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Google Compute Engine

Google Compute Engine


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

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Scalability Feature: Users have commended the flexibility of Google Compute Engine's scalability feature, enabling them to easily adjust …
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Popular Features

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  • Operating system support (51)
  • Security controls (51)
  • Pre-defined machine images (50)
  • Pre-configured templates (49)

Reviewer Pros & Cons

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Preemptible Price - Predefined Memory

0.000892 / GB


Three-year commitment price - Predefined Memory

$0.001907 / GB


One-year commitment price - Predefined Memory

$0.002669 / GB


Entry-level set up fee?

  • No setup fee
For the latest information on pricing, visit…


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

Google Compute Engine Load Balancing, a quick introduction


Computing with Google Compute Engine


RouterOS CHR deployment in Google Compute Engine (GCE) demo


Creating Custom Images for Google Compute Engine


Hands on with Load Balancing on Google Compute Engine

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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

Avg 8.1
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Product Details

What is Google Compute Engine?

Virtual machines for any workload

Online VMs on high-performance, reliable cloud infrastructure offered on preset or custom machine types for web servers, databases, or AI.

Includes one e2-micro VM instance, up to 30 GB storage, and up to 1 GB of outbound data transfers free per month.

Preset and custom configurations

Prebuilt samples called Jump Start Solutions can be used to deploy an application in minutes, such as a dynamic website, load-balanced VM, Java application, three-tier web app, or ecommerce web app.

Offers predefined machine types, sizes, and configurations for any workload, from large enterprise applications, to modern workloads (like containers) or AI/ML projects that require GPUs and TPUs.

For more flexibility, a custom machine type between 1 and 96 vCPUs with up to 8.0 GB of memory per core can be created. Also offers many block storage options, from flexible Persistent Disk to high performance and low-latency Local SSD.

Industry-leading reliability

Compute Engine boasts strong single instance compute availability SLA: 99.95% availability for memory-optimized VMs and 99.9% for all other VM families. Offers live migration to maintain workload continuity during planned and unplanned events. When a VM goes down, Compute Engine performs a live migration to another host in the same zone.

Automations and recommendations for resource efficiency

VMs can be added automatically to handle peak load and replace underperforming instances with managed instance groups.

Resources can be manually adjusted using historical data with rightsizing recommendations, or capacity for planned demand spikes can be guaranteed with future reservations. All of Google's latest compute instances (C3, A3, H3) run on Titanium, a system of purpose-built microcontrollers and tiered scale-out offloads to improve infrastructure performance, life cycle management, and security.

Pricing and discounting

Google offers detailed pricing guidance for any VM type or configuration, and a pricing calculator to get a personalized estimate.

To save on batch jobs and fault-tolerant workloads, Spot VMs are offered to reduce costs. Automatic discounts for sustained use are offered, or up to 70% off when signing up for committed use discounts.

Security controls and configurations

Encrypts data-in-use and while it’s being processed with Confidential VMs.

Defends against rootkits and bootkits with Shielded VMs.

Meets compliance standards for data residency, sovereignty, access, and encryption with Assured Workloads.

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 Screenshots

Screenshot of How to choose the right VM
With thousands of applications, each with different requirements, which VM is right for you?Screenshot of documentation, guides, and reference architectures
Migration Center is Google Cloud's unified migration platform with features like cloud spend estimation, asset discovery, and a variety of tooling for different migration scenarios.

Google Compute Engine Videos

Compute Engine in 2 minutes
What is Compute Engine?

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.

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

Reviewers rate Dynamic scaling highest, with a score of 8.4.

