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Google Compute Engine

Google Compute Engine

Overview

What is Google Compute Engine?

Google Compute Engine is an infrastructure-as-a-service (IaaS) product from Google Cloud. It provides virtual machines with carbon-neutral infrastructure which run on the same data centers that Google itself uses.

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Recent Reviews

Great Service

9 out of 10
October 28, 2019
Incentivized
We use Google Compute Engine to host a variety of services including proxy servers, small websites, and peripheral services. Additionally, …
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Awards

Products that are considered exceptional by their customers based on a variety of criteria win TrustRadius awards. Learn more about the types of TrustRadius awards to make the best purchase decision. More about TrustRadius Awards

Popular Features

View all 9 features
  • Security controls (34)
    8.1
    81%
  • Operating system support (34)
    7.8
    78%
  • Pre-configured templates (32)
    5.2
    52%
  • Pre-defined machine images (33)
    4.5
    45%

Reviewer Pros & Cons

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Pricing

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Preemptible Price - Predefined Memory

0.000892 / GB

Cloud
Hour

Three-year commitment price - Predefined Memory

$0.001907 / GB

Cloud
Hour

One-year commitment price - Predefined Memory

$0.002669 / GB

Cloud
Hour

Entry-level set up fee?

  • No setup fee
For the latest information on pricing, visithttps://cloud.google.com/compute/pricin…

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting/Integration Services

Starting price (does not include set up fee)

  • $0 GB
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Product Demos

Google Compute Engine Load Balancing, a quick introduction

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Computing with Google Compute Engine

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RouterOS CHR deployment in Google Compute Engine (GCE) demo

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Creating Custom Images for Google Compute Engine

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Hands on with Load Balancing on Google Compute Engine

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Features

Infrastructure-as-a-Service (IaaS)

IaaS provides the basic building blocks for an IT infrastructure like servers, storage, and networking, in an on-demand model over the Internet

6.7
Avg 8.1
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Product Details

What is Google Compute Engine?

Google Compute Engine is an infrastructure-as-a-service (IaaS) product from Google Cloud. It provides virtual machines with carbon-neutral infrastructure which run on the same data centers that Google itself uses.

Predefined Machine Types
Virtual machine configurations for micro instances to instances with up to 160 vCPUs and 3.75 TB of memory

Custom Machine Types
Or create and customized, virtual machines with the shape (i.e. vCPU and memory) needed for each project

Persistent Disks
Network storage, up to 64 TB in size, can be attached to VMs as persistent disks. Create persistent disks in HDD or SSD formats. If a VM instance is terminated, its persistent disk retains data and can be attached to another instance. Take snapshots create new persistent disks from that snapshot.

Local SSD
Always-encrypted local solid-state drive (SSD) block storage. Local SSDs are physically attached to the server hosting the virtual machine instance. Local SSD sizes up to 3 TB are available for any VM with at least 1 vCPU.

Global Load Balancing
Distributes incoming requests across pools of instances across multiple regions.

Batch Processing
For running large compute and batch jobs using Preemptible VMs. Features fixed pricing and no contracts or reservations. Activated by checking a box when creating the VM, and then they can be turned off when the work is done.

Containers
For running, managing, and orchestrating Docker containers directly on Compute Engine VMs or with Google Kubernetes Engine.

Google Compute Engine Features

Infrastructure-as-a-Service (IaaS) Features

  • Supported: Dynamic scaling
  • Supported: Elastic load balancing
  • Supported: Pre-configured templates
  • Supported: Pre-defined machine images
  • Supported: Operating system support
  • Supported: Security controls

Google Compute Engine Technical Details

Deployment TypesSoftware as a Service (SaaS), Cloud, or Web-Based
Operating SystemsUnspecified
Mobile ApplicationNo

Frequently Asked Questions

Google Compute Engine is an infrastructure-as-a-service (IaaS) product from Google Cloud. It provides virtual machines with carbon-neutral infrastructure which run on the same data centers that Google itself uses.

Google Compute Engine starts at $0.004237.

Amazon Web Services, Microsoft Azure, and Amazon S3 (Simple Storage Service) are common alternatives for Google Compute Engine.

Reviewers rate Service-level Agreement (SLA) uptime and Security controls highest, with a score of 8.1.

