Free 2024 Professional-Cloud-DevOps-Engineer Dumps 100 Pass Guarantee With Latest Demo [Q64-Q87]

Q64. 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 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

Q65. You support a high-traffic web application with a microservice architecture. The home page of the application displays multiple widgets containing content such as the current weather, stock prices, and news headlines. The main serving thread makes a call to a dedicated microservice for each widget and then lays out the homepage for the user. The microservices occasionally fail; when that happens, the serving thread serves the homepage with some missing content. Users of the application are unhappy if this degraded mode occurs too frequently, but they would rather have some content served instead of no content at all. You want to set a Service Level Objective (SLO) to ensure that the user experience does not degrade too much. What Service Level Indicator {SLI) should you use to measure this?

A quality SLI: the ratio of non-degraded responses to total responses

An availability SLI: the ratio of healthy microservices to the total number of microservices

A freshness SLI: the proportion of widgets that have been updated within the last 10 minutes

A latency SLI: the ratio of microservice calls that complete in under 100 ms to the total number of microservice calls

Q66. You use Spinnaker to deploy your application and have created a canary deployment stage in the pipeline. Your application has an in-memory cache that loads objects at start time. You want to automate the comparison of the canary version against the production version. How should you configure the canary analysis?

Compare the canary with a new deployment of the current production version.

Compare the canary with a new deployment of the previous production version.

Compare the canary with the existing deployment of the current production version.

Compare the canary with the average performance of a sliding window of previous production versions.

Q67. Your organization recently adopted a container-based workflow for application development. Your team develops numerous applications that are deployed continuously through an automated build pipeline to a Kubernetes cluster in the production environment. The security auditor is concerned that developers or operators could circumvent automated testing and push code changes to production without approval. What should you do to enforce approvals?

Configure the build system with protected branches that require pull request approval.

Use an Admission Controller to verify that incoming requests originate from approved sources.

Leverage Kubernetes Role-Based Access Control (RBAC) to restrict access to only approved users.

Enable binary authorization inside the Kubernetes cluster and configure the build pipeline as an attestor.

Q68. You are the Operations Lead for an ongoing incident with one of your services. The service usually runs at around 70% capacity. You notice that one node is returning 5xx errors for all requests. There has also been a noticeable increase in support cases from customers. You need to remove the offending node from the load balancer pool so that you can isolate and investigate the node. You want to follow Google-recommended practices to manage the incident and reduce the impact on users. What should you do?

1. Communicate your intent to the incident team.
2. Perform a load analysis to determine if the remaining nodes can handle the increase in traffic offloaded from the removed node, and scale appropriately.
3. When any new nodes report healthy, drain traffic from the unhealthy node, and remove the unhealthy node from service.

1. Communicate your intent to the incident team.
2. Add a new node to the pool, and wait for the new node to report as healthy.
3. When traffic is being served on the new node, drain traffic from the unhealthy node, and remove the old node from service.

1 . Drain traffic from the unhealthy node and remove the node from service.
2. Monitor traffic to ensure that the error is resolved and that the other nodes in the pool are handling the traffic appropriately.
3. Scale the pool as necessary to handle the new load.
4. Communicate your actions to the incident team.

1 . Drain traffic from the unhealthy node and remove the old node from service.
2. Add a new node to the pool, wait for the new node to report as healthy, and then serve traffic to the new node.
3. Monitor traffic to ensure that the pool is healthy and is handling traffic appropriately.
4. Communicate your actions to the incident team.

Q69. You are investigating issues in your production application that runs on Google Kubernetes Engine (GKE).
You determined that the source Of the issue is a recently updated container image, although the exact change in code was not identified. The deployment is currently pointing to the latest tag. You need to update your cluster to run a version of the container that functions as intended. What should you do?

Create a new tag called stable that points to the previously working container, and change the deployment to point to the new tag.

Apply the latest tag to the previous container image, and do a rolling update on the deployment.

Build a new container from a previous Git tag, and do a rolling update on the deployment to the new container.

Alter the deployment to point to the sha2 56 digest of the previously working container.

