Google Compute Engine Reviews and Ratings

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Use Cases and Deployment Scope

Google Cloud compute engine (GCE) is the backbone of all Google Cloud for us. Anything you plan to do needs computing, and GCE works well with all the offerings of different CPU, RAM, and GPU configurations for various workloads. We use GCE directly for stateful services while it is used under the hood for k8s clusters and other services.

Likelihood to Recommend

It is excellent if you have any workloads that need raw computing or plan to have any state-full services running in your environment like DBs (for which you don't want to use Managed services), cache, etc. It also gives you complete control over which versions of software, OS, etc., you need, and thus, you can build anything and deploy it on GCE.