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質問 # 82
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?
- A. 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. - B. 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. - C. 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. - D. 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.
正解：B
解説：
Explanation
The correct answer is A. Communicate your intent to the incident team. Perform a load analysis to determine if the remaining nodes can handle the increase in traffic offloaded from the removed node, and scale appropriately. When any new nodes report healthy, drain traffic from the unhealthy node, and remove the unhealthy node from service.
This answer follows the Google-recommended practices for incident management, as described in the Chapter
9 - Incident Response, Google SRE Book1. According to this source, some of the best practices are:
Maintain a clear line of command. Designate clearly defined roles. Keep a working record of debugging and mitigation as you go. Declare incidents early and often.
Communicate your intent before taking any action that might affect the service or the incident response.
This helps to avoid confusion, duplication of work, or unintended consequences.
Perform a load analysis before removing a node from the load balancer pool, as this might affect the capacity and performance of the service. Scale the pool as necessary to handle the expected load.
Drain traffic from the unhealthy node before removing it from service, as this helps to avoid dropping requests or causing errors for users.
Answer A follows these best practices by communicating the intent to the incident team, performing a load analysis and scaling the pool, and draining traffic from the unhealthy node before removing it.
Answer B does not follow the best practice of performing a load analysis before adding or removing nodes, as this might cause overloading or underutilization of resources.
Answer C does not follow the best practice of communicating the intent before taking any action, as this might cause confusion or conflict with other responders.
Answer D does not follow the best practice of draining traffic from the unhealthy node before removing it, as this might cause errors for users.
References:
1: Chapter 9 - Incident Response, Google SRE Book
質問 # 83
The new version of your containerized application has been tested and is ready to be deployed to production on Google Kubernetes Engine (GKE) You could not fully load-test the new version in your pre-production environment and you need to ensure that the application does not have performance problems after deployment Your deployment must be automated What should you do?
- A. Deploy the application through a continuous delivery pipeline by using canary deployments Use Cloud Monitoring to look for performance issues, and ramp up traffic as supported by the metrics
- B. Deploy the application by using kubectl and set the spec. updatestrategy. type field to RollingUpdate Use Cloud Monitoring to look for performance issues, and run the kubectl rollback command if there are any issues.
- C. Deploy the application by using kubectl and use Config Connector to slowly ramp up traffic between versions. Use Cloud Monitoring to look for performance issues
- D. Deploy the application through a continuous delivery pipeline by using blue/green deployments Migrate traffic to the new version of the application and use Cloud Monitoring to look for performance issues
正解：A
解説：
Explanation
The best option for deploying a new version of your containerized application to production on GKE and ensuring that the application does not have performance problems after deployment is to deploy the application through a continuous delivery pipeline by using canary deployments, use Cloud Monitoring to look for performance issues, and ramp up traffic as supported by the metrics. A canary deployment is a deployment strategy that involves releasing a new version of an application to a subset of users or servers and monitoring its performance and reliability. This way, you can test the new version in the production environment with real traffic and load, and gradually increase the traffic as the metrics indicate. You can use Cloud Monitoring to collect and analyze metrics from your application and GKE cluster, such as latency, error rate, CPU utilization, and memory usage. You can also use Cloud Monitoring to set up alerts and dashboards to track the performance of your application.
質問 # 84
Your team is designing a new application for deployment into Google Kubernetes Engine (GKE). You need to set up monitoring to collect and aggregate various application-level metrics in a centralized location. You want to use Google Cloud Platform services while minimizing the amount of work required to set up monitoring. What should you do?
- A. Install the Cloud Pub/Sub client libraries, push various metrics from the application to various topics, and then observe the aggregated metrics in Stackdriver.
- B. Publish various metrics from the application directly to the Slackdriver Monitoring API, and then observe these custom metrics in Stackdriver.
- C. Emit all metrics in the form of application-specific log messages, pass these messages from the containers to the Stackdriver logging collector, and then observe metrics in Stackdriver.
