# Google Compute Engine Reviews **Vendor:** Google **Category:** [Auto Scaling Software](https://www.g2.com/categories/auto-scaling) **Average Rating:** 4.5/5.0 **Total Reviews:** 954 ## About Google Compute Engine Compute Engine is Google's infrastructure as a service (IaaS) platform for organizations to create and run cloud-based virtual machines. ## Google Compute Engine Pros & Cons **What users like:** - Users appreciate the **ease of use** of Google Compute Engine, finding it intuitive and efficient for provisioning resources. (76 reviews) - Users value the **scalability and flexibility** of Google Compute Engine, which enhances performance for diverse workloads. (69 reviews) - Users love the **ease of use and quick setup** of Google Compute Engine's virtual machines for various workloads. (64 reviews) - Users appreciate the **easy implementation** and **customizable features** of Google Compute Engine for seamless cloud management. (58 reviews) - Users appreciate the **flexibility and control** of Google Compute Engine for managing infrastructure and scaling resources efficiently. (54 reviews) - Users appreciate the **flexibility** of Google Compute Engine to adjust VMs based on project needs efficiently. (50 reviews) - Integrations (49 reviews) - Performance (45 reviews) - Reliability (37 reviews) - User Interface (36 reviews) **What users dislike:** - Users find **pricing issues** in Google Compute Engine challenging, with predictions often being complex and unclear. (49 reviews) - Users find Google Compute Engine **expensive** due to complex pricing and the need for higher-tier plans for support. (45 reviews) - Users find **cost management challenging** , with unpredictable pricing and a complex interface for new users. (33 reviews) - Users find the **complexity of the interface** challenging, especially when handling advanced configurations and settings. (30 reviews) - Users face a **steep learning curve** with Google Compute Engine, making it challenging, especially for beginners. (27 reviews) - Users often find the **pricing structure complex** , making it challenging for beginners to navigate effectively. (26 reviews) - Difficult Learning (22 reviews) - Not User-Friendly (21 reviews) - Steep Learning Curve (20 reviews) - Unexpected Costs (19 reviews) ## Google Compute Engine Reviews ### 1. Powerful but Complex: Great for Advanced Users **Rating:** 3.5/5.0 stars **Reviewed by:** Safa K. | Small-Business (50 or fewer emp.) **Reviewed Date:** April 10, 2026 **What do you like best about Google Compute Engine?** I really like how Google Compute Engine gives me full control over the virtual machines. I can choose CPU, memory, OS, and storage based on my workload without any restrictions. Scalability is strong too; I can start small and scale up instantly as my workload grows. This is important for handling large geospatial data and machine learning pipelines. The performance is reliable, and instances remain stable even under high processing loads, which is great for long-running jobs. Communication is smooth as well, and it works well with the rest of Google Cloud, like storage, BigQuery, and AI tools. It especially helps with GIS and data pipelines by removing hardware limitations and giving me speed and control. **What do you dislike about Google Compute Engine?** Some areas need improvements. The setup is not beginner-friendly, like dealing with networking and IAM slows me down when I just want to run a quick job. The cost visibility can be confusing, and billing is granular. Small mistakes like leaving instances running can increase costs fast, and alerts need manual setup. The cost management overhead means I still manage VMs, patch, monitor, and optimize, rather than it being fully handled like serverless. GPU and quota limits can take time to sort out and block fast experimentation. Overall, it's powerful but not simple, and I need cloud experience to use it efficiently. **What problems is Google Compute Engine solving and how is that benefiting you?** I use Google Compute Engine to overcome local computing limits, handle large datasets, and run heavy processing tasks like GIS and machine learning. It provides scalable compute power without needing physical servers, enabling faster and more flexible system deployment. ### 2. Streamlined AI Training with Google Compute Engine, But Needs Longer Sessions **Rating:** 4.5/5.0 stars **Reviewed by:** Arban O. | Software Architect & Founder GEN 6 AI LAB, Small-Business (50 or fewer emp.) **Reviewed Date:** April 10, 2026 **What do you like best about Google Compute Engine?