PCD — questions

You are monitoring a web application that is written in Go and deployed in Google Kubernetes Engine. You notice an increase in CPU and memory utilization. You need to determine which source code is consuming the most CPU and memory resources. What should you do?

You have a container deployed on Google Kubernetes Engine. The container can sometimes be slow to launch, so you have implemented a liveness probe. You notice that the liveness probe occasionally fails on launch. What should you do?

You work for an organization that manages an ecommerce site. Your application is deployed behind a global HTTP(S) load balancer. You need to test a new product recommendation algorithm. You plan to use A/B testing to determine the new algorithm’s effect on sales in a randomized way. How should you test this feature?

You plan to deploy a new application revision with a Deployment resource to Google Kubernetes Engine (GKE) in production. The container might not work correctly. You want to minimize risk in case there are issues after deploying the revision. You want to follow Google-recommended best practices. What should you do?

Before promoting your new application code to production, you want to conduct testing across a variety of different users. Although this plan is risky, you want to test the new version of the application with production users and you want to control which users are forwarded to the new version of the application based on their operating system. If bugs are discovered in the new version, you want to roll back the newly deployed version of the application as quickly as possible. What should you do?

Your team is writing a backend application to implement the business logic for an interactive voice response (IVR) system that will support a payroll application. The IVR system has the following technical characteristics: • Each customer phone call is associated with a unique IVR session. • The IVR system creates a separate persistent gRPC connection to the backend for each session. • If the connection is interrupted, the IVR system establishes a new connection, causing a slight latency for that call. You need to determine which compute environment should be used to deploy the backend application. Using current call data, you determine that: • Call duration ranges from 1 to 30 minutes. • Calls are typically made during business hours. • There are significant spikes of calls around certain known dates (e.g., pay days), or when large payroll changes occur. You want to minimize cost, effort, and operational overhead. Where should you deploy the backend application?

You are developing an application hosted on Google Cloud that uses a MySQL relational database schema. The application will have a large volume of reads and writes to the database and will require backups and ongoing capacity planning. Your team does not have time to fully manage the database but can take on small administrative tasks. How should you host the database?

You are developing a new web application using Cloud Run and committing code to Cloud Source Repositories. You want to deploy new code in the most efficient way possible. You have already created a Cloud Build YAML file that builds a container and runs the following command: gcloud run deploy. What should you do next?

You are a developer at a large organization. You are deploying a web application to Google Kubernetes Engine (GKE). The DevOps team has built a CI/CD pipeline that uses Cloud Deploy to deploy the application to Dev, Test, and Prod clusters in GKE. After Cloud Deploy successfully deploys the application to the Dev cluster, you want to automatically promote it to the Test cluster. How should you configure this process following Google-recommended best practices?

Your application is running as a container in a Google Kubernetes Engine cluster. You need to add a secret to your application using a secure approach. What should you do?

You are a developer at a financial institution. You use Cloud Shell to interact with Google Cloud services. User data is currently stored on an ephemeral disk; however, a recently passed regulation mandates that you can no longer store sensitive information on an ephemeral disk. You need to implement a new storage solution for your user data. You want to minimize code changes. Where should you store your user data?

You recently developed a web application to transfer log data to a Cloud Storage bucket daily. Authenticated users will regularly review logs from the prior two weeks for critical events. After that, logs will be reviewed once annually by an external auditor. Data must be stored for a period of no less than 7 years. You want to propose a storage solution that meets these requirements and minimizes costs. What should you do? (Choose two.)

Your team is developing a Cloud Function triggered by Cloud Storage events. You want to accelerate testing and development of your Cloud Function while following Google-recommended best practices. What should you do?

Your team is setting up a build pipeline for an application that will run in Google Kubernetes Engine (GKE). For security reasons, you only want images produced by the pipeline to be deployed to your GKE cluster. Which combination of Google Cloud services should you use?

You are supporting a business-critical application in production deployed on Cloud Run. The application is reporting HTTP 500 errors that are affecting the usability of the application. You want to be alerted when the number of errors exceeds 15% of the requests within a specific time window. What should you do?

You need to build a public API that authenticates, enforces quotas, and reports metrics for API callers. Which tool should you use to complete this architecture?

You noticed that your application was forcefully shut down during a Deployment update in Google Kubernetes Engine. Your application didn’t close the database connection before it was terminated. You want to update your application to make sure that it completes a graceful shutdown. What should you do?

You are a lead developer working on a new retail system that runs on Cloud Run and Firestore in Datastore mode. A web UI requirement is for the system to display a list of available products when users access the system and for the user to be able to browse through all products. You have implemented this requirement in the minimum viable product (MVP) phase by returning a list of all available products stored in Firestore. A few months after go-live, you notice that Cloud Run instances are terminated with HTTP 500: Container instances are exceeding memory limits errors during busy times. This error coincides with spikes in the number of Datastore entity reads. You need to prevent Cloud Run from crashing and decrease the number of Datastore entity reads. You want to use a solution that optimizes system performance. What should you do?

You need to deploy an internet-facing microservices application to Google Kubernetes Engine (GKE). You want to validate new features using the A/B testing method. You have the following requirements for deploying new container image releases: • There is no downtime when new container images are deployed. • New production releases are tested and verified using a subset of production users. What should you do?

Your team manages a large Google Kubernetes Engine (GKE) cluster. Several application teams currently use the same namespace to develop microservices for the cluster. Your organization plans to onboard additional teams to create microservices. You need to configure multiple environments while ensuring the security and optimal performance of each team’s work. You want to minimize cost and follow Google-recommended best practices. What should you do?