The most common users of Google Compute Engine are from Small Businesses (1-50 employees).
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Comparisons

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Reviews and Ratings

(163)

Attribute Ratings

Reviews

(1-25 of 35)
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Score 7 out of 10
Vetted Review
Verified User
Incentivized
In our company, we primarily use Google Compute Engine to create VM instances that would power our website our testing environment and as a CI/CD tool.
The main purpose that help us decided to use Google Compute Engine was the cost and the ability to easily scale our instances to our needs.
  • Cost-effective
  • Scaling
  • Good-looking UI Dashboard
  • Documentation
  • Networking Configuration
Compute Engine is, in my opinion, very well advised if a scalable environment is needed.
Especially for those use cases where incoming traffic might change a lot in a time period.
Is it less appropriate instead if no high traffic is expected.
Score 8 out of 10
Vetted Review
Verified User
We use Google Compute Engine to run jenkins. This jenkins jobs do various tasks.
- Building products
- Running integration test
- Running accreditations tests
Before every release we set up a production grade deployment using Google Compute Engine and do performance test.
  • Running jenkins jobs
  • Running performance tests
  • Simulate a production environment before each release
  • GCE is only available only in three regions, They can add more regions.
  • Google can provide pricing model like AWS's reserved instances and spot instances .
  • They can improve the UI a bit better, when I get started I found it hard to get familier with the UI.
GCE is cost effective when compared to other cloud provider solutions. I would recommend a colleague GCE. When I ran same performance test on aws ec2 and Google GCE i got better numbers in GCE. It could be related our product but for performance tests i prefer using GCE.
Score 8 out of 10
Vetted Review
Verified User
We use it for microservices that has burst processing demands - they require lots of processing power for very short periods of time, thus requiring powerful hardware that, for most of the time, goes on without use. We wanted a cloud solution to avoid the hardware and infrastructure inherent to that scenario.
  • Better interface than AWS
  • Service has been very reliable
  • Excellent security policy structure
  • Documentation could be improved
  • Sometimes is hard to estimate how much we are going to spend
I would say that it is very helpful for scenarios with iregular processing power requirements, as situations where the application have burst of usage, or that have demands that change during the year or between the seasons. On the other hand, applications that have a very stable load can easily become too expensive for cloud usage.
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Most development servers and build machines are migrating into Google Cloud Compute engine. This allows us to spin up/down resources on demand based on workload, product needs, etc. QA does the same for testing resources.
  • Fast
  • Great CLI
  • Great APIs
  • gcloud CLI is very broad
  • Billing detail could get more finer grained
It's Google! Always strong for devs and engineers. Cost, seemingly cheaper than Azure and AWS, yes. In practice, who knows. Their APIs and CLI are strong enough to ensure this is definitely an 8 in recommendation.
Score 7 out of 10
Vetted Review
Verified User
Incentivized
My company uses Google Compute Engine to clean our "dirty" EDI files from the ports, terminals, and carriers that we work with for data cleansing services. We then put the cleansed files back into our dashboards for better visibility and to show potentially actionable insights for our customers.
  • Fast return of files.
  • Cost effective.
  • Good UI.
  • The document security has been an issue.
  • Not a lot of customization ability.
  • Customer service people weren't very knowledgeable.
If you have a prospective client who is currently using MS PowerBI, document security will be a really big deal. We are in the middle of trying to find a fixed gap for one of our government prospects. If secure documents aren't an issue for them, then it is fine.
Ye Yint Moe | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
I have used Google Compute Engine for testing and deploying SAP
S/4 Hana appliance for the internal training and learning purpose in Google cloud platform environment.
  • VM Instances
  • Storage
  • Bare metal solution
  • Quota limit for Compute Engine API Persistent Disk SSD
  • Quota limit for Compute Engine API A2 CPU
  • Quota limit for Compute Engine API N2 CPU
Google Compute Engine will be suited for the scenarios with the quota limit provided as default and less appropriate for the scenarios on deployments with quota limit increase request need to raise to Google Cloud support.
Score 8 out of 10
Vetted Review
Verified User
Incentivized
We use it as compute for external services outside our normal cloud as backups
  • UI
  • Integrations
  • Billing
  • Their UI is a bit clunky
  • Overcrowding on hosts
  • Locations
it is well suited for general compute, we use it more as a back up solution. In most workloads, it seems to be handling things just as it should.
Score 7 out of 10
Vetted Review
Verified User
Incentivized
We are using GCE to prototype new projects at scale for our customers. Unlike on premise infrastructure we can create servers at a moments notice and limited to just the timespan required. This saves us having to procure servers from our partnered procurement organisations which typically has a much longer lead time and hugely improves the overall time it takes to start a project.
  • Uptime