** 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. **What do you dislike about Google Compute Engine?** 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. **What problems is Google Compute Engine solving and how is that benefiting you?** 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. ### 3. Effortless Deployment, Needs Better Access Control **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Computer Software | Small-Business (50 or fewer emp.) **Reviewed Date:** March 14, 2026 **What do you like best about Google Compute Engine?** 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. **What do you dislike about Google Compute Engine?** 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. **What problems is Google Compute Engine solving and how is that benefiting you?** 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. ### 4. Great VM flexibility if you want control over your cloud infrastructure **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Mid-Market (51-1000 emp.) **Reviewed Date:** March 14, 2026 **What do you like best about Google Compute Engine?** One thing I really like about Google Compute Engine is how much control it gives you over your virtual machines. You can choose the exact CPU, memory, disk type, and networking configuration depending on what you need. It’s very flexible compared to some higher-level managed services. In my day-to-day work I also appreciate how well it fits into automation workflows. Spinning up instances, attaching disks, or modifying infrastructure is easy through APIs or infrastructure-as-code tools. Once everything is defined properly, you can recreate environments pretty quickly. Overall it feels reliable and production-ready, which is really important when you’re running backend services. **What do you dislike about Google Compute Engine?** The pricing model can take some time to fully understand. There are a lot of small components that affect the final cost, like machine types, storage, and network traffic. If you’re not paying attention it’s easy to underestimate how much something will cost. Another minor downside is the cloud console. It’s powerful but sometimes feels cluttered, especially when you’re trying to find a specific configuration option. After using it for a while it becomes easier, but the first impression can be a bit overwhelming. **What problems is Google Compute Engine solving and how is that benefiting you?** Using Google Compute Engine basically removes the need to worry about physical infrastructure. Instead of managing hardware or provisioning servers manually, we can launch instances whenever we need them. ### 5. Powerful scalability with a small learning curve **Rating:** 4.0/5.0 stars **Reviewed by:** Vadym S. | Senior Backend Developer, Mid-Market (51-1000 emp.) **Reviewed Date:** March 14, 2026 **What do you like best about Google Compute Engine?** I used Google Compute Engine to run microservices and test new ones. I really like that you can manage infrastructure with code, which allows for quick automation of server deployments and configurations through scripts. Scaling the infrastructure as the load increases is extremely convenient. I especially appreciate the flexible orchestration in GKE and the quick configuration of VM Instances. The monitoring also impressed me. Integration with the load balancer and the ability to quickly deploy a virtual server without setting up physical hardware greatly facilitate the work. **What do you dislike about Google Compute Engine?** Sometimes the interface can be a bit complex for beginners because there are many configurations and components. Also, the pricing model is not always immediately clear, as the cost is composed of several parameters - computing resources, network, disks, and other services. It would be nice to have a simpler and more visual cost calculation for new users, and of course, discounts for different categories of users. **What problems is Google Compute Engine solving and how is that benefiting you?