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


Attribute Ratings


(1-25 of 51)
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Ananth Suryanarayana | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User
We use Google Compute Engine (GCP) for compute (Virtual Machines) and GKE. Our use case is to provide seamless multi-cloud network connectivity between on-premise networks and Google Compute Engine VPC Network. My switching between on-premise and cloud resources, we aim to optimize cloud cost as well to enterprise customers.
  • Scalable rich set of platforms to run Virtual Machines
  • Seamless multi-region network connecitivity
  • Complete automation support via Terraform
  • Unstable GUI
  • Bare Metal Servers
Scalability is key aspect of Google Compute Engine (GCP). When in need to launch 100s of machines, Google Compute Engine (GCP) does really well. Google buckets is another excellent service we use to manage storage.
Score 9 out of 10
Vetted Review
Verified User
For a very long period, we have been utilising Google Compute Engine. Our application data is hosted on virtual machines that we have been building.We have utilised it to host Vector Databases in addition to our front-end and back-end databases.For even quicker processing, we have been employing the virtual machines offered by the TPU, and the greatest part is that they are always 100% up and running.
  • Hosting application frontend, backend, or any such things in your Virtual machine.
  • As we know today's generation is about GenAI, and vector stores are a huge part of it, computer engines are also able to host the Vector DB's.
  • The security scans provided by the compute engine are also very good and helpful.
  • The snapshots feature is also amazing, if you want to delete a VM always try to take snapshots of it with the date.
  • VM creation can be made simpler. For the very first time, user might feel a bit uneasy about it.
  • Price calculation for a particular VM maybe it is sometimes not exactly correct.
  • Subnetworks are not supported it should support it.
It's ideal for you, as I've already shown, if you wish to host front-end, back-end, vector databases, and other website components.It provides 100% uptime due to its security, which is essential for both new and existing businesses.However, Firebase is also an excellent front-end option because it comes from Google.Because GCP provides so many options, it can be a little confusing for beginning users and is quite pricey and technical.
Score 8 out of 10
Vetted Review
Verified User
We run a number of services via Google Compute Engine, particularly beta and support services as adjunct to our standard Kubernetes deployments. Google Compute Engine is very useful for prototyping and deployments with specific needs. Google Compute Engine allows us to use consistent deployment practices while still allowing experimentation outside of GKE (for example, via IAC/Terraform/Helm).
  • Easy deployment
  • Easy configuration
  • Custom control over hosts (compared to Kube)
  • UI very basic
  • Analytics could be better
Google Compute Engine works well in scenarios where horizontal scaling isn't important, where more detailed control over host parameters is required, and for one-off experimentation. It works less will when horizontal scaling is important (especially when compared to Kubernetes on Google Kubernetes Engine). It also may require more management overhead than something like GKE, depending on your deployment practices.
Score 8 out of 10
Vetted Review
Verified User
We are using Google Compute Engine for hosting Backend for our Project which is making Gen AI based chatbots, so my work here is in security and monitoring field and for that I need Google Compute Engine to host ops related tools as Grafana, Jaeger and also to host flask backend there, it is easily scalable hence we are using it with its easy to use interface
  • Scalability, as we needed the backend and our number of users were less so we used e2 medium and then when it went in production we used e2 large instance
  • Easy to configure, switching between settings and configuration was too easy just by some clicks and all things are done, including ports, security, etc
  • Snapshots and Virtual machine Image creation feature is too good when we don't need machine we stop it and create a snapshot of it for future use.
  • Networking configurations are somewhat hard to configure we need to add rules and policies and there I got confused a lot of time
  • Should include Automatic Scalability and Costing accordingly
It is best suited for hosting applications and back-end which does not require real time processing as fast as trading so we have used it for chatbots backend but for data analytics in real time we needed ultra low latency so we don't use it in our that data project
Score 8 out of 10
Vetted Review
Verified User
We are using Google Compute Engine for running our workloads with respect to scaling our platform using templates. The ease of creating the compute engine with compatibility of Operating systems and customisation features according to our requirements.
  • Easily customizable userdata scripts in compute engines
  • The integration with other services using RBAC is easy and quick
  • Community support for vm images if excellent
  • The UI can be improved. Difficult to find stuff if one is not experienced with GCP.
  • The cost options can be made much more competitive.
For monolithic workloads Google Compute Engine can be used but for microservices where services need to be decoupled, it becomes difficult to use.
Score 9 out of 10
Vetted Review
Verified User
Google Compute Engine is very affordable, user friendly and has AI capabilities so to me, it is superior to AWS in every aspect. And its scalability and 24/7 support lets me adjust to workload changes effortlessly, without compromising on performance. Also you can seamlessly integrate it with any google services specially google cloud services.
  • Quick customer service and intuitive design.
  • Top tier performance and seamless integration with other google services.
  • 24/7 support and user-friendly services.
  • Scalable and affordable for effortless workload adjustments.
  • Resource management and optimization can become complex, especially in large scale deployments.
  • Though not very important, more preconfigured templates would be a good addition to the platform.
  • Despite these issues, the platform delivers very satisfactory performance.
I have only tried Google Compute Engine and AWS and to me, Google Compute Engine is the best one out of them. As not only is it affordable, it is also scalable and customer service is very quick to respond and is available 24/7. Also performance was not compromised and overall I had a very good experience with it.
