High Performance, Scalable Cloud Computing with Seamless Integration with other Google Services.
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 …
Starting at $0 per month GB
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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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Popular Features
- Security controls (47)7.373%
- Operating system support (47)7.272%
- Pre-defined machine images (46)6.262%
- Pre-configured templates (45)5.858%
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0.000892 / GB
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$0.001907 / GB
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One-year commitment price - Predefined Memory
$0.002669 / GB
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- No setup fee
For the latest information on pricing, visithttps://cloud.google.com/compute/pricin…
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- Free Trial
- Free/Freemium Version
- Premium Consulting/Integration Services
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Google Compute Engine Load Balancing, a quick introduction
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Computing with Google Compute Engine
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RouterOS CHR deployment in Google Compute Engine (GCE) demo
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Creating Custom Images for Google Compute Engine
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Hands on with Load Balancing on Google Compute Engine
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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
Google Compute Engine Videos
Compute Engine in 2 minutes
What is Compute Engine?
Google Compute Engine Competitors
Google Compute Engine Technical Details
| Deployment Types | Software as a Service (SaaS), Cloud, or Web-Based |
|---|---|
| Operating Systems | Unspecified |
| Mobile Application | No |
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 8.3.
The most common users of Google Compute Engine are from Small Businesses (1-50 employees).
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April 26, 2024
High Performance, Scalable Cloud Computing with Seamless Integration with other Google Services.
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.
April 11, 2024
Google Compute Engine Review
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
March 30, 2024
Highly Available and Cost Effective Cloud Provider
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
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.
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
March 20, 2024
High productivity and good ROI with unique services
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
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
March 11, 2024
Perfect for rapid developments and scalability
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
Our specific department uses google cloud for its data analytics capabilities but also for its scalable and flexible virtual/compute infrastructure. We have some large jobs that we will provision ad-hoc compute to assist as needed. Google Compute Engine excels in this area and has never failed us.
- Auto Scaling
- Flexible Instance Sizes
- Easy to understand pricing model
- More inside the UI advanced capabilities would be nice
- Customer is currently forced to learn the CLI to do advanced functions / scripting
- Stability is just not the same as other cloud providers in our experience.
October 04, 2019
Best in breed mid market cloud compute: GCE
Google Compute Engine (GCE) is used for most of the AI workload spanning both on-prem private cloud and public cloud. It is used for both onetime training phase for our Deep Learning workload as well as ongoing Deep Learning inference for customer facing applications.
- East interface to scale up and down the compute capacity
- Easy, straight forward billing and chargeback capabilities
- Reliability / uptime is great and had no issues so far on uptime
- Works well in multi cloud environments
- Although not always used, there is room for adding more detailed and granular management console when things go wrong (and sometime they do)
- Documentation can sometime be hard to find especially for using GCE for time critical, large scale deployments
- There are also some compatibility issues when running custom libraries over GCE. Support for third party drivers and libraries can be improved.
September 28, 2019
The Foundation for Cloud Processing
Google Compute Engine is used for a variety of workloads. Its use is growing as larger parts of the organization start embracing cloud computing.
- Internal applications.
- Tools.
- QA and testing environments.
- Production deployment.
- Experimentation with new technologies.
- Migration from datacenter to cloud environments.
- Training environments (they can be easily created and then deleted after the training).
- Business processing.
- Data processing and pipelines (in combination with various other products available in Google Compute Platform (GCP).
- Easy and fast creation of the resource.
- Rich ecosystem of tools and cloud technologies.
- Ability to scale up and down, based on the needs.
- Better documentation.
- Up to date documentation.
- Capabilities on par with AWS.
August 19, 2019
Google's Compute Engine is Good if You Like the Google Ecosystem, and Probably Even if You Don't Like Google
Google Cloud Compute Engine is used by the organization to do automated advanced analytics for clients across the world. The software addresses two important aspects of our business: first, it runs in the background and with speed and accuracy that works well for the analyst as well as others; second, the software runs in the cloud, which makes analyzing the data generally easier.
- Google Cloud Compute Engine does a good job at crunching numbers.
- Google Cloud Compute Engine is great at always being available, and I have yet to find any latency.
- Google Cloud Compute Engine is great for doing advanced analytics (machine learning) without needing the software on my desktop.
- Google Compute Engine is in the cloud, which means that it is probably less secure than on-premise options. With that said, I have never had a problem.
- Google Compute Engine seems fine at running machine learning models, but is in no way as good as competing tools that are not run in the cloud.
- Google Compute Engine is less user friendly than AWS or Azure, at least that's my experience.
May 24, 2019
Host scalable and globally distrubuted compute systems to get best value for money in cloud
We use Compute Engine for one of our main consumer and business products. We have a globally distributed infrastructure for this. I believe we are using almost all the features/functionalities offered by GCE. e.g Instance, groups/templates with full rolling updates capability coupled with CI/CD. We also host part of our monitoring systems in GCE. Other than that, some other teams are on the POC phase for some critical backend products as well. Moreover, we experiment with some of our machine learning on Compute Engine. The benefit we get by using GCE is the combination of the autoscaling, rolling updates, preemptability, and global network.
- Advanced autoscaling logic to cater scenarios that involve high load at the global level.
- Seamless and reliable rolling updates with support for releases.
- Backup data via very fast snapshots helps to quickly back up systems
- Good support for things like metadata (pre-defined and custom).
- Ability use Windows client OS VMs (or support import capability)
- Increase the offered default monitoring metrics set.
- Adjustable shutdown cooldown period (instead of fixed 30 seconds window).
February 24, 2017
Google Compute Engine: The ONLY choice for cloud computing
We develop software for our clients and lean on Google Compute Engine and Google Container Engine for hosting those applications. These applications are used both across our clients' organizations as well as publicly by customers of these clients. We made the decision to use Google Compute Engine in order to reduce costs while getting solid reliability from a VPS platform. Google has provided us with both of those needs.
- Spinning up new systems is a breeze. We are able to auto-scale our container engine clusters easily based on CPU usage or resource reservations.
- Cost is ~1/2 of AWS in general. Google advertises this and so far they've been true to their word. They provide sustained-use discounts if you run systems that stay online for an entire month.
- The command line interface is very easy to use. Setting up new environments is simple since the process can be scripted through the command line.
- The L7 load balancer can be difficult to get set up. It's limited in its functionality, especially with the container engine.
- It's hard to find certain objects on the web console. Often times the things I need to get to are buried in advanced menus.
- Google's decision to only support MySQL on their relational DB service means that I have to manage Postgres instances in Compute on my own, managing everything from storage to backups.