** I can quickly deploy servers for microservices and testing without purchasing physical equipment. Scaling with increased load is very convenient. Code management automates deployment, which is important for microservices, and testing code in different environments has become easier. ### 6. Highly Customizable and Reliable Cloud Platform **Rating:** 5.0/5.0 stars **Reviewed by:** Aries B. | Technology Analyst | Verint SaaS - Digital Solutions, Information Technology and Services, Mid-Market (51-1000 emp.) **Reviewed Date:** January 08, 2026 **What do you like best about Google Compute Engine?** One of the things I like most i like about Google Engine is that I can create highly customized machine types with exact CPU and memory specs based on the specific workloads. The live migration is also a massive advantage, as it keeps my instances running smoothly even during backend maintenance. **What do you dislike about Google Compute Engine?** While the core features are robust, I find that some of the documentation are outdated or lacks in-depth troubleshooting steps. I also find that the premium tech support cost can be quite high for smaller organizations that aren't on an enterprise level. **What problems is Google Compute Engine solving and how is that benefiting you?** I am able to solve the challenges of managing physical hardware by using Google Compute Engine's scalability. pay-as-you-go virtual machine environment. This benefits me because I can use custom machine types and autoscaling to handle traffic spikes efficiently while keeping my infrastructure cost optimized. ### 7. Effortless Management, Scalable Solutions with Room for Improvement **Rating:** 3.5/5.0 stars **Reviewed by:** Alejandro B. | DevOps Engineer Specialist, Small-Business (50 or fewer emp.) **Reviewed Date:** March 19, 2026 **What do you like best about Google Compute Engine?** I find Google Compute Engine easy to manage, thanks to the gcli, and it's easy to scale both vertically and horizontally without much hassle. It's simpler than AWS since I don't need to stop and resize for maintenance. I appreciate the tight integration with IAM, which helps with permission provisioning. The setup was pretty easy and fast. **What do you dislike about Google Compute Engine?** What I don't really like is the division of the projects around it. I need a project on GCP for everything, and having it all divided can be quite a handful to manage with all my Google Compute Engine having to switch this up. **What problems is Google Compute Engine solving and how is that benefiting you?** Google Compute Engine makes it easy to manage infrastructure, scale applications without hassle, and manage security effectively. Its integration with IAM simplifies permission provisioning, and the Google Cloud CLI eases management even compared to AWS. ### 8. Scalable Powerhouse for Deep Learning **Rating:** 4.0/5.0 stars **Reviewed by:** Siddhartha S. | Sr.Data Scientist, Enterprise (> 1000 emp.) **Reviewed Date:** March 14, 2026 **What do you like best about Google Compute Engine?** I like the scaling of resources on Google Compute Engine. It's great that I can go from using 2 T4 to 6 H100 quickly. Once the permission is granted from my organization, I can get 6 more resources on the same day. We can turn off the training, change the config, add extra resources, and restart training all in one day. The initial setup was easy, especially because I've used AWS before, and this felt easier once the credentials were set. **What do you dislike about Google Compute Engine?** I mean BigQuery is still separate and sometimes when running a large SQL query, it takes time. I wish they could add compute there as well. **What problems is Google Compute Engine solving and how is that benefiting you?** I use Google Compute Engine for training and inference, benefiting from quick resource scaling, like switching from 2 T4 to 6 H100 in a day, enhancing our deep learning capabilities. ### 9. Engineer-Friendly Power and Flexibility with Rock-Solid Performance **Rating:** 5.0/5.0 stars **Reviewed by:** Venkata B. | Software development engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** February 10, 2026 **What do you like best about Google Compute Engine?** 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. • Strong performance & networking – Google’s global network is genuinely fast and reliable. Low latency, solid bandwidth, and great for distributed systems. • Live migration – VMs can be moved during host maintenance with little to no downtime. That’s huge for production stability. • Deep integration with the Google ecosystem – works seamlessly with GKE, Cloud Storage, BigQuery, IAM, and monitoring. Everything feels designed to work together. • Pricing transparency – per-second billing and sustained-use discounts kick in automatically, which is refreshing. Overall, GCE feels very engineer-friendly: fewer arbitrary limits, more control, and infrastructure that just quietly does its job. **What do you dislike about Google Compute Engine?