  • Automated backups
  • Strong security posture
  • Feature parity with other cloud providers
  • Total cost transparency
  • Free training
Works very well when you need scalability and quick infrastructure. As you start to scale it is important to evaluate other cloud services available to determine if there are greater advantages within the Google cloud platform offerings.
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Our specific department uses google cloud for its data analytics capabilities but also for its scalable and flexible virtual/compute infrastructure. We have some large jobs that we will provision ad-hoc compute to assist as needed. Google Compute Engine excels in this area and has never failed us.
  • Auto Scaling
  • Flexible Instance Sizes
  • Easy to understand pricing model
  • More inside the UI advanced capabilities would be nice
  • Customer is currently forced to learn the CLI to do advanced functions / scripting
  • Stability is just not the same as other cloud providers in our experience.
We use Google Compute Engine in a hybrid and multi-cloud solution. We find that using it for direct ad-hoc use cases meets all of our demands. We have attempted some more complex networking and multi-regional use cases but were not able to achieve satisfactory results. Google Compute Engine is extremely appropriate for anyone requiring quick, scalable, reliable infrastructure.
Manjeet Singh | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Google Compute Engine is being used across the company for all of the server needs. It lets us create VMs with a variety of customizable options. It does give us a predefined set of VMs that can be directly used based on needs. It also helps us to reduce the cost by using the right size of VMs.
  • It's very easy to spin up a VM from the console. We can say the console is very user-friendly.
  • Set of predefined VMs ready to be used for different needs.
  • Options of preemptible VMs which help reduce the considerable amount of cost.
  • Spin up takes some time and that's where containers come into the picture.
  • Setting up security for created VMs is still messy and it can be simpler.
GCE is well suited for the following scenarios. GCE is very easy to use, and we can navigate on the console easily for trying various options. Reasonable pricing for the VMs help to reduce the overall budget. Recommendations for running VMs to scale up or down. Set of predefined VM types. Preemptible instances.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
We use Google Compute Engine to support almost all of our in house computer. We have a web application that has a distributed backend of various workloads, all of which run on Compute Engine. Some of these workloads are even containerized. These workloads support the whole organization and provide analysis for research and development.
  • It can run containers.
  • It is completely flexible in terms of CPU, memory, etc.
  • It's APIs are useful for spinning up machines computationally.
  • Running multiple containers on one VM.
Google Compute Engine is suitable for any scenario that fits one of the pros I listed. It is very flexible and easily configurable. In many cases, VMs need to be spun up on the fly programmatically, and without orchestration software, one can accomplish this by using one of the APIs.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
We use Google Compute Engine across the organization along with other Google Cloud Platform Services. We have interconnected collections of Google Cloud Platform Services which include among these sets of services components deployed on the Google Compute Engine, which act as the backbone of multiple customer facing production deployments.<br><br>To be more precise we have one product which is a web app for monitoring and prediction of household energy consumption and household solar panel power generation. To implement this on GCP we are using numerous GCP services including Google Compute Engine but not limited only to GCE.<br><br>Additionally, we have another product which focuses on voltage optimization primarily for the purpose of conservation voltage reduction at a particular customer site (e.g. a substation controlling a factory, school, large building or facility, etc). The voltage optimization consists primarily of monitoring sensors and performing a near real-time prediction and optimization, and then providing recommended voltage levels for an OLTC controller. This particular deployment must occasionally be deployed on-site, however we also support production level cloud deployment. The cloud deployment will use Google Compute Engine to host a Docker environment, that mirrors the Docker environment that we set up on the machines for the onsite deployments. <br><br>We also use Google Compute engine in a number of prototype builds for testing the efficacy of data science and machine learning models and as a platform for quick collaboration during remote work. Though the number of such deployments are myriad, hence I will forgo the details.<br><br><br><br><br><br><br><br><br>
  • It is easy to use
  • It is easy to setup
  • Configuration and monitoring of the instances is straightforward and thorough
  • The configuration of ingress and egress for the nodes could be easier
  • Machine image storing, compression, etc. could be better or have more functionality
  • Transferring machine images to and from my local environment is something I have wanted on GCE and its competitors for a long time
I have recommended the platform to students, friends and family members alike. The help and documentation is very easy to follow for a beginner. Plus, GCP has built in tools which make some common tasks that non-production level cloud users need to accomplish very easy in an automated way.

