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Google Compute Engine

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Compute Engine
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Google Compute Engine is Google’s Infrastructure-as-a-Service virtual machine offering. It allows customers to use virtual machines in the cloud as server resources instead of acquiring and managing server hardware. Google Compute Engine offers virtual machines running in Google’s data centers connected to the worldwide fibre network. The tooling and workflow offered by compute engine enable scaling from single instances to global, load-balanced cloud computing.

Applications Of Compute Engine

Virtual Machine (VM) migration to Comput Engine: It provides tools to fast-track the migration process from on-premise or other clouds to GCP. If a user is starting with the public cloud, then they can leverage these tools to seamlessly transfer existing applications from their data center, AWS, or Azure to GCP. Users can have their applications running on Compute Engine within minutes while the data migrate transparently in the background.

Genomics Data Processing: Processing genomic data is computationally-intensive because the information is enormous with vast sets of sequencing. With the Compute Engine’s potentials, users can process such large data sets. The platform is not only flexible but also scalable when it comes to processing genomic sequences.

 Use-case

BYOL or Bring Your Own License images: A Compute Engine can help you run Windows apps in GCP by bringing their licenses to the platform as either license-included images or sole-tenant nodes. When users migrate to GCP, they can flexibly optimize their license and promote the bottom line.

Compute Engine- BOYL use-case

Advantages Of Compute Engine

  • Storage Efficiency: The persistent disks support up to 257 TB of storage which is more than 10 times higher than what Amazon Elastic Block Storage (EBS) can accommodate. The organizations that require more scalable storage options can go for Compute Engine
  • Cost: Within the GCP ecosystem, users pay only for the computing time that they have consumed. The per-second billing plan is used by the Google compute engine.
  • Stability: It offers more stable services because of its ability to provide live migration of VMs between the hosts.
  • Backups: Google Cloud Platform has a robust, inbuilt, and redundant backup system. The Compute Engine uses this system for flagship products like Search Engine and Gmail.
  • Scalability: It makes reservations to help ensure that applications have the capacity they need as they scale.
  • Security: Google Compute Engine is a more secure and safe place for cloud applications.

Benefits Of Compute Engine

  • Easy Integration: It allows to easily integrate with other Google Cloud services like AI/ML and data analytics.
  • Compute globally as per requirement: Rendering reservations for supporting and securing applications having the strength as per measurement and requirement.
  • Gain Infinite Value: Preventing cost only for executing Compute with sustained-use discounts, and obtaining huge profits while implementing devoted-use discounts.
  • Confidential Computing: Confidential VMs is a kind of advanced technology that enables users to encode delicate data into the cloud while data is being processed.

Machine Types

It describes the virtual hardware that is attached to an instance which also includes RAM and CPUs. There are two types of machines:

Predefined Machine Types: These are pre-configured virtual machine templates that can be used to set up the virtual machines. The configurations have been pre-optimized by Google and meet most of the requirements. The predefined machine types are divided into four categories:

  • Standard VMs
  • High-memory VMs
  • High-CPU VMs
  • Shared-core VMs

Compute Engine machine types

Custom Machine Types: The virtual hardware can be configured manually for a Compute Engine VM instance. Users can select the number of virtual CPUs (vCPUs) and memory, provided they are within Google’s set limits.

Persistent Disks

These are durable, high-performance block storage for VM instances which can be created in HDD or SSD formats. Users can take snapshots and create new persistent disks from that snapshot. If a VM instance is terminated, the data is retained by the persistent disk which can be attached to another instance. There are two types of persistent disks:

  • Shared
  • SSD

Local SSD

Google Compute Engine offers always-encrypted local solid-state drive (SSD) block storage which is physically attached to the virtual machine running it. It improves performance and reduces latency.

GPU Accelerators

GPUs are added to accelerate computationally intensive workloads like machine learning, virtual workstation applications, etc.

Images

An image contains the OS and the root file system that users leverage to run VM instances. Google Cloud Platform provides two main types of images:

Public Images: These are a collection of open-source and proprietary options. They serve as a starting point for most virtual machine instances and come packaged with only the operating system.

Custom Images: Public images are a good starting point, but they are designed to be built upon and turned into custom images to match the needs of the customers. A custom image has the software needed along with all the scripts necessary for the instance to work automatically without administrator intervention. These are automatically brought up and shut down for load balancing or recovery needs.

Global Load Balancing

It helps in distributing incoming requests across pools of instances across multiple regions so that users can achieve maximum performance, throughput, and availability at a low cost.

Similarly, there are many other features like Linux and Windows support, container support, reservations, OS patch management, Live migration for VMs, and many more.

Google Compute Engine has many pros such as fast I/O, less access time, smooth integration with other Google services, and few cons as well like most components are based on proprietary technologies and the choice of programming languages is limited. But it offers scale, performance, and value that allows users to launch quickly large compute clusters on Google’s infrastructure.

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