Professional Cloud DevOps Engineer Exam
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?
Configure the VPC as a Shared VPC Host project.
Configure your network services on the Standard Tier.
Configure your Kubernetes cluster as a Private Cluster.
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?
Call individual stakeholders to explain what happened.
Develop a post-mortem to be distributed to stakeholders.
Send the Incident State Document to all the stakeholders.
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?
Verify the maximum node pool size, enable a horizontal pod autoscaler, and then perform a load test to verify 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.
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?
Use Cloud Build to trigger a Spinnaker pipeline.
Use Cloud Pub/Sub to trigger a Spinnaker pipeline.
Use a custom builder in Cloud Build to trigger Jenkins pipeline.
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?
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%
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