Score 9 out of 10
Vetted Review
Verified User
We are using the compute engine to host our web applications frontend and backend, with jaeger for tracing of api calls from backend. We also are using Grafana monitoring tool for monitoring and observability of our gen ai chatbots metric in other vm. The best about it is the ease to create and configure the vm. Configuration of firewall from ui is very easy which is helpful.
  • configuration of firewall from ui is very easy.
  • can change the name of VM. Sometime the default name got saved which is very confusing, so we can change the VM name after stop it.
  • addition of extra disk space can be done in few clicks.
  • I got discount on VM original price.
  • I find the documentation a lit bit hard to understand for few times.
  • It will be good if I can change the VM name without stopping it.
  • Sometime the SSH feels slow and looks like its lagging.
Its best suited if we are working with other google services, the integration of it with other google services is very easy to implement. If you are using other cloud services then the integration can get little hard, and may find some error due to different cloud platform. Its perform is good with google services.
Sagar Mehta | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
We use GCP (Google Cloud Platform) for following purposes:
- VM instances for Linux as well as Windows
- GKE Cluster for hosting self auto-scaling cluster running dynamic/multiple applications
- Multi-user project management
- Multiple projects hosted with separate IAM users
- Scaling Up/Down based on requirements of servers and applications.
  • Google Compute Engine Servers are very stable
  • Google Compute Engine Firewall is excellent and easy to manage
  • All different OS images are available with custom images as well
  • Kubernetes Service is very stable and auto-scalable.
  • VM are excellent with great performance but some offer on commercials can be good.
  • GKE is excellent service but rates are little on higher side.
  • Increasing Quota(s) on accounts can be made automatic.
It is almost everywhere and good service:
- For any form of VM(s) required.
- Kubernetes Service is much better than other competitors.
- Project management is much easier and scalable.
- User Management is great and for different projects can be managed with multiple levels of access for users.
Score 10 out of 10
Vetted Review
Verified User
In our organization, we use Google Compute Engine (GCE) as central component of our cloud infrastructure. It provides us with scalable and flexible platform to sustain our virtual machines, which our applications run on, as well as storage and analytics capabilities. This tool helps us to address some business challenges like allows us easily to scale our resources up or down based on demand, ensuring that our applications remain permanent and available. Google Compute Engine greatly assists us in expanding or decreasing resources without worrying about sustaining it by ourselves. This has helped keeping our software running without interruption and with the highest performance.
  • Scalability. Allows us to scale our resources up or down based on demand.
  • Cost efficiency. Offers a pay-as-you-go pricing model.
  • Flexibility. Provides a wide range of VM configurations and customization options.
  • Top-notch security features. Helps to protect our data and applications.
  • Unparalleled customer support.
  • Although the cost is effective, for some small business enterprise this might be a big issue because the cost can be a bit higher.
  • Implementation and configuration may take time especially for the non-technical users.
One thing I really love about Google Compute Engine is the inbuilt security features such as virtual private clouds (VPCS), firewalls and encryption, which helps us by protecting our data and applications from unauthorised access and cyber threats. Also the cost efficiency as this tool offers pay-as-you-go pricing model, which allows us to pay for the resources we use makes it very unique and highly recommended cloud engine platform. Google Compute Engine is not well suited for the non-technical users because it might be difficult navigate through all the features as they're more technical.
Manan Soni | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Google Compute provides solutions to build dynamic websites and apps for clients without consuming much time. The tool has many features to build a customized apps according to our clients needs. It works on many programming languages and gives us option to build an app based on clients primary requirements.
  • Multiple Web Apps Options
  • Prebuilt Samples
  • Customization
  • Documentation For First Time Users
  • More Implementation Would be Handy
Google Compute Engine is so easy to implement and run. It doesn't require much knowledge to build an app since they provide multiple options to choose from with their prebuilt sample list. We can easily make customization on any website app we built for our client according to their needs and make changes if required.
Score 8 out of 10
Vetted Review
Verified User
Google Compute Engine (GCE) is the Infrastructure as a Service platform that we use for running workloads for different product/project teams. With GCE we can create custom VMs for different OS like Windows and different flavours of Linux. These VMs can support small/highly optimized configuration. GCE also provides us with ability to create high performance cloud storage spaces.
  • Runs various operating systems. It also does the patch management of those OS
  • Virtual Manager allows management of OS
  • Provides high performance block storage
  • Provides global load balancing
  • Subnetworks are not supported
  • Support is quite expensive
  • The user interface can be complex for a first time user
Google Compute Engine (GCE) is well suited adding cloud storage. GCE provides excellent block storage capabilities and is well suited for adding addition storage to the application. The applications can be globally load balanced across different regions thus maintaining high availability and response times. It supports VMs of different operating systems thus enabling correct infrastructural choices. GCE UI is not very user friendly can can be improved. Also the networking setup is not very intuitive.
Score 6 out of 10
Vetted Review
Verified User
Compute engine is an offering of GCP, it provides scalable and flexible virtual machine resources for organisations. Business Problem it addresses: Cost-Effectiveness Scalability Performance.

