Google Compute Engine Reviews and Ratings

Name: Google Compute Engine
Rating: 8.3 (198 reviews)
Author: Google

Rating: 8.3 out of 10

Score

8.3 out of 10

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Reviews

61 Reviews

Did you ever see Google down

Rating: 10 out of 10

Incentivized

April 22, 2025

Use Cases and Deployment Scope

In our company, we are both users and integrators of Google Cloud Platform. Among all the products, Google Compute Engine is probably one of the most widely used, as it allows for the creation of virtual machines. We manage a wide variety of projects using this product. Suffice it to say that our entire infrastructure runs on GCP.

Pros

Resources allocation
Monitoring
Catalogue deployment
Awesome free tier and discount credits

Cons

UI for advanced feature
Cost prediction

Likelihood to Recommend

From a purely cost-based perspective, Google Compute Engine is ideal if you're building an application from scratch, as it allows you to start small with the free tier or promotional credits and then gradually scale up your architecture. Under the hood, you have the power of Google, which provides a secure and reliable environment to work in.

Verified User

Solution Architect in Information Technology (501-1000 employees)

Vetted Review

5 years of experience

The cloud server infrastructure you need a few clicks away

Rating: 10 out of 10

Incentivized

April 9, 2025

Use Cases and Deployment Scope

Our entire server infrastructure runs on Google Compute Engine. This includes web, authentication and CI/CD servers (Jenkins). We can easily scale by deploying virtual instances as needed with just a few clicks. Tasks such as backup and monitoring are handled automatically, allowing our team to stay lean and focus on our main subject matter.

Pros

Instance deployment
Backup and Recovery
Alerts and monitoring

Cons

OS upgrades
Resource allocation
Disk management

Likelihood to Recommend

It's ideal for startups looking to launch a SaaS product to the market relatively fast. Even better if growth estimation are steady to forecast costs accurately. It can become expensive for scenarios where growth can't be well estimated.

ISIDRO MORAN

Director, Engineering in Engineering at Vistadash (51-200 employees)

Vetted Review

5 years of experience

View profile

Google Compute Engine (GCE)

Rating: 7 out of 10

Incentivized

February 26, 2025

Use Cases and Deployment Scope

Best for scalable customizable VMS with strong performance Google Cloud integration

Pros

Cost Benefits- Users can benefit from sustained use discounts reducing costs based on usage
High Availability- It offers automatic failover and managed instance groups to ensure application availability

Cons

Dashboard - A more customizable dashboard with widgets for key metrics, such as CPU usage, network traffic, and storage, would allow users to monitor their resources more effectively
Enhanced Container Support - A more unified container management platform that integrates container orchestration, and storage to simplify the containerization process
Networking and Security - Adding support for more advanced networking features, such as multi-cloud peering

Likelihood to Recommend

Google Compute Engine is a powerful and flexible tool for a wide range of workloads, particularly those requiring customization, scalability

Verified User

support engineer in Information Technology (501-1000 employees)

Vetted Review

1 year of experience

GCE the Google Cloud All Rounder

Rating: 8 out of 10

Incentivized

February 6, 2025

Use Cases and Deployment Scope

Google Compute Engine is a stateful compute service in GCP, so the business problems we try to use it for are deploying different solutions it can be AI solutions, for any other. Recently we are using for the deployment of LLMs, we are using it to deploy Open Source LLMs up there for security closure which has to be shown to clients. Being a server backed compute the main monitoring and flexibility of setup is the main benefit in my views, perfect for learning as well as noting down the last detail of the solution in terms of requirements or maintenance workloads.

Pros

Flexible Setup, the whole catalog of hardware and software is up your hand to select best from.
Security Closures, being the firewalls and other features, it saves our solution from network vulnerabilities.
Monitoring Dashboard, in general if we try to use the on-prem resources, the continuous monitoring is a headache but with GCE it is managed at all times.

Cons

Predictive Cost Modeling, I am using GCE from a very long time but always end up getting bills which are way ahead of what was shown on the dashboard.
Enhanced RIs Management, in the time of GenAI atleast we can expect best recommendations as per our usages for Reserved Instances to get optimized bills.
Some betterments in UI/UX, when I was new to GCE the UI was a bit of a learning curve for me. In exploring phase, it took some time.

