Gce google

Author: e | 2025-04-25

Figure 4: Google Compute Engine (GCE) Icon 3.1 Google Compute Engine (GCE)IaaS. GCE is Google’s IaaS offering. With GCE you have the liberty of creating Virtual Machines, allocating CPU and

Docker and GCE - Google Slides

Same machine types and VM configurations as standard compute instances. Spot VMs. These are affordable instance options used for fault-tolerant workloads and batch jobs. They help users cut costs, but they can be prone to service interruptions. Spot VMs come with the same capabilities and machine types as standard VMs. Virtual machine manager. GCE comes with the VM manager, which helps users manage OSes for large collections of VMs. GCE also provides right-sizing recommendations to help customers use resources efficiently. Why do businesses use Google Compute Engine? There are many reasons organizations use Google Compute Engine, including these three: Cost-effective. GCE is a cost-effective way to run large and compute-intensive High-performing and scalable. Both of these features make GCE good for businesses that need to process large quantities of data quickly. Flexible. GCE can be used for a variety of workloads, such as web applications, batch processing and machine learning. Some real-world, compute-intensive workload scenarios where GCE is used include the following: VM migration. Google cloud platform, or GCP, customers can use GCE to migrate their applications to the cloud from physical servers. Genomics data processing. GCE provides the processing power to handle compute-intensive tasks like genomics data processing. With GCE integrated in their data center, users can process petabytes of data fast. BYOL. BYOL in Google Compute Engine lets customers run their Windows-based applications in sole tenant nodes or with a license-included image. MySQL applications. Users can run databases on GCE by integrating with MySQL, which acts as a managed relational database service. Google Compute Engine vs. Google App Engine Both of GCE and Google App Engine are used for deploying applications in the cloud. However, each works at a different point in the process. Google Compute Engine is an IaaS tool, providing VMs that help organizations build and manage servers, OSes and network devices. Customers can manage infrastructure that Google hosts remotely. Google App Engine is a platform as a service. PaaS tools provide developers with a hosted environment to build applications. They help automate application design, development, testing and deployment. With App Engine, developers can deploy their code and the platform will automatically adjust to handle the traffic volume. Compute Engine users must manually adjust the infrastructure elements that host the application. This means they get more flexibility and, in some cases, reduced costs. Unlike Google Compute Engine, Google App Engine is a serverless offering that frees developers from server maintenance tasks like managing load balancers and patching operating systems. Google App Engine and Compute Engine can be used together as part of Google's cloud computing platform. Get more information about the integration of IaaS and PaaS offerings across providers to understand how the two work together. This was last updated in May 2022 Continue Reading About Google Compute Engine PaaS showdown: AWS Elastic Beanstalk vs. Google App Engine A cloud services cheat sheet for AWS, Azure and Google Cloud Compare serverless tools and services in the public cloud SaaS vs. IaaS vs. PaaS: Differences, Pros, Cons Google Compute Engine (GCE) is an infrastructure as a service (IaaS) offering that allows clients to run workloads on Google's physical hardware. Google Compute Engine provides a scalable number of virtual machines (VMs) to serve as large compute clusters for that purpose. GCE can be managed through a RESTful application program interface (API), command line interface or web console. Compute Engine pricing is on a pay-per-usage basis with a one minute minimum, charged on a per-second basis. Google doesn't charge any upfront fees or require a time-period commitment for GCE. Google's cloud services compete with Microsoft's Azure and Amazon Web Services. GCE provides administrators with VM, DNS server and load balancing capabilities. VMs are available in a number of CPU and RAM configurations and Linux distributions, including Debian and CentOS. Customers may use their own system images for custom VMs. With GCE, administrators can select the Google Cloud region and zone where their data will be stored and used. GCE also offers tools for administrators to create advanced networks on the regional level. Google Compute Engine is part of Google Cloud Platform, which includes many serverless services that can be used in conjunction with GCE for computing, processing and storage tasks. What are the key features of Google Compute Engine? GCE includes the following features: Cloud storage. Persistent disks feature high-performance block storage that lets users take snapshots and create new persistent disks from the snapshot. Confidential VMs. These VMs enable users to encrypt data while it's being processed without negatively affecting performance. Custom machine types. Users can customize VMs to suit business needs and optimize cost effectiveness. Global load balancing. This feature distributes workloads across multiple instance regions to improve performance, throughput and availability. GPU accelerators. Users can add GPUs to speed up computationally intensive workloads like virtual workstation applications and machine learning. Customers pay for GPU resources only while using them. Instance groups. These VM clusters run a single application and automatically manage updates. Live migration for VMs. VMs can migrate between host machines without rebooting. This feature enables applications to continue running during maintenance. Local solid-state drives. These local SSDs are always encrypted and physically attached to the host server. They have low latency compared to persistent disks. Operating system (OS) support. Users can run a number of different OSes, including Debian, CentOS, Red Hat Enterprise Linux, SUSE, Ubuntu and Windows Server. GCE also includes patch management for OSes. Payment. GCE offers per-second billing and committed use discounts with no upfront costs or instance lock-in. Predefined machine types. Predefined Compute Engine VM configurations range from small general-purpose virtual machine instances to large memory-optimized ones. Reservations. Users can reserve VM instances in a specific zone to ensure that a project has resources for a potential increase in demand. GCE also offers a placement policy that enables users to specify the location of underlying hardware instances. Sole-tenant nodes. These nodes are GCE servers dedicated to one tenant. They make it easier to deploy bring-your-own-license (BYOL) applications and allow the

