You need to quickly deploy a containerized web application on google cloud. you know the services you want to be exposed. you do not want to manage infrastructure. you only want to pay when requests are being handled and need support for custom packages. what technology meets these needs?

1. Before you begin Running websites can be difficult with all the overhead of creating and managing Virtual Machine (VM) instances, clusters, Pods, services, and more. That's fine for larger, multi-tiered apps, but if you're only trying to get your website deployed and visible, then it's a lot of overhead. With Cloud Run, the Google Cloud implementation of Not only does Cloud Run bring serverless development to containers, but it can also be run either on your own Google Kubernetes Engine (GKE) clusters or on a fully managed platform as a service (PaaS) solution provided by Cloud Run. You'll test the latter scenario in this codelab. The following diagram illustrates the flow of the deployment and Cloud Run hosting. You begin with a Docker image created via Cloud Build, which you trigger in Cloud Shell. Then, you deploy that image to Cloud Run with a command in Cloud Shell. Prerequisites • General familiarity with Docker (See Get started section of Docker's website.) What you'll learn • How to build a Docker image with Cloud Build and upload it to gcr.io • How to deploy Docker images to Cloud Run • How to manage Cloud Run deployments • How to set up an endpoint for an app on Cloud Run What you'll build • A static website that runs inside a Docker container • A version of this container that lives in • A Cloud Run deployment for your static website What you'll need • A Google Account with administrative access to create projects or a project with project-owner role 2. Envir...

Your company has developed a new application that consists of multiple microservices. You want to deploy the application to Google Kubernetes Engine (GKE), and you want to ensure that the cluster can scale as more applications are deployed in the future. You want to avoid manual intervention when each new application is deployed. What should you do? • A. Deploy the application on GKE, and add a HorizontalPodAutoscaler to the deployment. • B. Deploy the application on GKE, and add a VerticalPodAutoscaler to the deployment. • C. Create a GKE cluster with autoscaling enabled on the node pool. Set a minimum and maximum for the size of the node pool. • D. Create a separate node pool for each application, and deploy each application to its dedicated node pool. Answer is C The key point is "ensure that the CLUSTER can scale" A- HorizontalPodAutoscaler - ensures to scale the number of pods while C- Create a GKE cluster with autoscaling enabled on the node pool. Set a minimum and maximum for the size of the node pool. ensures to scale the number of nodes in the cluster. So the answer is C. Its A, When you first deploy your workload to a Kubernetes cluster, you may not be sure about its resource requirements and how those requirements might change depending on usage patterns, external dependencies, or other factors. Horizontal Pod autoscaling helps to ensure that your workload functions consistently in different situations, and allows you to control costs by only paying for extra ca...

You have developed a containerized web application that will serve internal colleagues during business hours. You want to ensure that no costs are incurred outside of the hours the application is used. You have just created a new Google Cloud project and want to deploy the application. What should you do? • A. Deploy the container on Cloud Run for Anthos, and set the minimum number of instances to zero. • B. Deploy the container on Cloud Run (fully managed), and set the minimum number of instances to zero. • C. Deploy the container on App Engine flexible environment with autoscaling, and set the value min_instances to zero in the app.yaml. • D. Deploy the container on App Engine flexible environment with manual scaling, and set the value instances to zero in the app.yaml. I think that is B the correct answer, because Cloud Run can scale to 0: https://cloud.google.com/run/docs/about-instance-autoscaling And App Engine Flexible can't scale to 0, the minimum instance number is 1: https://cloud.google.com/appengine/docs/the-appengine-environments#comparing_high-level_features C. and D. are wrong answers as only the App Engine standard environment scales down to zero. Answer A. will incur extra cost as Cloud Run for Anthos runs on Kubernetes, so need to have a k8s cluster available. B. Is correct, as "Cloud Run automatically scales up or down from zero to N depending on traffic, leveraging container image streaming for a fast startup time." from https://cloud.google.com/run htt...

Twitter Facebook LinkedIn Running applications in a stable and scalable way can be challenging. Fortunately, Google Cloud Platform (GCP) offers GCPCloud Run that allows users to deploy and manage scalable, containerized applications. The complexity of managing resources, hosting them in multiple environments, and dealing with potential service outages can cause headaches for developers. But worry not! This tutorial will walk you through how to deploy a basic scalable containerizedapplication using GCP Cloud Run. Ready? Read on to up your app ops game! Prerequisite This tutorial will be a hands-on demonstration. To follow along, ensure you have a GCP account with active billing enabled, but a Creating a GCP Project The first step in containerizing your application in GCP is to create a new GCP project. Projects are the logical way to organize resources across GCP. Each project provides an isolated environment in which all your services and resources are contained. Note that you should not mix resources from existing projects, which also helps when you clean up your environment later on. To create a GCP project, follow these steps: 1. Open your favorite web browser, and navigate to the Manage resources page in the Google Cloud Console. 2. Next, click CREATE PROJECT to initiate creating a new project. Initiating creating a new project On the next screen, provide the following for your project: Project name A unique name for your GCP project (i.e., gcp-cloud-run-project). Loca...

Get started with Cloud Code • Overview • Work with Kubernetes • Work with Cloud Run • Migrate an application from Cloud Shell Editor to a local IDE • Use version control • Workspace management • Debug your applications • Customize color themes • Use the Cloud Shell Terminal • Use accessibility features •

Containers have become an industry standard. Deploying software is easier and more reliable if it is containerized, especially if you are deploying to the cloud. AWS, being the leader among cloud providers, provides several ways for you to deploy your apps in a containerized fashion. In this article I will: - Explain why containers are so valuable - Examine the various ways of running containers in AWS - Demonstrate one approach to running a containerized web application on AWS Why Are Containers So Valuable? Mimicking a production environment locally can be challenging. Chances are that the operating system, runtime version, and many other dependencies are different on your local machine compared to the production server. These discrepancies can make local testing difficult, and cause unexpected behavior and critical failures in production. Enter Docker When Docker appeared in 2013, it quickly became very popular. All of a sudden you had a platform that enabled you to package your application, along with all of the other dependencies into a sort of "mini-computer" called a container. This ensured that there would be absolutely no discrepancy between the local and production environments, as long as both ran the app in a containerized manner. The Rise of Container Orchestrators The container revolution opened a number of new topics. Mainly - what is the optimal way to actually run containers in production? Industry leaders quickly realized that the need for some sort of or...