Architecting with Google Compute Engine Specialization

Start Date: 07/12/2020

Course Type: Specialization Course

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About Course

This specialization introduces learners to the comprehensive and flexible infrastructure and platform services provided by Google Cloud Platform, with a focus on Compute Engine. Through a combination of presentations, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as networks, systems and applications services. This course also covers deploying practical solutions including securely interconnecting networks, customer-supplied encryption keys, security and access management, quotas and billing, and resource monitoring. This class is intended for Cloud Solutions Architects, DevOps Engineers or individuals using Compute Engine. Note: This Specialization used to be called Architecting with Google Cloud Platform. As the Specialization is now focused on Compute Engine as the computing platform, we have renamed it to Architecting with Google Compute Engine. If you are looking to learn more about App Engine, Cloud Functions and Google Kubernetes Engine, which are services previously covered in the Elastic Cloud Infrastructure: Containers and Services course of this specialization, please refer to the Developing Applications with Google Cloud Platform Specialization and the Architecting with Kubernetes Engine Specialization. >>> By enrolling in this specialization you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: <<<

Course Syllabus

Google Cloud Platform Fundamentals: Core Infrastructure
Essential Cloud Infrastructure: Foundation
Essential Cloud Infrastructure: Core Services
Elastic Cloud Infrastructure: Scaling and Automation

Deep Learning Specialization on Coursera

Course Introduction

Launch your career in Cloud Architecture. Design, develop, and manage cloud solutions to drive business objectives. Architecting with Google Compute Engine Specialization This 1-week, accelerated online class focuses on advanced topics in architecture, data integration, and compute-intensive applications in Google Compute Engine (GCE). After completing this course, you will be able to build scalable and efficient webpages using Google Compute Engine (GCE). You will also be able to use GCE to create architecture-based images and maps for optimization. This is the second course in the Google Cloud Platform Specialization. The first course focused on creating GCE images and maps. To get the best out of this second course, you will need to follow the steps listed in the first course: 1. Create an empty Google Cloud Memory account (GCP or Google Cloud Memory provider). 2. Create an empty Google Virtual Machine (GV). 3. Create an empty Google Virtual Box (GV). 4. Create an empty Google Virtual Computer (GV). 5. Install Eclipse or another IDE using not more than 4 computers. 6. Use Visual Studio IDE to build the project. 7. Run it using Visual Studio IDE or another IDE. Note: You should have a computer with a stable Internet connection and a reliable power supply. You should also have an understanding of programming, including basic machine code, and have some familiarity using the command line.Google Compute Engine GCP Module Eclipse Module Compute Module <|start