Google Compute Engine (GCE) - SpringerLink

Shopping Assistant with RAG & AlloyDBThis demo adds a new service to Online Boutique called shoppingassistantservice which, alongside an Alloy-DB backed products catalog, adds a RAG-featured AI assistant to the frontned experience, helping users suggest products matching their home decor.Setup instructionsNote: This demo requires a Google Cloud project where you to have the owner role, else you may be unable to enable APIs or modify VPC rules that are needed for this demo.Set some environment variables.export PROJECT_NUMBER=export PGPASSWORD=">export PROJECT_ID=project_id>export PROJECT_NUMBER=project_number>export PGPASSWORD=pgpassword>Note: The project ID and project number of your Google Cloud project can be found in the Console. The PostgreSQL password can be set to anything you want, but make sure to note it down.Change your default Google Cloud project.gcloud auth logingcloud config set project $PROJECT_IDEnable the Google Kubernetes Engine (GKE) and Artifact Registry (AR) APIs.gcloud services enable container.googleapis.comgcloud services enable artifactregistry.googleapis.comCreate a GKE Autopilot cluster. This may take a few minutes.gcloud container clusters create-auto cymbal-shops \ --region=us-central1Change your Kubernetes context to your newly created GKE cluster.gcloud container clusters get-credentials cymbal-shops \ --region us-central1Create an Artifact Registry container image repository.gcloud artifacts repositories create images \ --repository-format=docker \ --location=us-central1Clone the microservices-demo repository locally.git clone \ && cd microservices-demo/Run script #1. If it asks about policy bindings, select the option None. This may take a few minutes../kustomize/components/shopping-assistant/scripts/1_deploy_alloydb_infra.shNote: If you are on macOS and use a non-GNU version of sed, you may have to tweak the script to use gsed instead.Create a Linux VM in Compute Engine (GCE).gcloud compute instances create gce-linux \ --zone=us-central1-a \ --machine-type=e2-micro \ --image-family=debian-12 \ --image-project=debian-cloud SSH into the VM. From here until we exit, all steps happen in the VM.gcloud compute ssh gce-linux \ --zone "us-central1-a"Install the Postgres client and set your default Google Cloud project.">sudo apt-get install -y postgresql-clientgcloud auth logingcloud config set project PROJECT_ID>Copy script #2, the python script, and the products.json to the VM. Make sure the scripts are executable.nano 2_create_populate_alloydb_tables.sh # paste contentnano generate_sql_from_products.py # paste contentnano products.json # paste contentchmod +x 2_create_populate_alloydb_tables.shchmod +x generate_sql_from_products.pyNote: You can find the files at the following places:kustomize/components/shopping-assistant/scripts/2_create_populate_alloydb_tables.shkustomize/components/shopping-assistant/scripts/generate_sql_from_products.pysrc/productcatalogservice/products.jsonRun script #2 in the VM. If it asks for a. Figure 4: Google Compute Engine (GCE) Icon 3.1 Google Compute Engine (GCE)IaaS. GCE is Google’s IaaS offering. With GCE you have the liberty of creating Virtual Machines, allocating CPU and Join the gce-discussion Google group to discuss Compute Engine with Google engineers and other users. Join the gce-announce Google group to get Compute Engine

The Fundamentals of Google Compute Engine (GCE)