Likelihood to Recommend

The scenarios where setups should be most flexible, monitoring you can setup as per needs, and high-performance requirement is a must, even we can setup the security premises as well. All of the setup is in your hand and as per your requirements and resources you can set up the whole solutioning till the very last inch of it.

Rajveer Mathur

AI/ML Engineer in Engineering at Brillio (5001-10,000 employees)

Vetted Review

3 years of experience

One of the best virtual machine infrastructure provider out there.

Rating: 9 out of 10

Incentivized

February 3, 2025

Use Cases and Deployment Scope

We host all our VMs on Google Compute Engine. Our Kubernetes cluster is also dependent upon the nodes created on the Google Compute Engine. We have our backend services running directly on the VMs and on the Kubernetes cluster on the VMs. It also gives us a view of how the VMs are performing and if we need to scale them up.

Pros

It provides us with managed VMs on the go that takes only a couple of minute to come up.
It helps us understand the performance metrics of the VMs (like CPU utilization, Memory utilization) which helps us in deciding if we need to scale up.
It gives us an option to create, destroy and even scale up or scale down VMs whenever necessary.

Cons

Pricing of the Google Compute Engine can be more transparent. Currently CPU and memory is charged separately and its difficult to understand VM specific pricing in the billing section.
Using GPUs in the Google Compute Engine can be made more easy.
Provide an instance that can auto scale based on certain performance rules

Likelihood to Recommend

Google Compute Engine is well suited for hosting VMs and running your applications on these VMs. They are pretty stable and we've rarely encountered issues with the VMs. However, it might not be appropriate if you don't have a continuously running service and you might want to explore GCP cloud run.

Verified User

Co-founder & CTO in Information Technology (1-10 employees)

Vetted Review

4 years of experience

Google Cloud Compute Engine is easy to use!

Rating: 10 out of 10

Incentivized

November 28, 2024

Use Cases and Deployment Scope

When it comes to hosting a server online, you usually want to find the right company that fits your needs. I personally have used most of the cloud providers. I find Google's cloud environment user-friendly. You can scale your projects accordingly, and you will know how much it will cost due to their transparent pricing.

Pros

Cost
User friendly
Options

Cons

Possibly more options to match competitors.
N/A

Likelihood to Recommend

Whether you are looking for a cloud provider for a small or large project, Google's compute engine suits both. You won't have a problem with cost because Google's pricing is affordable and near the same as AWS.

Jeffrey Lange

Cybersecurity Analyst in Information Technology at Confidential (1-10 employees)

Vetted Review

8 years of experience

Verified on LinkedIn

Great service for ad-hoc tasks

Rating: 10 out of 10

Incentivized

September 25, 2024

Use Cases and Deployment Scope

We use Google Compute Engine to spin up small development environments that host our development and staging Postgres database instances. We didn't want to have to use a more fully featured SQL solution like Google Cloud SQL or other major solutions for development/staging to cut down on cloud-related costs.

Pros

Can spin up very small instances
Instances can be paused
Instances can set up with a Docker image

Cons

It'd be nice to be able to set up auto pausing in the console
On that note, instances can be suspended only up to 60 days, it'd be nice if it went longer or indefinitely

Likelihood to Recommend

Google Compute Engine is perfectly suited to the more ad hoc tasks you might need a machine for. We use it for development/staging environments specifically, but it's great for running various tasks in isolation and having great control over how much it's going to cost you. Auto-pausing also helps greatly in this area.

Verified User

Senior Software Engineer in Research & Development (51-200 employees)

Vetted Review

2 years of experience

GCE - your cloud VM option on GCP.

Rating: 7 out of 10

Incentivized

September 23, 2024

Use Cases and Deployment Scope

Well, Google Compute Engine is basically Google's response to AWS EC2 or Azure VMs. It's a cloud VM service that provides you with VMs on demand, with various types and capabilities for your needs. Of course, it's flexible in terms of how many resources you want and whether you want auto-scaling or not. Also, enterprise features like IAM and VPC are supported.

Pros

Flexible pricing with various options for discounted rates.
Lots of customizations regarding machine capacity, including creating your mix.
Strong ML/AI support.

Cons

Not as popular as AWS EC2, even less than Azure VMs.
There is not much to differentiate itself from other offers.

