder requests a postmortem

The monitoring system detects that one of the instances for your application has failed

The CD pipeline detects an issue and rolls back a problematic release.

You are implementing a CI'CD pipeline for your application in your company s multi-cloud environment Your application is deployed by using custom Compute Engine images and the equivalent in other cloud providers You need to implement a solution that will enable you to build and deploy the images to your current environment and is adaptable to future changes Which solution stack should you use'?

Cloud Build with Google Cloud Deploy

Google Kubernetes Engine with Google Cloud Deploy

Your applications performance in Google Cloud has degraded since the last release You suspect that downstream dependencies might be causing some requests to take longer to complete You need to investigate the issue with your application to determine the cause What should you do?

Configure Cloud Trace in your application

Configure Error Reporting in your application

Configure Google Cloud Managed Service for Prometheus in your application

Configure Cloud Profiler in your application

Configure Cloud Trace in your application

You are creating a CI/CD pipeline in Cloud Build to build an application container image The application code is stored in GitHub Your company requires thai production image builds are only run against the main branch and that the change control team approves all pushes to the main branch You want the image build to be as automated as possible What should you do?Choose 2 answers

Create a trigger on the Cloud Build job Set the repository event setting to Push to a branch

Configure a branch protection rule for the main branch on the repository

Create a trigger on the Cloud Build job Set the repository event setting to Pull request'

Add the owners file to the Included files filter on the trigger

Create a trigger on the Cloud Build job Set the repository event setting to Push to a branch

Configure a branch protection rule for the main branch on the repository

Enable the Approval option on the trigger

You built a serverless application by using Cloud Run and deployed the application to your production environment You want to identify the resource utilization of the application for cost optimization What should you do?

Use Cloud Trace with distributed tracing to monitor the resource utilization of the application

Use Cloud Profiler with Ops Agent to monitor the CPU and memory utilization of the application

Use Cloud Monitoring to monitor the container CPU and memory utilization of the application

Use Cloud Ops to create logs-based metrics to monitor the resource utilization of the application

Your company is using HTTPS requests to trigger a public Cloud Run-hosted service accessible at the https://booking-engine-abcdef .a.run.app URL You need to give developers the ability to test the latest revisions of the service before the service is exposed to customers What should you do?

Runthegcioud run services update-traffic booking-engine ---to-revisions LATEST*! command Use the ht tps: //booking-engine-abcdef. a. run. ape URL for testing

Runthegcioud run deploy booking-engine ---no-traffic ----ag dev command Use the https://dev----booking-engine-abcdef. a. run. app URL for testing

Runthegcioud run services update-traffic booking-engine ---to-revisions LATEST*! command Use the ht tps: //booking-engine-abcdef. a. run. ape URL for testing

Pass the curl -K 'Authorization: Hearer S(gclcud auth print-identity-token)' auth token Use the https: / /booking-engine-abcdef. a. run. app URL to test privately

Grant the roles/run. invoker role to the developers testing the booking-engine service Use the https: //booking-engine-abcdef. private. run. app URL for testing

You are configuring connectivity across Google Kubernetes Engine (GKE) clusters in different VPCs You notice that the nodes in Cluster A are unable to access the nodes in Cluster B You suspect that the workload access issue is due to the network configuration You need to troubleshoot the issue but do not have execute access to workloads and nodes You want to identify the layer at which the network connectivity is broken What should you do?

Use Network Connectivity Center to perform a Connectivity Test from Cluster A to Cluster

Install a toolbox container on the node in Cluster A Confirm that the routes to Cluster B are configured appropriately

Use Network Connectivity Center to perform a Connectivity Test from Cluster A to Cluster

Use a debug container to run the traceroute command from Cluster A to Cluster B and from Cluster B to Cluster A Identify the common failure point

Enable VPC Flow Logs in both VPCs and monitor packet drops

You manage an application that runs in Google Kubernetes Engine (GKE) and uses the blue/green deployment methodology Extracts of the Kubernetes manifests are shown below The Deployment app-green was updated to use the new version of the application During post-deployment monitoring you notice that the majority of user requests are failing You did not observe this behavior in the testing environment You need to mitigate the incident impact on users and enable the developers to troubleshoot the issue What should you do?

Change the selector on the Service app-svc to app: my-app, version: blue

Update the Deployment app-blue to use the new version of the application

Update the Deployment ape-green to use the previous version of the application

Change the selector on the Service app-2vc to app: my-app.