- D. Install the OpenTelemetry client libraries in the application, configure Stackdriver as the export destination for the metrics, and then observe the application's metrics in Stackdriver.
正解：D
質問 # 85
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?
- A. Standard Tier with a regional load balancer
- B. Premium Tier with a regional load balancer
- C. Premium Tier with a global load balancer
- D. Standard Tier with a global load balancer
正解：B
解説：
Explanation
The most cost-effective network tier and load balancing configuration for your frontend tier is to use Premium Tier with a regional load balancer. Premium Tier is a network tier that provides high-performance and low-latency network connectivity across Google's global network. A regional load balancer is a load balancer that distributes traffic within a single region. Since your application is deployed entirely within the europe-west2 region and only serves users based in the United Kingdom, you can use Premium Tier with a regional load balancer to optimize the network performance and cost.
質問 # 86
You currently store the virtual machine (VM) utilization logs in Stackdriver. You need to provide an easy-to-share interactive VM utilization dashboard that is updated in real time and contains information aggregated on a quarterly basis. You want to use Google Cloud Platform solutions. What should you do?
- A. 1. Export VM utilization logs from Stackdriver to Cloud Pub/Sub.
2. From Cloud Pub/Sub, send the logs to a Security Information and Event Management (SIEM) system.
3. Build the dashboards in the SIEM system and share with your stakeholders. - B. 1. Export VM utilization logs from Stackdriver to a Cloud Storage bucket.
2. Enable the Cloud Storage API to pull the logs programmatically.
3. Build a custom data visualization application.
4. Display the pulled logs in a custom dashboard. - C. 1. Export VM utilization logs (rom Stackdriver to BigQuery.
2. From BigQuery. export the logs to a CSV file.
3. Import the CSV file into Google Sheets.
4. Build a dashboard in Google Sheets and share it with your stakeholders. - D. 1. Export VM utilization logs from Stackdriver to BigOuery.
2. Create a dashboard in Data Studio.
3. Share the dashboard with your stakeholders.
正解：D
質問 # 87
Your team is designing a new application for deployment into Google Kubernetes Engine (GKE). You need to set up monitoring to collect and aggregate various application-level metrics in a centralized location. You want to use Google Cloud Platform services while minimizing the amount of work required to set up monitoring.
What should you do?
- A. Install the Cloud Pub/Sub client libraries, push various metrics from the application to various topics, and then observe the aggregated metrics in Stackdriver.
- B. Publish various metrics from the application directly to the Stackdriver Monitoring API, and then observe these custom metrics in Stackdriver.
- C. Emit all metrics in the form of application-specific log messages, pass these messages from the containers to the Stackdriver logging collector, and then observe metrics in Stackdriver.
- D. Install the OpenTelemetry client libraries in the application, configure Stackdriver as the export destination for the metrics, and then observe the application's metrics in Stackdriver.
正解：D
質問 # 88
Your company runs applications in Google Kubernetes Engine (GKE). Several applications rely on ephemeral volumes. You noticed some applications were unstable due to the DiskPressure node condition on the worker nodes. You need to identify which Pods are causing the issue, but you do not have execute access to workloads and nodes. What should you do?
- A. Locate all the Pods with emptyDir volumes. use the df-h command to measure volume disk usage.
- B. Locate all the Pods with emptyDir volumes. Use the du -sh * command to measure volume disk usage.
- C. Check the metric by using Metrics Explorer.
- D. Check the node/ephemeral_storage/used_bytes metric by using Metrics Explorer.
正解：D
解説：
The correct answer is A, Check the node/ephemeral_storage/used_bytes metric by using Metrics Explorer.
The node/ephemeral_storage/used_bytes metric reports the total amount of ephemeral storage used by Pods on each node1. You can use Metrics Explorer to query and visualize this metric and filter it by node name, namespace, or Pod name2. This way, you can identify which Pods are consuming the most ephemeral storage and causing disk pressure on the nodes. You do not need to have execute access to the workloads or nodes to use Metrics Explorer.