Google Compute Engine provides a high level of customization, flexibility, & scalability in contrast to this, storage is also a major role that it plays. Performance and Security are the Real Factors to go for the GCP Compute Engine

  • Web and Application Hosting
  • High Performance Computing
  • Security, One can rely on Security related things if we are preferring Compute Engine.
  • Ease of Use
  • Pricing
  • Configuring Network & Setting up of VPC and all can be Improved.
I will recommend the Compute Engine if we are concerned of Security, Flexibility and Scalabilty but, It can be improved a bit more in terms of Ease of Usage as compared to AWS EC2 or Azure VM.

Manthan Dhola | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Google Compute Engine (GCE) to host and manage our applications and services in a scalable, reliable, and cost-effective manner. GCE helps us address business challenges related to scalability, reliability, performance, security, and cost-effectiveness. Our use case for GCE includes hosting web applications, running batch processing jobs, supporting machine learning tasks, and more, contributing to our organization's agility and innovation in the cloud.
  • Scalability and Flexibility - during peak hours or sudden spikes in traffic to our website, GCE automatically provisions additional virtual machine instances to handle the increased load.
  • Global Network Infrastructure - we can deploy multi-region architectures with ease, distributing workloads across multiple regions for improved redundancy and performance.
  • Advanced Security Features - encryption at rest and in transit, identity and access management (IAM) controls, network firewalls, and distributed denial-of-service (DDoS) protection
  • Costing - more visibility over how costing is calculated
  • More pre-configured templates like AWS has cloudformation
  • Advanced Monitoring Tools are needed
Suited -Batch Processing and Data Analytics, Web Application Hosting, Containerized Workloads, high performance computing
Unsuited - low traffic websites, static websites, legacy applications, small scale web apps
Score 10 out of 10
Vetted Review
Verified User
We use Google Compute Engine to host websites and APIs for small businesses. It lets us adjust resources based on how much traffic our clients get, making sure their sites and apps run smoothly without them needing to deal with server management. We pick different types of virtual machines depending on what each client needs, e.g a simple blog or an online store.
  • Easy to scale
  • Transparant costs
  • Wide range of services
  • Feature parity with AWS
  • Improved security tools
Hosting dynamic websites where traffic fluctuates - easy scaling. Running compute-heavy backend processes, like data analysis, to benefit from customizable VM sizes. Creating dev and testing environments quickly. Can be overkill for some solutions.
Score 9 out of 10
Vetted Review
Verified User
We use Google Compute Engine instances as our main servers to host our services and applications that are externally or internally used across the whole company. They are easy to use, configure, replicate, update, secure the machines, etc.