Likelihood to Recommend

I would only pick Google Compute Engine if I already used other GCP services. In my company, some projects use GCP, so GCE is the natural choice for those. However, the same can be said for projects on AWS/Azure. When you need a VM, it's usually much simpler to just use the service on the platform that you're already using.

Verified User

Engineering Manager in Engineering (501-1000 employees)

Vetted Review

3 years of experience

Driving Efficiency in the Cloud.

Rating: 9 out of 10

Incentivized

September 23, 2024

Use Cases and Deployment Scope

We use Google Compute Engine to Host our Backend Services. Our Product is an AI-driven Saas Platform (GIDE.AI) that helps high school students track their academic progress, activities, and interests. Help them prepare for entrance

exams and guide them to build a scholarship-worthy profile. A. With minimal human intervention, I am a platform that can counsel parents and students in choosing the right program, university, and career. For Universities, schools, and other education organizations, it offers self-serve subscription-based services to track their students, engage & network with students for admissions, counseling support, tests & quizzes, career interest, profile building, etc. The Google compute engines help us host various microservices.

Pros

Rule-based Autoscaling.
It offers a combination of CPU, RAM, and H/W per workload.

Cons

Improved documentation.
Allow autoscaling based on App performance.

Likelihood to Recommend

It is an excellent choice for microservice architecture deployments using GCP's Kubernetes K8 engines. It comes out of the box, and with a few configurations, you can get microservices up and working. I highly recommend it.

Alok Pabalkar

Co-Founder & CTO in Research & Development at GIDE.AI (51-200 employees)

Vetted Review

23 years of experience

View profile

A Good option to manage your Self hosted apps.

Rating: 8 out of 10

Incentivized

September 22, 2024

Use Cases and Deployment Scope

So currently, we are using Google Compute Engine for our Jenkins Server, where our Retail Finance jobs are configured. We are using two GCEs of type CentOS 7: one for our Master Jenkins controller, where all the pipelines are configured, and the other for Google Computer Engine, which is being used as a slave agent, which our job uses to run the pipeline. Our slave GCE uses the memory-optimized machine configuration of series M2 because, daily, multiple jobs run simultaneously, which almost uses more than 20 executors as multiple QAs run their unit testing workloads on the same server. In contrast, our Jenkins master uses the simple general-purpose machine configuration as it only has the job and credentials info.

Pros

It provides the ability to create your instance using the Google cloud command line if you do not have access to the Google Cloud Console and have appropriate permissions.
It offers multiple machine-type configurations that you can choose from depending on your organizational workload.
It comes with an instance scheduling option, which helps you schedule your VMs and save your bills on unnecessary running GCES.

Cons

GPU is not available for N2 series GCEs, understandable for E2 series but the N2 series GCE must have the option to add GPUs.
Instance costs are very high for memory-optimised machine types. A single instance costs us almost $40000 in a month.
A bit challenging and complex using Google cloud to automate GCE instance VM creations.

Likelihood to Recommend

You can use Google Cloud Compute Engine as an option to configure your Gitlab, GitHub, and Azure DevOps self-hosted runners. This allows full control and management of your runners rather than using the default runners, which you cannot manage. Additionally, they can be used as a workspace, which you can provide to the employees, where they can test their workloads or use them as a local host and then deploy to the actual production-grade instance.

Verified User

Associate Staff Engineer in Information Technology (501-1000 employees)

Vetted Review

1 year of experience

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A Good option to manage your Self hosted apps.

Rating: 8 out of 10

Incentivized

September 22, 2024

Use Cases and Deployment Scope

Pros

It provides the ability to create your instance using the Google cloud command line if you do not have access to the Google Cloud Console and have appropriate permissions.
It offers multiple machine-type configurations that you can choose from depending on your organizational workload.
It comes with an instance scheduling option, which helps you schedule your VMs and save your bills on unnecessary running GCES.

Cons

GPU is not available for N2 series GCEs, understandable for E2 series but the N2 series GCE must have the option to add GPUs.
Instance costs are very high for memory-optimised machine types. A single instance costs us almost $40000 in a month.
A bit challenging and complex using Google cloud to automate GCE instance VM creations.

Likelihood to Recommend

Verified User

Associate Staff Engineer in Information Technology (501-1000 employees)

Vetted Review

1 year of experience