Your preview application, deployed on a single-zone Google Kubernetes Engine (GKE) cluster in us-centrall, has gained popularity. You are now ready to make the application generally available. You need to deploy the application to production while ensuring high availability and resilience. You also want to follow Google-recommended practices. What should you do?
Your manager asks you to deploy a workload to a Kubernetes cluster. You are not sure of the workloads resource requirements or how the requirements might vary depending on usage patterns, external dependencies, or other factors. You need a solution that makes cost-effective recommendations regarding CPU and memory requirements, and allows the workload to function consistently in any situation. You want to follow Google-recommended practices. What should you do?
You have several hundred microservice applications running in a Google Kubernetes Engine (GKE) cluster. Each microservice is a deployment with resource limits configured for each container in the deployment. You've observed that the resource limits for memory and CPU are not appropriately set for many of the microservices. You want to ensure that each microservice has right sized limits for memory and CPU. What should you do?
You have a project for your App Engine application that serves a development environment. The required testing has succeeded and you want to create a new project to serve as your production environment. What should you do?
You want to host your video encoding software on Compute Engine. Your user base is growing rapidly, and users need to be able 3 to encode their videos at any time without interruption or CPU limitations. You must ensure that your encoding solution is highly available, and you want to follow Google-recommended practices to automate operations. What should you do?
You are deploying a web application using Compute Engine. You created a managed instance group (MIG) to host the application. You want to follow Google-recommended practices to implement a secure and highly available solution. What should you do?
You have two Google Cloud projects: project-a with VPC vpc-a (10.0.0.0/16) and project-b with VPC vpc-b (10.8.0.0/16). Your frontend application resides in vpc-a and the backend API services ate deployed in vpc-b. You need to efficiently and cost-effectively enable communication between these Google Cloud projects. You also want to follow Google-recommended practices. What should you do?
Your company has embraced a hybrid cloud strategy where some of the applications are deployed on Google Cloud. A Virtual Private Network (VPN) tunnel connects your Virtual Private Cloud (VPC) in Google Cloud with your company's on-premises network. Multiple applications in Google Cloud need to connect to an on-premises database server, and you want to avoid having to change the IP configuration in all of your applications when the IP of the database changes.
What should you do?