Q70. Your product is currently deployed in three Google Cloud Platform (GCP) zones with your users divided between the zones. You can fail over from one zone to another, but it causes a 10-minute service disruption for the affected users. You typically experience a database failure once per quarter and can detect it within five minutes. You are cataloging the reliability risks of a new real-time chat feature for your product. You catalog the following information for each risk:
* Mean Time to Detect (MUD} in minutes
* Mean Time to Repair (MTTR) in minutes
* Mean Time Between Failure (MTBF) in days
* User Impact Percentage
The chat feature requires a new database system that takes twice as long to successfully fail over between zones. You want to account for the risk of the new database failing in one zone. What would be the values for the risk of database failover with the new system?

MTTD: 5
MTTR: 10
MTBF: 90
Impact: 33%

MTTD:5
MTTR: 20
MTBF: 90
Impact: 33%

MTTD:5
MTTR: 10
MTBF: 90
Impact 50%

MTTD:5
MTTR: 20
MTBF: 90
Impact: 50%

Q71. You support a high-traffic web application and want to ensure that the home page loads in a timely manner. As a first step, you decide to implement a Service Level Indicator (SLI) to represent home page request latency with an acceptable page load time set to 100 ms. What is the Google-recommended way of calculating this SLI?

Buckelize Ihe request latencies into ranges, and then compute the percentile at 100 ms.

Bucketize the request latencies into ranges, and then compute the median and 90th percentiles.

Count the number of home page requests that load in under 100 ms, and then divide by the total number of home page requests.

Count the number of home page requests that load in under 100 ms. and then divide by the total number of all web application requests.

Q72. You support an e-commerce application that runs on a large Google Kubernetes Engine (GKE) cluster deployed on-premises and on Google Cloud Platform. The application consists of microservices that run in containers. You want to identify containers that are using the most CPU and memory. What should you do?

Use Stackdriver Kubernetes Engine Monitoring.

Use Prometheus to collect and aggregate logs per container, and then analyze the results in Grafana.

Use the Stackdriver Monitoring API to create custom metrics, and then organize your containers using groups.

Use Stackdriver Logging to export application logs to BigOuery. aggregate logs per container, and then analyze CPU and memory consumption.

Q73. You support a large service with a well-defined Service Level Objective (SLO). The development team deploys new releases of the service multiple times a week. If a major incident causes the service to miss its SLO, you want the development team to shift its focus from working on features to improving service reliability. What should you do before a major incident occurs?

Develop an appropriate error budget policy in cooperation with all service stakeholders.

Negotiate with the product team to always prioritize service reliability over releasing new features.

Negotiate with the development team to reduce the release frequency to no more than once a week.

Add a plugin to your Jenkins pipeline that prevents new releases whenever your service is out of SLO.

Q74. 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 Packer

Cloud Build with Google Cloud Deploy

Google Kubernetes Engine with Google Cloud Deploy

Cloud Build with kpt

Explanation
Cloud Build is a fully managed continuous integration and continuous delivery (CI/CD) service that helps you automate your builds, tests, and deployments. Google Cloud Deploy is a service that automates the deployment of your applications to Google Kubernetes Engine (GKE).
Together, Cloud Build and Google Cloud Deploy can be used to build and deploy your application’s custom Compute Engine images to your current environment and to other cloud providers in the future.
Here are the steps involved in using Cloud Build and Google Cloud Deploy to implement a CI/CD pipeline for your application:
Create a Cloud Build trigger that fires whenever a change is made to your application’s code.
In the Cloud Build trigger, configure Cloud Build to build your application’s Docker image.
Create a Google Cloud Deploy configuration file that specifies how to deploy your application’s Docker image to GKE.
In Google Cloud Deploy, create a deployment that uses your configuration file.
Once you have created the Cloud Build trigger and Google Cloud Deploy configuration file, any changes made to your application’s code will trigger Cloud Build to build a new Docker image. Google Cloud Deploy will then deploy the new Docker image to GKE.
This solution stack is adaptable to future changes because it uses a cloud-agnostic approach. Cloud Build can be used to build Docker images for any cloud provider, and Google Cloud Deploy can be used to deploy Docker images to any Kubernetes cluster.
The other solution stacks are not as adaptable to future changes. For example, solution stack A (Cloud Build with Packer) is limited to building Docker images for Compute Engine. Solution stack C (Google Kubernetes Engine with Google Cloud Deploy) is limited to deploying Docker images to GKE. Solution stack D (Cloud Build with kpt) is a newer solution that is not yet as mature as Cloud Build and Google Cloud Deploy.
Overall, the best solution stack for implementing a CI/CD pipeline for your application in a multi-cloud environment is Cloud Build with Google Cloud Deploy. This solution stack is fully managed, cloud-agnostic, and adaptable to future changes.