Now, to address the question of recommending GCE to a colleague, ultimately the organization will have to make a decision regarding the entire cloud platform. It wouldn't make much sense, outside of a special case, to use GCE for some parts of your cloud infrastructure and a competitor on other parts.

That practical caveat aside, I believe that the GCP brings a strong suite of tools to the table overall and is good value for money at this time as well.

Developer familiarity to certain competing platforms can be a sticking point, but a colleague who is already asking for a recommendation is likely already open minded about moving to GCP.
Score 7 out of 10
Vetted Review
Verified User
Incentivized
For hybrid cloud solution we decided to use the separated cloud provider as a DR (pilot light model) in our project. Compute Engine was created in one Region with general purpose machine family. The project requirements were set - one of the first priorities - cloud provider independence.
  • Project base access.
  • Well tested DR scenario.
  • Competitive overall prices.
  • Less flexible machine type selection.
  • Sometimes non-intuitive interface.
  • Limited network configuration.
It is a stable service created by Google. The quality of service is good enough to create a full fledged production environment.
October 28, 2019

Great Service

Score 9 out of 10
Vetted Review
Verified User
Incentivized
We use Google Compute Engine to host a variety of services including proxy servers, small websites, and peripheral services. Additionally, we make use of the Google Compute Engine to quickly spin up instances for testing and experimentation and then destroy them once finished without incurring a lot of costs, both money and time.
  • GCE is well suited for multi-environment testing, development, and experimentation.
  • Very cost effective.
  • If you want to do something outside of a standard image it can be a little cumbersome.
Google Compute Engine is particularly well suited for multi-environment testing, development, and experimentation with the low cost of spinning up small instances along with the speed at which it can be done. It also does well hosting small websites and proxy servers that don't see a lot of network traffic.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Google Compute Engine (GCE) is used for most of the AI workload spanning both on-prem private cloud and public cloud. It is used for both onetime training phase for our Deep Learning workload as well as ongoing Deep Learning inference for customer facing applications.
  • East interface to scale up and down the compute capacity
  • Easy, straight forward billing and chargeback capabilities
  • Reliability / uptime is great and had no issues so far on uptime
  • Works well in multi cloud environments
  • Although not always used, there is room for adding more detailed and granular management console when things go wrong (and sometime they do)
  • Documentation can sometime be hard to find especially for using GCE for time critical, large scale deployments
  • There are also some compatibility issues when running custom libraries over GCE. Support for third party drivers and libraries can be improved.
GCE is very well suited to small to mid scale deployments. It is also run very well with AI workloads especially when using Google TenserFlow et al. It is less appropriate for extremest scale deployments that spam multiple data center (probably because of lack of document on best practices)
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Google Compute Engine is used for a variety of workloads. Its use is growing as larger parts of the organization start embracing cloud computing.
  • Internal applications.
  • Tools.
  • QA and testing environments.
  • Production deployment.
  • Experimentation with new technologies.
  • Migration from datacenter to cloud environments.
  • Training environments (they can be easily created and then deleted after the training).
  • Business processing.
  • Data processing and pipelines (in combination with various other products available in Google Compute Platform (GCP).
  • Easy and fast creation of the resource.
  • Rich ecosystem of tools and cloud technologies.
  • Ability to scale up and down, based on the needs.
  • Better documentation.
  • Up to date documentation.
  • Capabilities on par with AWS.
Google Compute Engine is well suited for:
  • All situations where one needs to allocate compute capability. Google Compute Engine offers a variety of server configuration and one should be able to find a matching configuration, except for largest servers or mainframes. This still may be the case for large relational databases in enterprises.
Google Compute Engine is less well suited for:
  • Processing confidential information if the organization does not master security in cloud environments. One cannot simply transplant an application from a private data center to the cloud and expect the same security. Security needs to be designed and implemented from the start.
  • Period workloads processing events. For that, consider Serverless/Function as a Service which is also a offering on Google Compute Platform.
Brendon Brown | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User
Incentivized
We use Google Compute Engine for staging deployments in the web development department. We are operating off an external assessment that competitor services offer better pricing on production units, so we've agreed to keep Compute Engine in a low tier staging system only. We have yet to do our own audit from an internal efficiency perspective, and how that will impact pricing assessments.
  • Compute Engine is gaining traction, and documentation is getting easier to find.