Currently, we face no problems with this service and everything is working more than fine.
  • Running services and applications
  • Secure access
  • Easy replication and backups
  • It is totally easy to use
  • Would be nice if prices drop a little bit
Google Compute Engine instances are an easy way to quickly run your applications with good performance, security, and functionality.

With Google Compute Engine instances, you don't need to worry much about machine maintenance and upgrades, and instance monitoring is easy and clear since Google provides cool dashboards to check machine status and notify you about required updates or changes.
Score 8 out of 10
Vetted Review
Verified User
We use it for cross platform software testing and its performance, earlier we were using VM Ware for the same but because Google Compute Engine grants you with more features to increase/decrease the core capabilities of the OS involved for the application testing, we are able to do regression testings more efficiently.

It helped us in identifying the key lacking areas/bugs during the initials phases of a product development.
  • Networking via VPC (Virtual Private Cloud)
  • Big Data Analysis/IoT
  • Storage/Databases for Data Transfer
  • Machine Learning for cloud based translations
  • Third party integrations are very tricky, UI can be improved
  • Artificial Intelligence is an area that can be clubbed together with Machine Learning for better result and future customisation
  • Networking tools can be simplified for better structuring
I would still recommend Google Compute Engine for application build and testing but not for building SaaS. As it'd be more tricky to integrate any third party apps, as Google already provides most of the services but sometime our clients request for such customisations, which is more suited per their internal alignments.

Machine Learning is a tool which is more efficient than any other provider and has wide range of languages for processing.
Score 7 out of 10
Vetted Review
Verified User
A scalable and flexible setup to quickly get our apps up and running without dropping tons of cash upfront, paying only for what we actually use with that pay-as-you-go thing and resources automatically scaling to match demand. High availability comes baked in through load balancing across Google's global infrastructure, with security features and custom VM configs letting us tailor things to our app's needs. With growth, it is possible to integrate with Google's full suite of cloud services like analytics, machine learning, serverless, etc. - to keep adding on capabilities while still focusing on building cool stuff instead of dealing with infrastructure headaches. Comparable to AWS EC2.
  • Scaling - whether it's traffic spikes or just steady growth, Google Compute Engine's auto-scaling makes sure we've got the compute power we need without any manual juggling acts
  • Load balancing - Keeping things smooth with that load balancing across multiple VMs, so our users don't have to deal with slow load times or downtime even when things get crazy busy
  • Customizability - Mix and match configs for CPU, RAM, storage and whatnot to suit our specific app needs
  • The pricing model can get a bit convoluted at times
  • While the integration with other Google Cloud services is pretty slick, linking up Google Compute Engine with services outside of Google's ecosystem isn't always smooth sailing
  • The learning curve for more advanced Google Compute Engine features can be pretty steep at times
If your startup has a web app or SaaS offering that needs to scale quickly based on user demand, Google Compute Engine's auto-scaling capabilities make it a great fit. You can easily spin up more VMs during traffic spikes without overprovisioning resources. For data-intensive workloads like big data processing or training machine learning models, Google Compute Engine's flexible compute instances with GPU support can provide cost-effective scalability. If you have a short-term project or MVP with minimal scaling needs, the overhead of setting up Google Compute Engine may not be worth it.
Score 7 out of 10
Vetted Review
Verified User
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
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
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
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
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
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.
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