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    Google Cloud Containers: Top 3 Options for Containers on GCP

    Learn about the top three services that can help you run containerized applications on the Google Cloud Platform.

    Google Cloud Storage

    Google Cloud Containers: Top 3 Options for Containers on GCP

    October 24, 2021

    Topics: Cloud Volumes ONTAP, DevOps, Google Cloud, Elementary

    How Can You Run Containers in Google Cloud?

    Google provides several technologies you can use to run containers in Google Cloud environments. Here are the most commonly used services:

    Google Kubernetes Engine (GKE)—a managed Kubernetes service that lets you run Kubernetes clusters on Google Cloud infrastructure. You can use the standard options, which let you configure nodes, or the autopilot option, which automatically oversees the entire cluster and node infrastructure. Google Anthos—a hybrid and cloud-agnostic container environment management platform. The service lets you replace virtual machines (VMs) with container clusters to create a unified environment across public cloud and on-premises data centers. Google Cloud Run—serverless computing management platform for your container resources. Cloud Run can scale deployments to fulfill traffic demands and can integrate with various tools in your containerization stack, including Docker.

    Google Cloud provides additional tools to support flexible deployment and CI/CD pipelines, such as:

    Knative, an open-source project for deploying Kubernetes cloud applications on-premises

    Google Cloud Code for debugging and authoring code

    Google Cloud Build to allow for CI/CD

    Google’s Artifact Registry for image and package management

    This is part of our series of articles about Google Cloud Storage.

    In this article:

    Google Kubernetes Engine

    Google Anthos Google Cloud Run

    Google Cloud Tools for Containers

    Google Cloud Build Artifact Registry

    Google Cloud Containers with NetApp Cloud Volumes ONTAP

    Google Kubernetes Engine

    Google Kubernetes Engine (GKE) is a managed Kubernetes service run by Google Cloud Platform (GCP). It allows you to host highly scalable and available container workloads. There is also a GKE sandbox option available, which is useful if you have to run workloads that are susceptible to security threats—the sandbox lets you run them in an isolated environment.

    GKE clusters may be deployed as regional and multi-zonal, to safeguard workloads from cloud outages. GKE also has many out-of-the-box security attributes, including vulnerability scanning and data encryption for container images—this is enabled via integration with the Container Analysis service.

    The amount of responsibility, control and flexibility that you need for your clusters will determine the type of operation you will need to use in GKE. GKE clusters feature two types of operations:

    Autopilot—oversees the whole cluster and node infrastructure for you. Autopilot offers a hands-off Kubernetes process, which lets you attend to your workloads and only pay for the resources you need to run your applications. Autopilot clusters are pre-configured using an optimized cluster configuration, which is equipped for production workloads.

    Standard—offers node configuration flexibility and total control when managing your node and cluster infrastructure. For clusters developed using the Standard mode, you decide the configurations required for your production workloads, and you are charged for the nodes that you use.

    As is the case with other cloud service providers and managed Kubernetes service providers, GKE provides automated upgrades, repair of faulty notes, and on-demand scaling. It may also be integrated with GCP monitoring services for detailed visibility into the functioning of deployed applications.

    If you aim to host HPC, graphic-intensive or ML workloads, you may augment GKE via specialized hardware accelerators such as TPU and GPU during deployment.

    Google Anthos

    Google Cloud Anthos is a cloud-agnostic, hybrid container environment. It lets organizations utilize container clusters rather than cloud virtual machines (VMs), which makes it possible to run workloads in a uniform manner across public clouds and on-premises data centers.

    Not all organizations will want to get rid of their existing infrastructure. This multi-cloud platform provides organizations with the possibility of using cloud technology, including Kubernetes clusters and containers, with their current internal hardware.

    Anthos provides a consistent series of services and design for both in-cloud and on-premises deployments. This affords an organization the freedom to select where to send applications, in addition to migrating workloads from environment to environment.

    Google Cloud Anthos is developed using several systems, but Anthos’ core is a container cluster which is overseen by Google Kubernetes Engine. To allow for hybrid environments, Google Cloud Anthos has a GKE On-Premises environment and the Google Kubernetes Engine managed container service—this packages the same series of security and management features.