RightScale dashboard, the server or instance nickname you entered in RightScale is over-written by the instance tag name (ec2:Name) from EC2 if one exists. Similarly, if you add a tag of the form ec2:Name= and then launch the server, the server/instance name displayed in the Dashboard will be synched with the tag value. Once the server instance is terminated, the original server/instance nickname you created in RightScale is re-established. Finally, if you begin managing a previously existing EC2 instance in RightScale, the server/instance name displayed in RightScale will be initially set to the value of the existing instance tag name (ec2:Name) in EC2.Add EC2 Tags in the RightScale DashboardIn the RightScale Dashboard, go to a deployment with an operational server and click on the running server.From the Info tab, scroll down to to the tags field.Click Edit Tags -- you will be able to remove the current tags of the instance as well as add tags.When adding an EC2 tag, make sure the syntax is name:predicate=value and the name is ec2. For example: ec2:stack=productionClick Add.The tag will be applied to the server and will can be viewable in the RightScale Dashboard as well as the AWS Management Console. Similarly, you can view and add RightScale and EC2 tags in the AWS Management Console that will influence your instance.GCE Instance TagsGoogle Compute Engine supports instance tags as plain strings which are commonly used for networking-related tasks -- these tags are synced with RightScale tags as well. When a tag is discovered in GCE, it is imported into RightScale with the tag namespace of gce. In order for a tag in RightScale to be synced to GCE, it similarly must have the namespace gce. All characters following the : after the namespace will be synced to GCE. For example, the tag gce:mytag will show in GCE as mytag. Since GCE tags support limited characters, if you attempt to create a tag in RS starting with gce: and then use any disallowed characters, you will get an error message and the tag will not be created.Note that in GCE, instance tags are used for a variety of purposes, including specifying Firewall Rules and network Routes. When modifying tags associated with an instance, take extra care in determining the network impacts of such a change.Azure Resource Manager (ARM) TagsThe following RightScale Resources support tag sync to the cloud: Placement Groups (Storage Accounts in ARM)Instances/Servers (Virtual Machines in ARM)Deployments (Resource Groups in ARM)When a tag is discovered in ARM, it is imported into RightScale with the tag namespace of azure. Likewise, a tag in RightScale will be synced to ARM if it has the namespace azure. All characters following the : after the namespace will be synced to ARM. For example, the RightScale tag azure:name=value will show in ARM as name:value and a tag in ARM of name:value will show in RightScale as azure:name=value.Please be aware that certain limitations exist with regards to tag length and limits on certain resources. For more information, see the Run Java applications natively without requiring a full Java Virtual Machine (JVM). This is accomplished through a custom runtime environment called Capstan.PricingOSv is a free and open source tool. Users can download OSv and run it locally or in the cloud via Amazon EC2 (elastic compute cloud) or Google Compute Engine (GCE).FeaturesIncludes the Jolokia JMX connector, an HTTP/JSON bridge for remote JMX access.Supports various language runtimes, including unmodified JVM, Python 2 and 3, Node.JS, Ruby, and Erlang.OS instances are deployable from a developer IDE or through a continuous integration system.Can run applications written in languages compiling directly to native machine code, such as C, C++, Golang, and Rust.ProsOffers an optional in-browser dashboard.OSv can be used for horizontal scaling.Fast boot time.ConsOSv is designed to run only one application at a time.ChromeOSBest for: Enterprises and dedicated ChromebooksChromeOS is a Linux-based, lightweight, web-based OS developed by Google on its open-source Chromium OS platform. It’s designed to work primarily with web apps and Chromebooks. It’s built around the Google Chrome web browser, uses the web browser as its primary interface, and is designed to provide users with a simple, secure, and fast computing experience. ChromeOS comes preinstalled on Chromebooks, but it’s also available as the web-based ChromeOS Flex for Windows and Mac PCs.Image: Google ChromeOS EnvironmentChromeOS is optimized for the web, with most apps and documents in the cloud. It also includes integrated media players, file managers, and access to the Google Play Store for downloading Android apps.PricingChromeOS (including ChromeOS Flex) is a free,