  • Menus and services are structured more intelligently.
  • The idea of poor Support from the Google brand prevents my technicians from picking up the phone.
  • It's easier to find EC2 experts to consult and support mission-critical operations.
In my opinion, most cloud applications should consider Google Compute Engine from a speed and pricing perspective. Of course, you should do an assessment based on what your application needs to do and how it needs to perform, but there's a machine for most kinds of deployments. If you have the expertise nearby, all the better.
Score 10 out of 10
Vetted Review
Verified User
Incentivized
Using Google Compute Engine, you can manage your costs. It helps to avoid the high costs of buying hardware and setting up a new server infrastructure on your physical location. Also, Google Computer Engine offers you the possibility of accessing your files and data with higher security, and save days worth of time spent on setup and installation. We migrated from hardware to visualized servers hosted to Google Compute Engine. We made Windows and Linux servers and hostel our core-services: ERP, accounting, marketing app.
  • Access files and data with higher security.
  • Easy to manage.
  • Create virtual machines very easily.
  • Google Compute Engine is user-friendly.
  • The price is good.
  • Documentation can be more detailed.
  • More costs options.
  • No other recommendations.
Google Compute Engine offers you the possibility to scale your computing resources up or down quickly. Is a flexible solution that can be utilized by everyone who wants to manage software without having to worry about hardware. It's easy to create servers, and can connect to servers by RDP or SSH. It's a great choice for small and big organizations. We migrated all our critical servers from hardware to visualized servers and we reduced our cost significantly. It is more efficient to migrate you ERP to virtualization server to Google Compute Engine that on your hardware.
Thomas Young | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Google Cloud Compute Engine is used by the organization to do automated advanced analytics for clients across the world. The software addresses two important aspects of our business: first, it runs in the background and with speed and accuracy that works well for the analyst as well as others; second, the software runs in the cloud, which makes analyzing the data generally easier.
  • Google Cloud Compute Engine does a good job at crunching numbers.
  • Google Cloud Compute Engine is great at always being available, and I have yet to find any latency.
  • Google Cloud Compute Engine is great for doing advanced analytics (machine learning) without needing the software on my desktop.
  • Google Compute Engine is in the cloud, which means that it is probably less secure than on-premise options. With that said, I have never had a problem.
  • Google Compute Engine seems fine at running machine learning models, but is in no way as good as competing tools that are not run in the cloud.
  • Google Compute Engine is less user friendly than AWS or Azure, at least that's my experience.
Google Cloud Compute Engine is well suited for companies doing advanced analytics, including machine learning and artificial intelligence. The software is less useful for smaller companies with only small data sets available for analysis. The software works well if you need instant access from anywhere in the world and if you are used to the Google infrastructure.
Tristan Dobbs | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
ResellerIncentivized
We use compute engine across a number of departments at our company. We deploy temporary workloads to VMs on a daily basis and have deployed our production systems to GCE for deployment and CI/CD pipelines, ETL for data projects, and for large-scale customer engineering.
GCE is in play primarily for our engineering department as well as our customer engineering and sales teams.
  • GCE is excellent at cost management. We are able to manage billing to the second and set up rules to manage those expenses easily.
  • GCE is fast! Our teams constantly provision/de-provision workloads and GCE is able to keep up well, no matter the type or number of servers that need to be spun up.
  • The configuration is extremely easy. The UI is being improved and tweaked on a regular basis to keep up with UI/UX trends and make it easy for users to do everything from the console. That said, the API is extensive and powerful. Many of us prefer the CLI for bulk actions.
  • Windows management is lacking. When managing a Windows machine, it's nearly always necessary to RDP into the machine and an agent would be very helpful for system-level API calls.
  • Stackdriver integration could be rolled out better. We would like to see more standard monitoring functionality and metrics built-in for instant deployment when using a new project.
  • Inter-project organization. It's difficult to connect different GCP projects in order to share a VPC. Once that is complete, it's nearly impossible to extricate them.
GCE is so customizable and extensible that it can fit most use cases and applications. Costs are excellent and it has become the most useful tool in our collection to deploy products, test scenarios, migrate workloads, and move out of the "server room". Ease of management cost control and customization are the biggest wins with GCE.
Score 10 out of 10
Vetted Review
Verified User
Incentivized
The big advantage of using Google Computer Engine is that pricing is much less than if you bought your own hardware. You are only paying for what you need, there's no over-spend required for redundant systems. Google Compute Engine is one of the best IaaS cloud solution at the moment.

