GCP Cloud's Google Compute Engine
We use GCP (Google Cloud Platform) for following purposes:
- VM instances for Linux as well as Windows
- GKE Cluster for hosting self …
- VM instances for Linux as well as Windows
- GKE Cluster for hosting self …
Starting at $0 per month GB
View PricingOverview
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.
Recent Reviews
Awards
Products that are considered exceptional by their customers based on a variety of criteria win TrustRadius awards. Learn more about the types of TrustRadius awards to make the best purchase decision. More about TrustRadius Awards
Popular Features
- Security controls (44)7.070%
- Operating system support (44)6.969%
- Pre-defined machine images (43)5.656%
- Pre-configured templates (42)5.252%
Reviewer Pros & Cons
Pricing
Preemptible Price - Predefined Memory
0.000892 / GB
Cloud
Hour
Three-year commitment price - Predefined Memory
$0.001907 / GB
Cloud
Hour
One-year commitment price - Predefined Memory
$0.002669 / GB
Cloud
Hour
Entry-level set up fee?
- No setup fee
For the latest information on pricing, visithttps://cloud.google.com/compute/pricin…
Offerings
- Free Trial
- Free/Freemium Version
- Premium Consulting/Integration Services
Product Demos
Google Compute Engine Load Balancing, a quick introduction
YouTube
Computing with Google Compute Engine
YouTube
RouterOS CHR deployment in Google Compute Engine (GCE) demo
YouTube
Creating Custom Images for Google Compute Engine
YouTube
Hands on with Load Balancing on Google Compute Engine
YouTube
Features
Return to navigation
Product Details
- About
- Competitors
- Tech Details
- FAQs
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 8.2.
The most common users of Google Compute Engine are from Small Businesses (1-50 employees).
Comparisons
Compare with
Reviews and Ratings
(172)Attribute Ratings
Reviews
(1-5 of 5)Companies can't remove reviews or game the system. Here's why
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
55%
5.5
- We are promised lower total cost and some discounts are in place
- In practice, at first migration, the cost is just as high as any prior cloud
- However, with clever use of APIs we should get a positive ROI
- Amazon Elastic Compute Cloud (EC2) and Azure Kubernetes Service (AKS)
Similar in capabilities, slightly slicker APIs and CLIs. More observability in the default UI and the CLIs. Easier to setup, the google console is slick. Azure has a good user interface as well with lots of documentation to help. CLI is slightly less intuitive, but decent. AWS I find is the most lacking, most convoluted and complex.
- CLI
- API
- Instance management
- Networking setup
- Orchestration
- Scheduled instance allocations
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.
78.75%
7.9
- Dynamic allocation of computing when we need them.
- Faster experimentation.
- Reduced time troubleshooting.
- Amazon Elastic Compute Cloud (EC2)
Google Compute Engine has similar capabilities and features as Amazon EC2. Their ecosystems differ, and Amazon has a lead in more innovative products, but Google is working on closing the gap. If sticking to the essential functionality of computing, Google Compute Engine and Amazon EC2 are practically interchangeable; we run workloads on both. We appreciated the more cost-effective solution offered by Google Compute Engine for our use cases.
We use Google Compute Engine to host our cloud-based web application. We manage a multi-node, shared instance of our application for thousands of monthly users, as well as individual, dedicated instances for a few of our larger clients. We are a fairly small organization and GCE manages all of our hosting needs.
GCE is very straightforward to use, most of our engineers interact with it on a daily basis. Using GCE means that we can forget about the pains of maintaining computing hardware and just focus on making great software. As a Google Apps user, we also benefit from GCE's rich integration with the rest of the Google product line. Picking GCE over competitors was an easy choice for us.
GCE is very straightforward to use, most of our engineers interact with it on a daily basis. Using GCE means that we can forget about the pains of maintaining computing hardware and just focus on making great software. As a Google Apps user, we also benefit from GCE's rich integration with the rest of the Google product line. Picking GCE over competitors was an easy choice for us.
- A simple web-based interface that is a breeze to train new engineers to use. Our experienced engineers never have trouble finding or doing anything on GCE.
- Sustained use and Committed use discounts mean we get top-tier VMs for an incredibly competitive price.
- Wonderful identity and access management that gives us peace-of-mind when granting access to machines to contractors and other 3rd parties.
- Fast VMs, lastest in hardware, and enough RAM to power even the hungriest of our services.
- Built-in monitoring via Stackdriver is quite expensive for what it provides.
- Initially provided quotas (ie. max compute units one can use) are very low and it took several requests to get an appropriate amount.
- Support on GCE is limited to their knowledge base and forums. For more hands-on support provided by Google, you must pay for their Premium services.
70%
7.0
- We don't need to hire server admins or infrastructure engineers and instead our web engineers are more than capable of maintaining all of our services.
- Fast-boot VMs and top-tier SLA mean that GCE keeps up with our fast release cycle.
- We use instance templates to quickly launch dedicated services for our clients. They are often amazed at our less than a 24-hour turnaround.
- Amazon Elastic Compute Cloud (EC2), DigitalOcean and Heroku
GCE was an easy choice for us after evaluating our options. We needed something that was dynamic enough to handle our specialized stack, but easy enough that our engineers weren't spending too much time configuring and launching. We found AWS's offering to be similar but confusing in use resulting in misconfigured services and bloat. We used DigitalOcean for a time but outgrew them once our service required more than a few dozen nodes. Heroku was easy to use but ultimately could not handle our unique set of services. Finally, GCE's rich integration with the rest of the Google product line made it easy for our engineers to begin using it with their existing Google Apps accounts.
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.
91.25%
9.1
- With Google Compute we don't have the overhead of managing our own data centers reducing costs and reducing the staff needed to manage systems.
- As I said earlier, Google's costs are ~1/2 of AWS, so we are able to see a ROI much faster.
- AWS and Azure
We ultimately chose Google Compute for the price difference as compared to other providers. Google's pricing for Windows servers is even lower than Microsoft's own cloud service, Azure. The terminology used across Google Compute is much easier to understand than the competitors. Rather than S3, Google's file storage service is simply called "Storage". Rather than Lamba, Google's serverless platform is just called "Cloud Functions". It's very easy to get up and running quickly with Google Cloud.
April 11, 2016
Google Compute Engine Review
It is being used by a department. It is used to host our school department's website, which is used by both teaching assistants and students.
- UNIX-style command line tools
- Web-based console panel
- Persistent disks
- Web console is a bit slow
87.5%
8.8
- It has been cheaper overall to host our website.
Google App Engine is slower in comparison, and costs more than Google Compute Engine. We chose Google Compute Engine because Google App Engine was way too slow (mainly due to having to use Google Cloud Storage).