    You can also register current non-GKE clusters with Anthos. GKE on AWS assists with multi-cloud situations, where a compatible GKE environment in AWS may be developed, updated or deleted via a management service from Anthos’ UI. In addition, Service Mesh and Anthos Config Management solutions assist with security management, policy automation and visibility into applications you run across multiple clusters, which makes management easier.

    स्रोत : bluexp.netapp.com

    What are containers?

    Containers are lightweight packages of software that contain all of the necessary elements to run in any environment.

    What are Containers?

    Containers are packages of software that contain all of the necessary elements to run in any environment. In this way, containers virtualize the operating system and run anywhere, from a private data center to the public cloud or even on a developer’s personal laptop. From Gmail to YouTube to Search, everything at Google runs in containers. Containerization allows our development teams to move fast, deploy software efficiently, and operate at an unprecedented scale. We’ve learned a lot about running containerized workloads and we’ve shared this knowledge with the community along the way: from the early days of contributing cgroups to the Linux kernel, to taking designs from our internal tools and open sourcing them as the Kubernetes project.

    Google Cloud is a Leader in The Forrester Wave™: Public Cloud Container Platforms, Q1 2022

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    Containers defined

    Containers are lightweight packages of your application code together with dependencies such as specific versions of programming language runtimes and libraries required to run your software services.

    Containers make it easy to share CPU, memory, storage, and network resources at the operating systems level and offer a logical packaging mechanism in which applications can be abstracted from the environment in which they actually run.

    What are the benefits of containers?

    Separation of responsibility

    Containerization provides a clear separation of responsibility, as developers focus on application logic and dependencies, while IT operations teams can focus on deployment and management instead of application details such as specific software versions and configurations.

    Workload portability

    Containers can run virtually anywhere, greatly easing development and deployment: on Linux, Windows, and Mac operating systems; on virtual machines or on physical servers; on a developer’s machine or in data centers on-premises; and of course, in the public cloud.

    Application isolation

    Containers virtualize CPU, memory, storage, and network resources at the operating system level, providing developers with a view of the OS logically isolated from other applications.

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    Containers vs. VMs

    You might already be familiar with VMs: a guest operating system such as Linux or Windows runs on top of a host operating system with access to the underlying hardware. Containers are often compared to virtual machines (VMs). Like virtual machines, containers allow you to package your application together with libraries and other dependencies, providing isolated environments for running your software services. As you’ll see below, however, the similarities end here as containers offer a far more lightweight unit for developers and IT Ops teams to work with, carrying a myriad of benefits.

    Containers are much more lightweight than VMs

    Containers virtualize at the OS level while VMs virtualize at the hardware level

    Containers share the OS kernel and use a fraction of the memory VMs require

    What are containers used for?

    Containers offer a logical packaging mechanism in which applications can be abstracted from the environment in which they actually run. This decoupling allows container-based applications to be deployed easily and consistently, regardless of whether the target environment is a private data center, the public cloud, or even a developer’s personal laptop.

    Agile development

    Containers allow your developers to move much more quickly by avoiding concerns about dependencies and environments.

    Efficient operations

    Containers are lightweight and allow you to use just the computing resources you need. This lets you run your applications efficiently.

    Run anywhere

    Containers are able to run virtually anywhere. Wherever you want to run your software, you can use containers.

    Related products and services

    Backed by the same expertise that developed Kubernetes, Google Kubernetes Engine (GKE), the first production-ready managed service for running containerized applications, can help you implement a successful Kubernetes strategy for your cloud workloads.

    With Anthos, Google offers a consistent Kubernetes experience for your applications across on-premises and multiple clouds. Using Anthos, you get a reliable, efficient, and secured way to run Kubernetes clusters, anywhere.

    Google Kubernetes Engine

    Easy to use and trusted Kubernetes service to run apps on containers.

    Cloud Build

    Quickly build, test, and deploy your apps on containers.

    Cloud Run

    Write code your way using your favorite languages and deploy your apps on containers.

    Container Registry

    Store, manage, and secure your Docker container images.

    Cloud Code

    Integrated development environment to write, run and debug your containerized apps.

    Deep Learning Containers

    Containers with data science frameworks, libraries, and tools.


    Cloud-native app development

    Build, run, and operate cloud-native apps using containers in Google Cloud.


    Modernize apps with Anthos

    स्रोत : cloud.google.com

    What are cloud containers and how do they work?

