You support an application deployed on Compute Engine. The application connects to a Cloud SQL instance to store and retrieve data. After an update to the application, users report errors showing database timeout messages. The number of concurrent active users remained stable. You need to find the most probable cause of the database timeout. What should you do?
A. Check the serial port logs of the Compute Engine instance.
B. Use Stackdriver Profiler to visualize the resources utilization throughout the application.
C. Determine whether there is an increased number of connections to the Cloud SQL instance.
D. Use Cloud Security Scanner to see whether your Cloud SQL is under a Distributed Denial of Service (DDoS) attack.
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. flex/connections/current
B. tcp_ssl_proxy/new_connections
C. tcp_ssl_proxy/open_connections
D. flex/instance/connections/current
Your company experiences bugs, outages, and slowness in its production systems. Developers use the production environment for new feature development and bug fixes. Configuration and experiments are done in the production environment, causing outages for users. Testers use the production environment for load testing, which often slows the production systems. You need to redesign the environment to reduce the number of bugs and outages in production and to enable testers to toad test new features. What should you do?
A. Create an automated testing script in production to detect failures as soon as they occur.
B. Create a development environment with smaller server capacity and give access only to developers and testers.
C. Secure the production environment to ensure that developers can't change it and set up one controlled update per year.
D. Create a development environment for writing code and a test environment for configurations, experiments, and load testing.
You are managing the production deployment to a set of Google Kubernetes Engine (GKE) clusters. You want to make sure only images which are successfully built by your trusted CI/CD pipeline are deployed to production. What should you do?
A. Enable Cloud Security Scanner on the clusters.
B. Enable Vulnerability Analysis on the Container Registry.
C. Set up the Kubernetes Engine clusters as private clusters.
D. Set up the Kubernetes Engine clusters with Binary Authorization.
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?
A. Use Stackdriver Kubernetes Engine Monitoring.
B. Use Prometheus to collect and aggregate logs per container, and then analyze the results in Grafana.
C. Use the Stackdriver Monitoring API to create custom metrics, and then organize your containers using groups.
D. Use Stackdriver Logging to export application logs to BigQuery, aggregate logs per container, and then analyze CPU and memory consumption.
Your application images are built and pushed to Google Container Registry (GCR). You want to build an automated pipeline that deploys the application when the image is updated while minimizing the development effort. What should you do?
A. Use Cloud Build to trigger a Spinnaker pipeline.
B. Use Cloud Pub/Sub to trigger a Spinnaker pipeline.
C. Use a custom builder in Cloud Build to trigger Jenkins pipeline.
D. Use Cloud Pub/Sub to trigger a custom deployment service running in Google Kubernetes Engine (GKE).
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 (MTTD) 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?
A. MTTD: 5 MTTR: 10 MTBF: 90 Impact: 33%
B. MTTD: 5 MTTR: 20 MTBF: 90 Impact: 33%
C. MTTD: 5 MTTR: 10 MTBF: 90 Impact: 50%
D. MTTD: 5 MTTR: 20 MTBF: 90 Impact: 50%
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 network services on the Standard Tier.
C. Configure your Kubernetes duster as a Private Cluster.
D. Configure a Google Cloud HTTP Load Balancer as Ingress.
You encountered a major service outage that affected all users of the service for multiple hours. After several hours of incident management, the service returned to normal, and user access was restored. You need to provide an incident summary to relevant stakeholders following the Site Reliability Engineering recommended practices. What should you do first?
A. Call individual stakeholders to explain what happened.
B. Develop a post-mortem to be distributed to stakeholders.
C. Send the Incident State Document to all the stakeholders.
D. Require the engineer responsible to write an apology email to all stakeholders.
You are performing a semi-annual 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?
A. Verify the maximum node pool size, enable a horizontal pod autoscaler, and then perform a load test to verify your expected resource needs.
B. Because you are deployed on GKE and are using a cluster autoscaler, your GKE cluster will scale automatically regardless of growth rate.
C. 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.
D. 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.
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