The other options are incorrect because they require execute access to the workloads or nodes, which you do not have. The df -h and du -sh * commands are Linux commands that can measure disk usage, but you need to run them inside the Pods or on the nodes, which is not possible in your scenario34.
Reference:
Monitoring metrics for Kubernetes system components, Node metrics, node/ephemeral_storage/used_bytes. Using Metrics Explorer, Querying metrics. How do I find out disk space utilization information using Linux command line?, df command. How to check disk space in Linux from the command line, du command.
質問 # 89
You support the backend of a mobile phone game that runs on a Google Kubernetes Engine (GKE) cluster. The application is serving HTTP requests from users. You need to implement a solution that will reduce the network cost. What should you do?
- A. Configure the VPC as a Shared VPC Host project.
- B. Configure your Kubernetes duster as a Private Cluster.
- C. Configure a Google Cloud HTTP Load Balancer as Ingress.
- D. Configure your network services on the Standard Tier.
正解：D
解説：
The Standard Tier network service offers lower network costs than the Premium Tier. This is the correct option to reduce the network cost for the application3.
質問 # 90
You are on-call for an infrastructure service that has a large number of dependent systems. You receive an alert indicating that the service is failing to serve most of its requests and all of its dependent systems with hundreds of thousands of users are affected. As part of your Site Reliability Engineering (SRE) incident management protocol, you declare yourself Incident Commander (IC) and pull in two experienced people from your team as Operations Lead (OLJ and Communications Lead (CL). What should you do next?
- A. Establish a communication channel where incident responders and leads can communicate with each other.
- B. Look for ways to mitigate user impact and deploy the mitigations to production.
- C. Start a postmortem, add incident information, circulate the draft internally, and ask internal stakeholders for input.
- D. Contact the affected service owners and update them on the status of the incident.
正解：B
解説：
https://sre.google/sre-book/managing-incidents/
質問 # 91
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?
- A. Assign the team lead as the owner for all action items because they are in charge of the SRE team.
- B. Assign collaborators but no individual owners to the items to keep the postmortem blameless.
- C. Assign multiple owners for each item to guarantee that the team addresses items quickly
- D. Assign one owner for each action item and any necessary collaborators.
正解：D
解説：
https://devops.com/when-it-disaster-strikes-part-3-conducting-a-blameless-post-mortem/
質問 # 92
You are the on-call Site Reliability Engineer for a microservice that is deployed to a Google Kubernetes Engine (GKE) Autopilot cluster. Your company runs an online store that publishes order messages to Pub/Sub and a microservice receives these messages and updates stock information in the warehousing system. A sales event caused an increase in orders, and the stock information is not being updated quickly enough. This is causing a large number of orders to be accepted for products that are out of stock You check the metrics for the microservice and compare them to typical levels.
You need to ensure that the warehouse system accurately reflects product inventory at the time orders are placed and minimize the impact on customers What should you do?
- A. Increase the Pod CPU and memory limits
- B. Increase the number of Pod replicas
- C. Decrease the acknowledgment deadline on the subscription
- D. Add a virtual queue to the online store that allows typical traffic levels
正解：B
解説：
Explanation
The best option for ensuring that the warehouse system accurately reflects product inventory at the time orders are placed and minimizing the impact on customers is to increase the number of Pod replicas. Increasing the number of Pod replicas will increase the scalability and availability of your microservice, which will allow it to handle more Pub/Sub messages and update stock information faster. This way, you can reduce the backlog of undelivered messages and oldest unacknowledged message age, which are causing delays in updating product inventory. You can use Horizontal Pod Autoscaler or Cloud Monitoring metrics-based autoscaling to automatically adjust the number of Pod replicas based on load or custom metrics.
質問 # 93
You use Cloud Build to build and deploy your application. You want to securely incorporate database credentials and other application secrets into the build pipeline. You also want to minimize the development effort. What should you do?
- A. Encrypt the secrets and store them in the application repository. Store a decryption key in a separate repository and grant Cloud Build access to the repository.
- B. Create a Cloud Storage bucket and use the built-in encryption at rest. Store the secrets in the bucket and grant Cloud Build access to the bucket.