Google Compute Engine (GCE)- EngineeringHulk

HI Guys,Sorry about not posting the URL as I was in a hurry last night and I forgot to add it silly me .. Anyway here is the URL to my page for the firmware. You can also download MTKFLASH v1.55 from there as well. know this fellow that used this version of MTKFLASH v1.55 and has an LG 8480B Burner. But before he flashed his drive he had V1.02 firmware and then then he used my V1.03 and it worked and he is very happy with it. This is what he had to say.Hi, Well, I succeeded flashing my GCE-8480B to firmware 1.03... and did some tests. Basically it behaves *exactly the same* as 1.02 with my collection of 20 different blank CDR brands, except for one : The samsung digitall 32x CDRs, which were written at CAV 48x with firmware 1.02 and now are written at PCAV 40x (fw 1.03). I suppose it's because this brand/make has been added to the 'database' of CDRs the firmware knows. Since this firmware *probably* could have also other fixes, I'll live with it (i.e not going back to 1.02). I flashed the drive with MKTFLASH 1.55, command line : mktflash 3 W /B /M 8480B103.BIN (3 because my cdrw is secondary master) Note that having succeeded in this test (contrary to reports of mktflash not being able to flash this drives) opens two doors : 1) It is mostly important for USA people, because their 8480Bs are flashed with 1.10 fw, a special version *without* mount Rainier support. 2) Whenever we locate a GCE-8481B firmware, we now know how to try to flash ours and make this 48-16-48 become a 48-24-48 writer!! ... Anyone has a GCE-8481B and volunteers to get the firmware for us ? ........................ Thanks again for all CybaGirl. Regards FTCAnyway hope this helps some people out!RegardsErica

GCE GCE Moving Image Arts - CCEA

Security Command Center 보안 기능지난 글에서는 Security Command Center 주요 보안 기능 개요 및 활성화 방안을 살펴보았습니다. 이번에는 Security Command Center가 제공하는 보안 기능을 상세히 알아보겠습니다. Security Command Center가 제공하는 대표적인 기능은 다음과 같습니다. Google Cloud 자원의 중앙 집중방식의 가시성 및 제어 확보Google Cloud에서 운영하는 자원의 잘못된 구성 및 취약점 찾기Google Cloud 자원에서 발생하는 위협 감지Google Cloud 환경의 보안 컴플라이언스 규정 준수 및 유지ㅇ자원의 중앙 집중 방식의 가시성 및 제어 확보기업 전산 환경에서 어려운 일 하나는 운영 자산 목록을 최신상태로 관리하는 것입니다. 운영하는 서버 및 컴퓨터의 수량, 제품의 도입 시기, 업그레이드 시기 등을 파악하는 것입니다. 전산 환경의 규모가 크고, 많은 이기종 제품을 운영하고 있다면 이 업무는 1-2명이 해결할 수 있는 수준이 아닙니다. 운영 자산의 실제 목록은 정보보안에서도 매우 중요한 기본 자료입니다. 보안은 자산을 위협으로부터 보호하는 행위입니다. 그러므로 자산을 보호하려면 보호 대상을 먼저 목록화하고 개별 자원의 특성을 파악해야 합니다. 그 이후에 자산별 보안 취약점에 대응한다면 보안 정책을 수립하기 매우 용이합니다. Security Command Center는 Asset Inventory를 활용하여 사용자가 사용하는 자원 목록을 최신상태로 실시간에 가깝게 관리합니다. 자원은 Google Cloud에서 생성하거나 운영하는 모든 컴퓨팅 자원을 말합니다. VPC 네트워크, GCE(Google Compute Engine), 네트워크 로드 밸런서와 NAT를 위해 설정한 대표 IP 등이 모두 자원입니다. Security Command Center는 Google Cloud내에서 사용자가 생성한 자원을 유형별 또는 프로젝트별로 자동으로 구분하여 보여줍니다.[운영 자원 가시성 확보]예시 그림에서는 IP 주소인 Address 자원을 확인할 수 있습니다. 자원 이름, 자원 소유자, 생성 시간과 수정 시간을 필드에서 확인할 수 있습니다. 자원 유형별로 필드 구성이 다를 수 있습니다. 목록 우측 위를 클릭하여 필드 정보를 수정할 수 있으며, 자원별로 필드를 다르게 설정하거나 모든 자원에 일괄적으로 동일한 설정을 구성할 수 있습니다. 사용자가 자원을 새로 생성하거나 수정하는 경우에도 거의 실시간으로 변경 내역이 Asset Inventory에 반영됩니다. 개별 자원의 잘못된 구성 및 취약점 찾기사용자가 생성한 자원은 워크로드 실행, 데이터 저장 등 다양한 역할을 수행합니다. 하지만 올바른 구성을 갖지 않는 경우 보안 문제가 발생할 수 있습니다. Security Command Center는 위협 방지를 위해서 Security Health Analytics라는 보안 위협 탐지 기능을 제공합니다. 프리미엄 등급에서는 모든 취약점 탐지를 제공하지만 표준 등급에서는 위험도가 High인 항목만을 점검할 수 있습니다.Security Health Analytics의 개별 감지기는 Google Cloud에서 운영중인 자원의 위협을 스캔합니다. 스캔은 Security Command Center가 사용 설정된 후 약 1시간 후 시작되며 두 가지 모드(배치 모드, 실시간 모드)로 실행됩니다. 일괄 모드는 매일 2번 12시간 간격으로 자동으로 스캔이 실행되고 실시간 모드는 자원 구성 변경사항이 감지되는 경우 위협 방지 스캔을 실행합니다. API 접속에 사용하는 키가 90일 동안 변경되지 않았거나 HTTPS 대신 HTTP 로드 밸런서를 사용하거나, 가상머신에 인터넷 IP를 할당하는 등의 Google이 설정한 보안 취약점을 자동으로 점검하고 이를 관리자에게 알립니다. Security Health Analytics의 취약점 발견 항목 전체 목록은 이곳에서 확인할 수 있습니다.Cloud 자원의 취약점 외에도 Web Security Scanner를 사용하면 클라우드에서 운영하는 웹 애플리케이션의 취약점도 탐지할 수 있습니다. 표준 등급에서는 스캔 대상 URL을 사용자가 직접 등록해야 합니다. 등록후에 스캔 주기를 지정할 수 있습니다. 프리미엄등급에서는 1주일마다 스캔 대상 URL을 자동으로 점검한 후에 취약점 스캔까지 완료합니다. 클라우드 자원의 동작 중 위협 탐지클라우드 환경의 전체 자원 목록을 확보하고 개별 자원의 취약점을 탐지했습니다. 다음 단계로는 각 자원들이 동작하는 과정에서 발생하는 통신 로그 등을 기반으로 위협을 감지를 수행합니다. 이 기능은 컨테이너 위협 탐지(Container Threat Detection), 이벤트 위협 탐지(Event Threat Detection), 가상머신 위협 탐지(VM Threat Detection), 이상징후 탐지(Anomaly Detection)이. Figure 4: Google Compute Engine (GCE) Icon 3.1 Google Compute Engine (GCE)IaaS. GCE is Google’s IaaS offering. With GCE you have the liberty of creating Virtual Machines, allocating CPU and