** What I dislike about Google Compute Engine (being honest, not dramatic 😅): • Steep learning curve – GCE assumes you’re already comfortable with cloud concepts. IAM, networking, projects, VPCs… powerful, but not very beginner-friendly. • IAM can feel overcomplicated – super granular (which is good), but figuring out the right role vs too much access can be frustrating. • Console UX is cluttered – the web console tries to do everything at once. Simple tasks sometimes take more clicks than they should. • Support isn’t great unless you pay – community docs are solid, but real-time help or faster resolution usually means a paid support plan. • Unexpected costs if you’re not careful – things like egress traffic, static IPs, and idle resources can quietly add up. • Smaller ecosystem compared to AWS – fewer third-party tools, tutorials, and “copy-paste” solutions in some niches. In short: GCE is excellent for engineers who know what they’re doing, but it can feel intimidating and a bit unforgiving if you’re new or moving fast without guardrails. **What problems is Google Compute Engine solving and how is that benefiting you?** Google Compute Engine is mainly solving the problem of reliable, scalable infrastructure without owning or managing hardware, and that’s a big win in a few concrete ways for me. Problems it solves → How that benefits me: • On-demand compute capacity I don’t have to guess future hardware needs or over-provision. I can spin up VMs in minutes and scale up/down as workloads change, which saves both time and money. • Infrastructure reliability & maintenance Google handles hardware failures, host maintenance, and upgrades. Features like live migration mean fewer outages, so I can focus on building and running applications instead of babysitting servers. • Flexible workload requirements With custom machine types, GPUs, preemptible/spot VMs, and different disk options, I can tailor resources exactly to my use case—whether it’s development, data processing, or production workloads. • Global deployment & low latency Running VMs close to users across regions reduces latency and improves performance without setting up physical data centers. • Cost efficiency for long-running workloads Per-second billing and sustained-use discounts automatically lower costs for VMs that run longer, which makes budgeting more predictable. • Security & access control at scale Built-in IAM, VPCs, firewalls, and OS-level hardening help secure workloads without needing custom security infrastructure. Overall, GCE benefits me by removing operational friction—less time spent on infrastructure decisions and troubleshooting, more time focused on actual product development and performance. ### 10. Modern, Intuitive Cloud Platform That Makes Getting Things Done Easy **Rating:** 4.0/5.0 stars **Reviewed by:** Artsiom H. | Devops engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** February 17, 2026 **What do you like best about Google Compute Engine?** I like that GCP feels like a modern solution where everything is fairly simple and clear. Unlike some other providers with a lot of legacy stuff, where you can spend hours trying to find what you need, GCP feels intuitive. Most of the time, I can figure out what I need and get it done within a few minutes without having to dig through a lot of documentation. **What do you dislike about Google Compute Engine?** I can’t really think of anything I genuinely dislike. Maybe the documentation could be better in some cases **What problems is Google Compute Engine solving and how is that benefiting you?