  • Provides resizable compute capacity
  • Great scalability and elasticity
  • Very customizable
  • Generous free tier
  • Some loading issues
  • Setup can be tricky
  • No other problems
You can use Google’s web services to build a highly customized solution to meet all your company’s needs. Very easy to build, test, deploy and manage applications and services though their data centers. Google Compute Engine gives you the freedom to move away from having your servers based on premises which can reduce costs.
Vinicius Lima | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Incentivized
We use Google Compute Engine as IaaS provider across the whole organization. Almost all of our servers are deployed in this environment. We also help some of our customers to deploy virtual machines due to our expertise in cloud computing. We think it is a reliable platform that delivers everything we need regarding IaaS.
  • A friendly and intuitive graphical interface is available
  • There are several resources available, such as networking and snapshots.
  • The performance is amazing and you can select the region/zone close to your region.
  • There is a shell environment that helps a lot
  • Better price for Windows Server virtual machines
  • The graphical interface to manage a specific VM could be improved.
As any IaaS provider, Google Compute engine is suitable for any kind of companies, from small to large ones. You can easily create new servers and start configuring it in minutes. Usually, the prices are lower when comparing with buying a local server. Furthermore, Google Compute Engine is integrated with other services from Google Cloud platform.
June 29, 2019

Google delivers

Score 9 out of 10
Vetted Review
Verified User
Incentivized
Google Compute Engine is used by the DevOps team for hosted Windows servers. This alleviates countless concerns with having a server on-site, and is very comparable to other hosting providers.
  • We are able to select a custom amount of vCPU and Memory resources.
  • It provides pricing estimates on the page when configuring a new instance (versus having to reference separate documentation).
  • We are able to tie into G-Suite User Directory for access control to the Google Compute Engine console.
  • It would be nice to move a Google Compute Engine Server to a different project without having to recreate it.
Google Compute Engine is very similar to AWS EC2, and in most of the same regions, but also in a couple of additional geographic locations. So if proximity is crucial, there are some additional options with GCE over AWS EC2.
Score 8 out of 10
Vetted Review
Verified User
Incentivized
We use Compute Engine for one of our main consumer and business products. We have a globally distributed infrastructure for this. I believe we are using almost all the features/functionalities offered by GCE. e.g Instance, groups/templates with full rolling updates capability coupled with CI/CD. We also host part of our monitoring systems in GCE. Other than that, some other teams are on the POC phase for some critical backend products as well. Moreover, we experiment with some of our machine learning on Compute Engine. The benefit we get by using GCE is the combination of the autoscaling, rolling updates, preemptability, and global network.
  • Advanced autoscaling logic to cater scenarios that involve high load at the global level.
  • Seamless and reliable rolling updates with support for releases.
  • Backup data via very fast snapshots helps to quickly back up systems
  • Good support for things like metadata (pre-defined and custom).
  • Ability use Windows client OS VMs (or support import capability)
  • Increase the offered default monitoring metrics set.
  • Adjustable shutdown cooldown period (instead of fixed 30 seconds window).
Suited: Compute Engine is really good for any monolith type services which you need to host a service globally. And it works very well. Not Suited: autoscaled services that have long/heavy post-processing activity during termination.
Fedor Paretsky | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User
Incentivized
We use Google Compute Engine for creating cloud virtual machines that are GPU-accelerated. Because we have centralized most of our backend services to DigitalOcean, we use Google Compute Engine for most of the services that DigitalOcean doesn't offer. Additionally, we use the custom image functionality that GCE offers to create VMs with custom images.
  • Great scalability. The cloud VMs all have elastic specs functionality, but re-scaling some VMs may create a significant amount of downtime for your backend.
  • GPU offerings. Google Cloud offers NVIDIA Tesla K80s, P4s, and P100s, which some of the cloud computing competitors don't offer.
  • Downtime, Google's SLA is very good. I've never had a poor experience with downtime or maintenance on their services.
  • Internet speed can be quite variable. The bandwidth for different instances ranges a lot. Some instances have had internet bandwidth that is in the range of 5-10x the speed of other instances.
  • Customizability. Customizing the number of cores, RAM beyond what Google offers in their standard compute plans can get quite expensive.
  • Firewalls/networking. Figuring out how to use these took way longer than necessary. Getting the right ports opened and forwarded took lots of reading, something that other services included in the creation/initialization process of virtual machines.
For companies that require GPU-accelerated instances, GCE may be your only good option. They offer a lot of services that aren't available at the next best cloud computing platform (in my opinion), DigitalOcean. Beyond the functionality, the UI and documentation can be approved a lot, but if you're used to the way Google designs their developer tools and APIs, then you're probably all set with moving forward with Google's Compute Engine.
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