Deploy CockroachDB on Google Cloud Platform GCE

For an OpenStack project using Ansible, I recently had to figure out how to make Ansible work with a jump host. After an initial phase of total confusion, I finally found my way through the documentation and various sources and ended up with several working configurations. This post documents what I have learned on that journey to hopefully make your life a bit easier.SetupIn my previous posts on Ansible, I have used a rather artificial setup – a set of hosts which all expose the SSH port on the network so that we can connect directly. In real world, hosts are often hidden behind firewalls, and a pattern that you will see frequently is that only one host in a network can directly be reached via SSH – called a jump host or a bastion host – and you need to SSH into all the other hosts from there.To be able to experiment with this situation, let us first create a lab environment which simulates this setup on Google’s cloud plattform (but any other cloud platform that has a concept of a VPC should do as well). First, we need a project in which our resources will live. For this lab, create a new project called terraform-project with a project ID like terraform-project-12345 (of course, you will not be able to use the exact same project ID as I did, as project IDs are supposed to be unique), for instance from the Google Cloud console under “Manage Resources” in the IAM & Admin tab.Next, create a service account for this project and assign the role “Compute Admin” to this account (which is definitely not the most secure setup and clearly not advisable for a production setup). Create a key for this service account, download the key in JSON format and store it as ~/gcp_terraform_service_account.jsonIn addition, you will need a private / public SSH key pair. You can reuse an existing key or create a new one usingssh-keygen -P "" -b 2048 -t rsa -f ~/.ssh/gcp-default-keyNow we are ready to download and run the Terraform script. To do this, open a terminal on your local PC and entergit clone ansible-samples/jumphostterraform initterraform apply -auto-approveWhen opening the Google Cloud Console after the script has completed, you should be able to verify that two virtual networks with two machines on them have been created, with a topology as summarized by the following diagram.So we see that there is a target host which is connected to a private network only, and a jump host which has a public IP address and is attached to a public network.One more hint: when playing with SSH, keep in mind that on the Ubuntu images used by GCE, sshguard