Change the selector on the Service app-svc to app: my-app, version: blue

You are running a web application deployed to a Compute Engine managed instance group Ops Agent is installed on all instances You recently noticed suspicious activity from a specific IP address You need to configure Cloud Monitoring to view the number of requests from that specific IP address with minimal operational overhead. What should you do?

Configure the Ops Agent with a logging receiver Create a logs-based metric

Create a script to scrape the web server log Export the IP address request metrics to the Cloud Monitoring API

Update the application to export the IP address request metrics to the Cloud Monitoring API

Configure the Ops Agent with a metrics receiver

As part of your company's initiative to shift left on security, the infoSec team is asking all teams to implement guard rails on all the Google Kubernetes Engine (GKE) clusters to only allow the deployment of trusted and approved images You need to determine how to satisfy the InfoSec teams goal of shifting left on security. What should you do?

Use Binary Authorization to attest images during your CI CD pipeline

Deploy Falco or Twistlock on GKE to monitor for vulnerabilities on your running Pods

Configure Identity and Access Management (1AM) policies to create a least privilege model on your GKE clusters

Use Binary Authorization to attest images during your CI CD pipeline

Enable Container Analysis in Artifact Registry, and check for common vulnerabilities and exposures (CVEs) in your container images

You have an application that runs in Google Kubernetes Engine (GKE). The application consists of several microservices that are deployed to GKE by using Deployments and Services One of the microservices is experiencing an issue where a Pod returns 403 errors after the Pod has been running for more than five hours Your development team is working on a solution but the issue will not be resolved for a month You need to ensure continued operations until the microservice is fixed You want to follow Google-recommended practices and use the fewest number of steps What should you do?

Add a HTTP liveness probe to the microservice s deployment

Create a cron job to terminate any Pods that have been running for more than five hours

Add a HTTP liveness probe to the microservice s deployment

Monitor the Pods and terminate any Pods that have been running for more than five hours

Configure an alert to notify you whenever a Pod returns 403 errors

You want to share a Cloud Monitoring custom dashboard with a partner team What should you do?

Provide the partner team with the dashboard URL to enable the partner team to create a copy of the dashboard

Export the metrics to BigQuery Use Looker Studio to create a dashboard, and share the dashboard with the partner team

Copy the Monitoring Query Language (MQL) query from the dashboard; and send the MQL query to the partner team

Download the JSON definition of the dashboard, and send the JSON file to the partner team

You are building an application that runs on Cloud Run The application needs to access a third-party API by using an API key You need to determine a secure way to store and use the API key in your application by following Google-recommended practices What should you do?

Save the API key in Secret Manager as a secret Reference the secret as an environment variable in the Cloud Run application

Save the API key in Secret Manager as a secret key Mount the secret key under the /sys/api_key directory and decrypt the key in the Cloud Run application

Save the API key in Cloud Key Management Service (Cloud KMS) as a key Reference the key as an environment variable in the Cloud Run application

Encrypt the API key by using Cloud Key Management Service (Cloud KMS) and pass the key to Cloud Run as an environment variable Decrypt and use the key in Cloud Run

You are currently planning how to display Cloud Monitoring metrics for your organization's Google Cloud projects. Your organization has three folders and six projects: You want to configure Cloud Monitoring dashboards lo only display metrics from the projects within one folder You need to ensure that the dashboards do not display metrics from projects in the other folders You want to follow Google-recommended practices What should you do?

Create new scoping projects for each folder

Create a single new scoping project

Create new scoping projects for each folder

Use the current app-one-prod project as the scoping project

Use the current app-one-dev, app-one-staging and app-one-prod projects as the scoping project for each folder

Your company's security team needs to have read-only access to Data Access audit logs in the _Required bucket You want to provide your security team with the necessary permissions following the principle of least privilege and Google-recommended practices. What should you do?

Assign the roles/logging.privateLogviewer role to a group with all the security team members

Assign the roles/logging, viewer role to each member of the security team

Assign the roles/logging. viewer role to a group with all the security team members

Assign the roles/logging.privateLogViewer role to each member of the security team

Assign the roles/logging.privateLogviewer role to a group with all the security team members

Google Professional Cloud DevOps Engineer Practice Test 3

You support a popular mobile game application deployed on Google Kubernetes Engine (GKE) across several Google Cloud regions. Each region has multiple Kubernetes clusters. You receive a report that none of the users in a specific region can connect to the application. You want to resolve the incident while following Site Reliability Engineering practices. What should you do first?

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Google Professional Cloud DevOps Engineer Practice Test 3

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