    Explore how cloud containers, a lightweight virtualization technology for a single application, offer a secure way to deploy apps regardless of environment.



    FEATURE 1 OF 5

    Part of: The ins and outs of containers and container security

    What are cloud containers and how do they work?

    What are cloud containers and how do they work? Containers in cloud computing have evolved from a security buzzword. Deployment of cloud containers is now an essential element of IT infrastructure protection.

    Rob Shapland, Falanx Cyber

    Ben Cole, Executive Editor

    Kyle Johnson, Technology Editor

    Cloud containers remain a hot topic in the IT world in general, especially in security. The world's top technology companies, including Microsoft, Google and Facebook, all use them. For example, Google said everything it has runs in containers, and that it runs several billion containers each week.

    Containers have seen increased use in production environments over the past decade. They continue the modularization of DevOps, enabling developers to adjust separate features without affecting the entire application. Containers promise a streamlined, easy-to-deploy and secure method of implementing specific infrastructure requirements and are a lightweight alternative to VMs.

    How do cloud containers work?

    Container technology has roots in partitioning and chroot process isolation developed as part of Linux. The modern forms of containers are expressed in application containerization, such as Docker, and in system containerization, such as Linux Containers (LXC). Both enable an IT team to abstract application code from the underlying infrastructure to simplify version management and enable portability across various deployment environments.

    Containers rely on virtual isolation to deploy and run applications that access a shared OS kernel without the need for VMs. Containers hold all the necessary components, such as files, libraries and environment variables, to run desired software without worrying about platform compatibility. The host OS constrains the container's access to physical resources so a single container cannot consume all of a host's physical resources.

    The key thing to recognize with cloud containers is that they are designed to virtualize a single application. For example, you have a MySQL container, and that's all it does -- it provides a virtual instance of that application. Containers create an isolation boundary at the application level rather than at the server level. This isolation means that, if anything goes wrong in that single container -- for example, excessive consumption of resources by a process -- it only affects that individual container and not the whole VM or whole server. It also eliminates compatibility problems between containerized applications that reside on the same OS.

    Major cloud vendors offer containers-as-a-service products, including Amazon Elastic Container Service, AWS Fargate, Google Kubernetes Engine, Microsoft Azure Container Instances, Azure Kubernetes Service and IBM Cloud Kubernetes Service. Containers can also be deployed on public or private cloud infrastructure without the use of dedicated products from a cloud vendor.

    There are still key questions that need answers: How exactly do containers differ from traditional hypervisor-based VMs? And, just because containers are so popular, does it mean they are better?

    Cloud containers vs. VMs

    The key differentiator with containers is the minimalist nature of their deployment. Unlike VMs, they don't need a full OS to be installed within the container, and they don't need a virtual copy of the host server's hardware. Containers can operate with a minimum amount of resources to perform the task they were designed for -- this can mean just a few pieces of software, libraries and the basics of an OS. This results in being able to deploy two to three times as many containers on a server than VMs, and they can be spun up much faster than VMs.

    Cloud containers are also portable. Once a container has been created, it can easily be deployed to different servers. From a software lifecycle perspective, this is great, as containers can quickly be copied to create environments for development, testing, integration and production. From a software and security testing perspective, this is advantageous because it ensures the underlying OS is not causing a difference in the test results. Containers also offer a more dynamic environment as IT can scale up and down more quickly based on demand, keeping resources in check.

    One downside of containers is the problem of splitting your virtualization into lots of smaller chunks. When there are just a few containers involved, it's an advantage because you know exactly what configuration you're deploying and where. However, if you fully invest in containers, it's quite possible to soon have so many containers that they become difficult to manage. Just imagine deploying patches to hundreds of different containers. If a specific library needs updating inside a container because of a security vulnerability, do you have an easy way to do this? Problems of container management are a common complaint, even with container management systems, such as Docker, that aim to provide easier orchestration for IT.

    Containers are deployed in two ways: either by creating an image to run in a container or by downloading a pre-created image, such as from Docker Hub. Although Docker is by far the largest and most popular container platform, there are alternatives. However, Docker has become synonymous with containerization. Originally built on LXC, Docker has become the predominant force in the world of containers.

    स्रोत : www.techtarget.com

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