Q75. Your company follows Site Reliability Engineering practices. You are the Incident Commander for a new. customer-impacting incident. You need to immediately assign two incident management roles to assist you in an effective incident response. What roles should you assign?
Choose 2 answers

Operations Lead

Engineering Lead

Communications Lead

Customer Impact Assessor

External Customer Communications Lead

Q76. You are managing an application that exposes an HTTP endpoint without using a load balancer. The latency of the HTTP responses is important for the user experience. You want to understand what HTTP latencies all of your users are experiencing. You use Stackdriver Monitoring. What should you do?

In your application, create a metric with a metricKind set to DELTA and a valueType set to DOUBLE.
* In Stackdriver’s Metrics Explorer, use a Slacked Bar graph to visualize the metric.

In your application, create a metric with a metricKind set to CUMULATIVE and a valueType set to DOUBLE.
* In Stackdriver’s Metrics Explorer, use a Line graph to visualize the metric.

In your application, create a metric with a metricKind set to gauge and a valueType set to distribution.
* In Stackdriver’s Metrics Explorer, use a Heatmap graph to visualize the metric.

In your application, create a metric with a metricKind. set toMETRlc_KIND_UNSPECIFIEDanda valueType set to INT64.
* In Stackdriver’s Metrics Explorer, use a Stacked Area graph to visualize the metric.

Q77. You are managing an application that exposes an HTTP endpoint without using a load balancer. The latency of the HTTP responses is important for the user experience. You want to understand what HTTP latencies all of your users are experiencing. You use Stackdriver Monitoring. What should you do?

* In your application, create a metric with a metricKind set to DELTA and a valueType set to DOUBLE.
* In Stackdriver’s Metrics Explorer, use a Slacked Bar graph to visualize the metric.

* In your application, create a metric with a metricKind set to CUMULATIVE and a valueType set to DOUBLE.
* In Stackdriver’s Metrics Explorer, use a Line graph to visualize the metric.

* In your application, create a metric with a metricKind set to gauge and a valueType set to distribution.
* In Stackdriver’s Metrics Explorer, use a Heatmap graph to visualize the metric.

* In your application, create a metric with a metricKind. set toMETRlc_KIND_UNSPECIFIEDanda valueType set to INT64.
* In Stackdriver’s Metrics Explorer, use a Stacked Area graph to visualize the metric.

Q78. You are running an experiment to see whether your users like a new feature of a web application. Shortly after deploying the feature as a canary release, you receive a spike in the number of 500 errors sent to users, and your monitoring reports show increased latency. You want to quickly minimize the negative impact on users. What should you do first?

Roll back the experimental canary release.

Start monitoring latency, traffic, errors, and saturation.

Record data for the postmortem document of the incident.

Trace the origin of 500 errors and the root cause of increased latency.

Q79. You have migrated an e-commerce application to Google Cloud Platform (GCP). You want to prepare the application for the upcoming busy season. What should you do first to prepare for the busy season?

Load teat the application to profile its performance for scaling.

Enable AutoScaling on the production clusters, in case there is growth.

Pre-provision double the compute power used last season, expecting growth.

Create a runbook on inflating the disaster recovery (DR) environment if there is growth.

Q80. You support a trading application written in Python and hosted on App Engine flexible environment. You want to customize the error information being sent to Stackdriver Error Reporting. What should you do?

Install the Stackdriver Error Reporting library for Python, and then run your code on a Compute Engine VM.

Install the Stackdriver Error Reporting library for Python, and then run your code on Google Kubernetes Engine.

Install the Stackdriver Error Reporting library for Python, and then run your code on App Engine flexible environment.

Use the Stackdriver Error Reporting API to write errors from your application to ReportedErrorEvent, and then generate log entries with properly formatted error messages in Stackdriver Logging.

Q81. You are performing a semiannual capacity planning exercise for your flagship service. You expect a service user growth rate of 10% month-over-month over the next six months. Your service is fully containerized and runs on Google Cloud Platform (GCP). using a Google Kubernetes Engine (GKE) Standard regional cluster on three zones with cluster autoscaler enabled. You currently consume about 30% of your total deployed CPU capacity, and you require resilience against the failure of a zone. You want to ensure that your users experience minimal negative impact as a result of this growth or as a result of zone failure, while avoiding unnecessary costs. How should you prepare to handle the predicted growth?

