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.
$0.01
Hour
OVHcloud Public Cloud
Score 8.0 out of 10
N/A
OVHcloud Public Cloud offers users a large number of cloud solutions that are billed on a pay-as-you-go basis. OVH states their infrastructure is set up in a simple way to enable businesses to harness the flexibility of on-demand resources to scale up from small projects to large-scale deployments.
$0.01
Hour
Pricing
Google Compute Engine
OVHcloud Public Cloud
Editions & Modules
Preemptible Price - Predefined Memory
0.000892 / GB
Hour
Three-year commitment price - Predefined Memory
$0.001907 / GB
Hour
One-year commitment price - Predefined Memory
$0.002669 / GB
Hour
On-demand price - Predefined Memory
$0.004237 / GB
Hour
Preemptible Price - Predefined vCPUs
0.006655 / vCPU
Hour
Three-year commitment price - Predefined vCPUS
$0.014225 / CPU
Hour
One-year commitment price - Predefined vCPUS
$0.019915 / vCPU
Hour
On-demand price - Predefined vCPUS
$0.031611 / vCPU
Hour
Discovery
$0.01
Hour
General Purpose
$0.08
Hour
Compute Optimized
$0.12
Hour
Memory Optimized
$0.12
Hour
Offerings
Pricing Offerings
Google Compute Engine
OVHcloud Public Cloud
Free Trial
Yes
No
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
Prices vary according to region (i.e US central, east, & west time zones). Google Compute Engine also offers a discounted rate for a 1 & 3 year commitment.
Exact pricing depends on operating system (Windows/Linux), memory and storage size and network speed.
More Pricing Information
Community Pulse
Google Compute Engine
OVHcloud Public Cloud
Features
Google Compute Engine
OVHcloud Public Cloud
Infrastructure-as-a-Service (IaaS)
Comparison of Infrastructure-as-a-Service (IaaS) features of Product A and Product B
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.
For demo uploads or for production uploads of companies from different sectors looking for a "general computing" cloud solution, I think that OVH can be a good provider. However, for more delicate or advanced loads or for specific solutions of, for example, AI, OVH has a wide margin for improvement.
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.
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.
Its pretty good, easy and good performance. Also, interface is very good for starters compared to competitors. Infra as Code (IaC) using Terraform even added easiness for creation, management and deletion of compute Virtual Machines (VM). Overall, very good and very easy cloud based compute platform which simplified infrastructure, very much recommend.
Having interacted with several cloud services, GCE stands out to me as more usable than most. The naming and locating of features is a little more intuitive than most I've interacted with, and hinting is also quite helpful. Getting staff up to speed has proven to be overall less painful than others.
Google Compute Engine works well for cloud project with lesser geographical audience. It sometimes gives error while everything is set up perfectly. We also keep on check any updates available because that's one reason of site getting down. Google Compute Engine is ultimately a top solution to build an app and publish it online within a few minutes
The raw computer power is excellent; our applications feel snappy, pages load almos instantly for our customers and so on. The primary reason it is not a perfect 10 is that the native tools for monitoring individual VM performance can be complex, making it challenging to easily diagnose specific resource bottlenecks without significant configuration
The documentation needs to be better for intermediate users - There are first steps that one can easily follow, but after that, the documentation is often spotty or not in a form where one can follow the steps and accomplish the task. Also, the documentation and the product often go out of sync, where the commands from the documentation do not work with the current version of the product.
Google support was great and their presence on site was very helpful in dealing with various issues.
When configuring Amazon ECS, it is a bit confusing as you are not able to find the actual issue. You need to enable Additional AppInsights to get detailed level info, which is not a concern when configuring on the Instance Level. Moreover, Azure VM does not provide an in-browser option; instead, it is Azure Bastion, but for that, you have to enable a dedicated subnet, which is a bit unnecessary.
Most notably OVHcloud [Public Cloud] has dedicated servers which are a different breed of product than Linode's flagship VPS servers, the unfortunate fact of the matter is that OVHcloud [Public Cloud] can provide a fully-dedicated server at a lower price point than Linode's virtual server. Even worse than that is that with a dedicated server from [OVHcloud Public Cloud] there is zero chance of "cpu theft" (aka, noisy neighbor) which is a very real problem at Linode (we would require multiple migrations every year for servers hosted at Linode that were experiencing cpu theft). In addition to the improvement in quality for network/hardware at OVHcloud [Public Cloud] with their dedicated server offering, their VPS servers are also highly competitive against Linode's VPS servers - in the 2 years we've used OVHcloud [Public Cloud] VPS's we've had zero downtime associated with OVH actions such as host-node reboots or cpu theft or host node upgrades, a stark difference compared to Linode which regularly experiences those types of downtimes and many more on a very regular basis.
Scalability means flexibility and less upfront costs
Can become expensive when hard set compute requirements are clear, but things like Spot VMs can help here too, or just having your own infrastructure and scaling up with Google. This is for more advanced cases though
Ramp up time is long, but after that it is quick to do many things and ROI is awesome