Google Compute Engine Reviews

I love how practical and easy to use it is; it has really improved the way I manage my VMs. It gives me plenty of options to create and configure different settings for some of my older services running there. The integration with the Google CLI is great and gives me more control. I also appreciate the pricing best practices it supports, like shutting down machines at night or setting different schedules.

Between AWS EC2 and GCE, AWS EC2 used to have the worst documentation out there, but now GCE takes first place.

Docker server, services in the cloud and web hosting It's been my main vm in the cloud for a couple of years.

Google Compute Engine is a good option for anyone who needs a virtual computer system to run a wide range of computing applications and projects. I especially like the broad selection of instances to choose from, as well as how easy it is to set up and manage using both the GUI and the command-line interface. I am able to setup my instances quickly at a cost that is not too prohibitive. Their multimodal AI Gemini, is also integrated for those who need it, I personally did not need it.

I dislike the fact that many times I am denied access to higher performance gpu compute to run my AI intensive applications mainly because they are reserved for larger organizations .

Google compute engine is solving the problem of difficulty setting up VM instances and provides quick fast and reliable solutions which increase the efficiency of my DevOps operations.

I like the integration of Gemini with Google Compute Engine, as it allows me to create a markdown file on my server, download it with the training data, and let Gemini handle the scripting. This integration makes my tasks a lot easier and faster. I'm also looking forward to trying the Google Drive integration for longer training sessions because of the time limit, which seems promising for my workflow.

I would be happier if the time limitation could be longer, because it's not even 12H. I got about 1H and then it told me to stop because of high demand, so after that I could only use CPU, but it would take forever to train the model on that. Maybe the UI is a little bit messy. When you have lots of scripts, you have to scroll up or down and search for the training script etc. This could use an upgrade.

I use Google Compute Engine because my server lacks a GPU, which would take forever to train my AI model. I like the integration with Gemini for easier and faster scripting, and I'm excited to try Google Drive integration for longer training sessions.

I like how Google Compute Engine gives me the flexibility to fully control VM configurations and easily scale based on my application needs. It helps me tailor infrastructure exactly to my app needs by letting me choose the right CPU/memory for backend APIs, which improves performance and avoids overpaying. Also, the initial setup was pretty easy.

Complexity of setup and management, it requires solid knowledge of networking, IAM, VM configurations

Google Compute Engine eliminates the need for hardware by providing cloud-based virtual machines, offering flexibility to control VM configurations, and scaling easily based on application needs, which improves performance and cost efficiency.

I really like how I can start a Google Compute Engine instance by clicking on the SSH button that is available on the portal, so I don't need to hassle with installing gcloud or SSH to my own terminal. It is a really handy feature. I really like its user interface—everything I need is visible. For example, if I need an external IP, it's already visible in the table at the top. It doesn't waste time; everything is just right there available on the screen. The initial setup was really smooth because of the SSH button.

I can't see or update anything of backend files if the person responsible is on leave or if the backend suddenly breaks. I wish there was a way to control access so any developer can decide who else can access their folder.

I can easily start a Google Compute Engine instance with the SSH button on the portal, avoiding the hassle of installing gcloud and SSH on my terminal. The user interface is efficient, with essential information like external IPs readily visible, which saves time.

I have very good experiences using Google Compute Engine's cloud virtual machines for all kinds of purposes. I like the versatility and scalability, and you can 'pay as you grow,' if you know what I mean. The initial setup was easy for my team.

price

I use Google Compute Engine for automatic dockerized functions that run on triggers. It offers versatility and scalability, allowing me to pay as I grow.

What I like best about Google Compute Engine (GCE) is how cleanly it balances power, flexibility, and performance without getting in your way.

A few standout things for me:

• Custom machine types – you’re not forced into rigid instance sizes. Need more CPU but less RAM? Easy. That level of control saves money and fits real workloads better.

It's ability to provide access to fast and smoothly.

I didn't find anything that I dislike from google compute engine .

I user compute engine for connecting vpc resources as bastion host.

Google Compute Engine is reliable, secure and scalable platform to get direct access to Goggle finest compute. It has a lot of pricing tiers to match my requirement with a variety of RAM, storage and processing.

The compute power of always free tier of compute engine is very low. It is unable to sustain a lot of traffic and might get down.

Google Compute engine is providing me with a platform where I can host my websites reliably and securely. It comes with a aways free tier that helps me to validate my idea before paying anything upfront.

What I appreciate most about GCE is its emphasis on performance and the flexibility of its customizable VM architecture. One standout feature is live migration, which allows virtual machines to remain operational during maintenance, minimizing downtime—a capability that's uncommon among major providers. The per-second billing model ensures you only pay for the resources you actually use, adding to its cost-effectiveness. With custom machine types, you can precisely adjust CPU and RAM allocations rather than being limited to preset VM sizes. Networking performance is robust, which is particularly beneficial for distributed workloads and global deployments. Additionally, GCE offers deep integration with Google services, making it especially advantageous for AI/ML workloads, Kubernetes, and BigQuery. Altogether, these features make GCE a highly cost-efficient and reliable choice for production workloads, particularly for organizations that require flexibility and high uptime.

One aspect I find frustrating about Google Compute Engine is the complexity of its pricing structure. The costs for custom machine types and network egress can accumulate quickly, and if you’re not keeping a close eye on your usage, it’s easy to end up spending more than intended.

Google Compute Engine addresses the challenges of handling physical servers and fluctuating workloads. Rather than investing in and maintaining hardware, I am able to quickly launch virtual machines as needed, which scale automatically. This approach not only saves time and lowers infrastructure expenses, but also helps keep applications running smoothly, even during periods of high traffic.