Verity the maximum node pool size, enable a horizontal pod autoscaler, and then perform a load test to verity your expected resource needs.

Because you are deployed on GKE and are using a cluster autoscaler. your GKE cluster will scale automatically, regardless of growth rate.

Because you are at only 30% utilization, you have significant headroom and you won’t need to add any additional capacity for this rate of growth.

Proactively add 60% more node capacity to account for six months of 10% growth rate, and then perform a load test to make sure you have enough capacity.

Q82. Your product is currently deployed in three Google Cloud Platform (GCP) zones with your users divided between the zones. You can fail over from one zone to another, but it causes a 10-minute service disruption for the affected users. You typically experience a database failure once per quarter and can detect it within five minutes. You are cataloging the reliability risks of a new real-time chat feature for your product. You catalog the following information for each risk:
* Mean Time to Detect (MUD} in minutes
* Mean Time to Repair (MTTR) in minutes
* Mean Time Between Failure (MTBF) in days
* User Impact Percentage
The chat feature requires a new database system that takes twice as long to successfully fail over between zones. You want to account for the risk of the new database failing in one zone. What would be the values for the risk of database failover with the new system?

MTTD: 5
MTTR: 10
MTBF: 90
Impact: 33%

MTTD:5
MTTR: 20
MTBF: 90
Impact: 33%

MTTD:5
MTTR: 10
MTBF: 90
Impact 50%

MTTD:5
MTTR: 20
MTBF: 90
Impact: 50%

Q83. Your company processes IOT data at scale by using Pub/Sub, App Engine standard environment, and an application written in GO. You noticed that the performance inconsistently degrades at peak load. You could not reproduce this issue on your workstation. You need to continuously monitor the application in production to identify slow paths in the code. You want to minimize performance impact and management overhead.
What should you do?
Install a continuous profiling tool into Compute Engine. Configure the application to send profiling data to the tool.

Periodically run the go tool pprof command against the application instance. Analyze the results by using flame graphs.

Configure Cloud Profiler, and initialize the [email protected]/go/profiler library in the application.

Use Cloud Monitoring to assess the App Engine CPU utilization metric.

Q84. You have a CI/CD pipeline that uses Cloud Build to build new Docker images and push them to Docker Hub. You use Git for code versioning. After making a change in the Cloud Build YAML configuration, you notice that no new artifacts are being built by the pipeline. You need to resolve the issue following Site Reliability Engineering practices. What should you do?

Disable the CI pipeline and revert to manually building and pushing the artifacts.

Change the CI pipeline to push the artifacts to Container Registry instead of Docker Hub.

Upload the configuration YAML file to Cloud Storage and use Error Reporting to identify and fix the issue.

Run a Git compare between the previous and current Cloud Build Configuration files to find and fix the bug.

Q85. 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.

Q86. You manage several production systems that run on Compute Engine in the same Google Cloud Platform (GCP) project. Each system has its own set of dedicated Compute Engine instances. You want to know how must it costs to run each of the systems. What should you do?

In the Google Cloud Platform Console, use the Cost Breakdown section to visualize the costs per system.

Assign all instances a label specific to the system they run. Configure BigQuery billing export and query costs per label.

Enrich all instances with metadata specific to the system they run. Configure Stackdriver Logging to export to BigQuery, and query costs based on the metadata.

Name each virtual machine (VM) after the system it runs. Set up a usage report export to a Cloud Storage bucket. Configure the bucket as a source in BigQuery to query costs based on VM name.

Q87. Your team is designing a new application for deployment both inside and outside Google Cloud Platform (GCP). You need to collect detailed metrics such as system resource utilization. You want to use centralized GCP services while minimizing the amount of work required to set up this collection system. What should you do?

Import the Stackdriver Profiler package, and configure it to relay function timing data to Stackdriver for further analysis.

Import the Stackdriver Debugger package, and configure the application to emit debug messages with timing information.

Instrument the code using a timing library, and publish the metrics via a health check endpoint that is scraped by Stackdriver.

Install an Application Performance Monitoring (APM) tool in both locations, and configure an export to a central data storage location for analysis.

Free 2024 Professional-Cloud-DevOps-Engineer Dumps 100 Pass Guarantee With Latest Demo [Q64-Q87]

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