** It’s fairly priced and easy to use. The support has been good, and overall it helps us save both time and money. ## Google Compute Engine Discussions - [What is a compute instance?](https://www.g2.com/discussions/what-is-a-compute-instance) - 2 comments, 2 upvotes - [Is Google Compute Engine PaaS?](https://www.g2.com/discussions/is-google-compute-engine-paas) - 1 comment, 1 upvote - [What does Google Compute Engine do?](https://www.g2.com/discussions/what-does-google-compute-engine-do) - 4 comments, 1 upvote - [Can I get the manual to understand the different features of it ?](https://www.g2.com/discussions/can-i-get-the-manual-to-understand-the-different-features-of-it) - 1 comment, 1 upvote - [Feature Max Limit and Partnership](https://www.g2.com/discussions/feature-max-limit-and-partnership) - 1 comment, 1 upvote ## Google Compute Engine Pricing - **Beyond Free Tier and Free Trial**: Pay As You Go Pricing for Compute Engine is based on per-second usage of the machine types, persistent disks, and other resources that you select for your virtual machines. - **Try Google Compute Engine Free**: Free New customers get $300 in free credits to spend on Compute Engine during the first 90 days. Free trial starts spending after free monthly usage is exhausted. Free usage includes: [View full pricing details](https://www.g2.com/products/google-compute-engine/pricing) ## Google Compute Engine Integrations - [Airbyte](https://www.g2.com/products/airbyte/reviews) - [Coralogix](https://www.g2.com/products/coralogix/reviews) - [Datadog](https://www.g2.com/products/datadog/reviews) - [Docker](https://www.g2.com/products/docker-inc-docker/reviews) - [Firebase](https://www.g2.com/products/firebase/reviews) - [GitHub](https://www.g2.com/products/github/reviews) - [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews) - [Google Cloud Load Balancing](https://www.g2.com/products/google-cloud-load-balancing/reviews) - [Google Cloud Monitoring](https://www.g2.com/products/google-cloud-monitoring/reviews) - [Google Cloud SQL](https://www.g2.com/products/google-cloud-sql/reviews) - [Google Cloud Storage](https://www.g2.com/products/google-cloud-storage/reviews) - [Google Kubernetes Engine (GKE)](https://www.g2.com/products/google-kubernetes-engine-gke/reviews) - [Google Maps Platform](https://www.g2.com/products/google-maps-platform/reviews) - [Google Translate](https://www.g2.com/products/google-translate/reviews) - [Google Workspace](https://www.g2.com/products/google-workspace/reviews) - [IBM Terraform (formerly HashiCorp Terraform)](https://www.g2.com/products/ibm-terraform-formerly-hashicorp-terraform/reviews) - [Jenkins](https://www.g2.com/products/jenkins/reviews) - [Kubernetes](https://www.g2.com/products/kubernetes/reviews) - [Microsoft Power BI](https://www.g2.com/products/microsoft-microsoft-power-bi/reviews) - [MongoDB](https://www.g2.com/products/mongodb/reviews) - [MongoDB Atlas](https://www.g2.com/products/mongodb-atlas/reviews) - [MySQL](https://www.g2.com/products/mysql/reviews) - [New Relic](https://www.g2.com/products/new-relic/reviews) - [Snowflake](https://www.g2.com/products/snowflake/reviews) - [SonarQube](https://www.g2.com/products/sonarqube/reviews) - [Supabase](https://www.g2.com/products/supabase-supabase/reviews) - [Verint Workforce Management](https://www.g2.com/products/verint-workforce-management/reviews) - [Visual Studio Code](https://www.g2.com/products/visual-studio-code/reviews) - [WordPress.org](https://www.g2.com/products/wordpress-org/reviews) ## Google Compute Engine Features **Functionality** - Cloud Consolidation - Cloud Orchestration - Cloud Optimization **Infrastructure Provision** - Public Cloud - Private Cloud - Hybrid Cloud - Bare Metal - High-Performance Computing (HPC) - Virtual Machines (VMs) - Edge Computing - Virtual Networks **Performance** - Scalability - Portability - Data Recovery **Automated resource scaling** - Automatic resource discovery - Smart scaling **Management** - Cloud Cost Analytics - Cloud Security - Cloud Resource Management - Cloud Backup and Recovery **Management** - Pay by Usage - Usage Tracking - Performance Tracking **Functionality** - OS Integration - Resource Saving - Performance Management - Security **Scaling strategies** - Pre-defined optimization strategies - Predictive scaling **Functionality** - Resource Auto-Scaling **Visualization** - Unified scaling - Dashboard **Agentic AI - Cloud Management Platforms** - Autonomous Task Execution - Cross-system Integration - Decision Making **Agentic AI - Server Virtualization** - Autonomous Task Execution - Multi-step Planning - Cross-system Integration - Adaptive Learning - Proactive Assistance - Decision Making ## Top Google Compute Engine Alternatives - [Azure Virtual Machines](https://www.g2.com/products/azure-virtual-machines/reviews) - 4.4/5.0 (374 reviews) - [Vultr](https://www.g2.com/products/vultr/reviews) - 4.3/5.0 (282 reviews) - [Amazon EC2](https://www.g2.com/products/amazon-ec2/reviews) - 4.6/5.0 (1,127 reviews)