- C. Use client-side encryption to encrypt the secrets and store them in a Cloud Storage bucket. Store a decryption key in the bucket and grant Cloud Build access to the bucket.
- D. Use Cloud Key Management Service (Cloud KMS) to encrypt the secrets and include them in your Cloud Build deployment configuration. Grant Cloud Build access to the KeyRing.
正解：D
解説：
Explanation
https://cloud.google.com/build/docs/securing-builds/use-encrypted-credentials
質問 # 94
You support an application running on App Engine. The application is used globally and accessed from various device types. You want to know the number of connections. You are using Stackdriver Monitoring for App Engine. What metric should you use?
- A. tcp_ssl_proxy/open_connections
- B. flex/instance/connections/current
- C. flex/connections/current
- D. tcp_ssl_proxy/new_connections
正解：B
解説：
Explanation/Reference: https://cloud.google.com/monitoring/api/metrics_gcp
質問 # 95
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?
- A. Build a new container from a previous Git tag, and do a rolling update on the deployment to the new container.
- B. Create a new tag called stable that points to the previously working container, and change the deployment to point to the new tag.
- C. Alter the deployment to point to the sha2 56 digest of the previously working container.
- D. Apply the latest tag to the previous container image, and do a rolling update on the deployment.
正解：C
質問 # 96
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?
- A. 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.
- B. Use the filter-record-transformer Fluentd filter plugin to remove the fields from the log entries in flight.
- C. Use the fluent-plugin-record-reformer Fluentd output plugin to remove the fields from the log entries in flight.
- D. Wait for the application developers to patch the application, and then verify that the log entries are no longer exposing PII.
正解：C
質問 # 97
You are reviewing your deployment pipeline in Google Cloud Deploy You must reduce toil in the pipeline and you want to minimize the amount of time it takes to complete an end-to-end deployment What should you do?
Choose 2 answers
- A. Add more engineers to finish the manual steps.
- B. Create a trigger to notify the required team to complete the next step when manual intervention is required
- C. Automate promotion approvals from the development environment to the test environment
- D. Divide the automation steps into smaller tasks
- E. Use a script to automate the creation of the deployment pipeline in Google Cloud Deploy
正解：B、C
解説：
The best options for reducing toil in the pipeline and minimizing the amount of time it takes to complete an end-to-end deployment are to create a trigger to notify the required team to complete the next step when manual intervention is required and to automate promotion approvals from the development environment to the test environment. A trigger is a resource that initiates a deployment when an event occurs, such as a code change, a schedule, or a manual request. You can create a trigger to notify the required team to complete the next step when manual intervention is required by using Cloud Build or Cloud Functions. This way, you can reduce the waiting time and human errors in the pipeline. A promotion approval is a process that allows you to approve or reject a deployment from one environment to another, such as from development to test. You can automate promotion approvals from the development environment to the test environment by using Google Cloud Deploy or Cloud Build. This way, you can speed up the deployment process and avoid manual steps.
質問 # 98
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?
- A. Use the metrics from Anthos Service Mesh to measure the health of the microservices
- B. Create SLIs from metrics Enable Alert Policies if the services do not pass
- C. Create a SLO Create an Alert Policy on select_slo_bum_rate
- D. Create a SLO and configure uptime checks for your services Enable Alert Policies if the services do not pass
正解：C
解説：
Explanation
The best option for detecting consumption of an error budget to protect customers and define release policies is to create a service level objective (SLO) and create an alert policy on select_slo_burn_rate. A SLO is a target value or range of values for a service level indicator (SLI) that measures some aspect of the service quality, such as availability or latency. An error budget is the amount of time or number of errors that a service can tolerate while still meeting its SLO. A select_slo_burn_rate is a metric that indicates how fast the error budget is being consumed by the service. By creating an alert policy on select_slo_burn_rate, you can trigger notifications or actions when the error budget consumption exceeds a certain threshold. This way, you can balance change, velocity, and reliability of the service by adjusting the release policies based on the error budget status.
質問 # 99
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