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Related Wiki Topic

Article Example
Google Compute Engine Google compute engine unit (GCEU), which is pronounced as GQ, is an abstraction of compute resources. According to Google, 2.75 GCEUs represent the minimum power of one logical core (a hardware hyper-thread) based on the Sandy Bridge platform.
Google Compute Engine Google Compute Engine (GCE) is the Infrastructure as a Service (IaaS) component of Google Cloud Platform which is built on the global infrastructure that runs Google’s search engine, Gmail, YouTube and other services. Google Compute Engine enables users to launch virtual machines (VMs) on demand. VMs can be launched from the standard images or custom images created by users. GCE users need to get authenticated based on OAuth 2.0 before launching the VMs. Google Compute Engine can be accessed via the Developer Console, RESTful API or Command Line Interface.
Google Compute Engine A network belongs to only one project, and each instance can only belong to one network. All Compute Engine networks use the IPv4 protocol. Compute Engine currently does not support IPv6. However, Google is a major advocate of IPv6 and it is an important future direction.
Google Compute Engine During the scheduled maintenance of Google data center, Compute Engine can automatically migrate the VMs from one host to the other without involving any action from the users. This delivers better uptime to applications.
Google Compute Engine Every Google Compute Engine instance starts with a disk resource called persistent disk. Persistent disk provides the disk space for instances and contains the root filesystem from which the instance boots. Persistent disks can be used as raw block devices. By default, Google Compute Engine uses SCSI for attaching persistent disks. Persistent Disks provide straightforward, consistent and reliable storage at a consistent and reliable price, removing the need for a separate local ephemeral disk. Persistent disks need to be created before launching an instance. Once attached to an instance, they can be formatted with the native filesystem. A single persistent disk can be attached to multiple instances in read-only mode. Each persistent disk can be up to 10TB in size. Google Compute Engine encrypts the persistent disks with AES-128-CB, and this encryption is applied before the data leaves the virtual machine monitor and hits the disk. Encryption is always enabled and is transparent to Google Compute Engine users. The integrity of persistent disks is maintained via a HMAC scheme.
Google Compute Engine A Google Compute Engine instance is a virtual machine running on a Linux or Microsoft Windows configuration. Users can choose to modify the instances including customizing the hardware, OS, disk, and other configuration options.
Google Compute Engine An image is a persistent disk that contains the operating system and root file system that is necessary for starting an instance. An image must be selected while creating an instance or during the creation of a root persistent disk. By default, Google Compute Engine installs the root filesystem defined by the image on a root persistent disk. Google Compute Engine provides CentOS and Debian images as standard Linux images. Red Hat Enterprise Linux (RHEL) and Microsoft Windows Server 2008 R2 images are a part of the premier operating system images which are available for an additional fee. CoreOS, the lightweight Linux OS based on Chromium OS is also supported on Google Compute Engine.
Google Compute Engine Compute Engine VMs boot within 30 seconds which is considered to be 4-10x faster than the competition.
Google Compute Engine Google Compute Engine offers a routing table to manage how traffic destined for a certain IP range should be routed. Similar to a physical router in the local area network, all outbound traffic is compared to the routes table are appropriately forwarded if the outbound packet matches any rules in the routes table.
Google Compute Engine A region refers to a geographic location of Google's infrastructure facility. Users can choose to deploy their resources in one of the available regions based on their requirement. As of June 1, 2014, Google Compute Engine is available in central US region, Western Europe and Asia East region.
Google Compute Engine Google Compute Engine uses KVM as the hypervisor, and supports guest images running Linux and Microsoft Windows which are used to launch virtual machines based on the 64 bit x86 architecture. VMs boot from a persistent disk that has a root filesystem. The number of virtual CPUs, amount of memory supported by the VM is dependent on the machine type selected.
Google Compute Engine The persistent disks of Compute Engine deliver higher IOPS consistently. With the cost of provisioned IOPS included within the cost of storage, users need not pay separately for the IOPS.
Google Compute Engine Google announced Compute Engine on June 28, 2012 at Google I/O 2012 in a limited preview mode. In April 2013, GCE was made available to customers with Gold Support Package. On February 25, 2013, Google announced that RightScale was their first reseller. During Google I/O 2013, many features including sub-hour billing, shared-core instance types, larger persistent disks, enhanced SDN based networking capabilities and ISO 27001 certification got announced. GCE became available to everyone on May 15, 2013. Layer 3 load balancing came to GCE on August 7, 2013. Finally, on December 2, 2013, Google announced that GCE is generally available. It also expanded the OS support, enabled live migration of VMs, 16-core instances, faster persistent disks and lowered the price of standard instances.
Google App Engine AppScale automatically deploys and scales unmodified Google App Engine applications over popular public and private cloud systems and on-premises clusters. AppScale can run Python, Java, PHP, and Go applications on EC2, Google Compute Engine, Softlayer, Azure and other cloud vendors.
Buddy (software) Google Cloud Storage, Google Compute Engine, Google App Engine
Google Compute Engine Compute Engine connects various entities called resources that will be a part of the deployment. Each resource performs a different function. When a virtual machine instance is launched, an Instance resource is created that uses other resources, such as Disk resources, Network resources, Image resources, and so on. For example, a Disk resource functions as data storage for the virtual machine, similar to a physical hard drive, and a Network resource helps regulate traffic to and from the instances.
Google Compute Engine At the Google Cloud Platform Live event on March 25, 2014, Urs Hölzle, Senior VP of technical infrastructure announced sustained usage discounts, support for Microsoft Windows Server 2008 R2, Cloud DNS and Cloud Deployment Manager. On May 28, 2014, Google announced optimizations for LXC containers along with dynamic scheduling of Docker containers across a fleet of VM instances.
Google App Engine In Oct 2011, Google previewed a zero maintenance SQL database, which supports JDBC and DB-API. This service allows to create, configure, and use relational databases with App Engine applications. Google Cloud SQL offers MySQL 5.5 and 5.6.
Google Earth Engine The Google Earth Engine provides a data catalog along with computers for analysis; this creates an environment where scientists can collaboratively share data, algorithms, and visualizations using URLS’s.
Google Earth Engine These key changes, like the progression of agriculture, natural resources,and climate can be now viewed on Google Earth Engine. Google Earth Engine has become a platform that makes Landsat data easily accessible to researchers.