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
IBM Cloud Foundry
Score 6.0 out of 10
N/A
IBM Cloud Foundry is an IBM version of the open-source platform designed for building, testing, deploying, and scaling applications. Enterprises can run Cloud Foundry in a public isolated environment, while natively integrating with other IBM Cloud services, such as AI, Blockchain, and IoT.
$0.07
Per GBH
Pricing
Google Compute Engine
IBM Cloud Foundry
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
Community Runtimes
$0.07
Per GBH
Offerings
Pricing Offerings
Google Compute Engine
IBM Cloud Foundry
Free Trial
Yes
Yes
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.
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More Pricing Information
Community Pulse
Google Compute Engine
IBM Cloud Foundry
Considered Both Products
Google Compute Engine
Verified User
Anonymous
Chose Google Compute Engine
Cloud providers offering virtual machines are quite common. I think, Google, however, is arguably one of the top players in the market, with some of the largest (if not the largest) and most advanced server farms in the world. If you're looking for reliability and cost …
The perfect blend of setup flexibility, costing and trust of Google could be my answer to the comparison. This being a server backed service so, ruling out the functions. The Setup flexibility and speed set the GCE apart from Kubernetes. Compliance, regulation and the security …
We have tried using DigitalOcean droplets for some of our minor and non critical VMs. In our experience, Google Compute Engine fares well in comparison the DigitalOcean droplets as they provide better availability, better support and in general, a better experience.
As far as user-friendliness is concerned, I personally rank Google Cloud above both AWS and Azure. Their user interface makes it easy to manage, which is important.
I find Google Compute Engine to be much easier to use than Amazon's EC2 service. The console makes much more sense, permission management is much cleaner, and I'd say the other categories feel on par with EC2: performance, how fine-grained the settings are, connecting to …
The obvious and natural alternatives to GCE are AWS EC2 and Azure VMs. I would say all three are more similar than not. Picking one will most likely depend on what platform you're on already, where your running services are, and which one is more familiar to your team.
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 …
The Google Cloud computing engine is fair at the top because it bills customers, automatic discounting for extended use, and how fast it can be turned on. We enjoy things around setting it up very easily via APIs and CLI commands, and with the always-on recommendations from …
I have utilised Google Compute Engine in addition to Amazon EC2. Both exhibit excellent performance in terms of consumption, speed, and efficiency.My decision to adopt Google Compute Engine was solely based on how user-friendly it is. more basic UI/UX than EC2.Google's customer …
Google Compute Engine provides on-demand computing resources that are easy to scale up or down according to my organization needs. This allows our business to quickly adapt to changes in demand without having to invest in additional hardware. It also offers a very competitive …
While Amazon EC2 is the best tool for developers to build an app and make it live, It has some downsides too. EC2 requires so much development while Google Compute Engine makes it easy to build an app within a days. EC2 pricing also relatively high compare to Google Compute …
GCE is available in 3 different regions whereas Ec2 is available in 11 different regions. The compute resources offered by the GCE has lower maximum capacity compared to AWS Ec2. The pricing model of GCE offers first 10 mins free and then charging in increments of 10 mins. Both …
I prefer the Compute Engine Over these as it provides us with Better Scalability, Performance, and Reliability Security-related Issues don't arise with the Compute Engine, but yes, in terms of accessing or running, it can be improved a bit as compared to EC2 offered by AWS.
the main reason of choosing GCE is availability and user friendly UI with a very good documentation and API explanations. Great visibility over the infra and security.
The features specific to Google Compute Engine vs Amazon EC2 along with cost and availability are comparable, there may be other services within the vendor which may mean that one is more suitable for specific applications than the other one. We have used both for different …
Google Compute Engine provides a one stop solution for all the complex features and the UI is better than Amazon's EC2 and Azure Machine learning for ease of usability.
It's always good to have an eco-system of products from Google as it's one of the most used search engine and …
AWS has become the de facto standard. Skills in Google Compute Engine and AWS are not easily transferable. Still, after getting to know Google Compute Engine well, productivity can be very high and ROI impressive. There are many additional services offered around Google Compute …
IBM Cloud Foundry is our first choice industry-standard platform as a service (PaaS) which has always provided us with quicker, simpler, and more consistent ways for the deployment of the cloud-native applications which in result saved us lots of time and money.
Why I prefer IBM Cloud Foundry platform over AWS Elastic Beanstalk or Heroku Platform is the automation of development process and pushing of projects to cloud with clear step by step instructions - which is available on the documentation. I can say categorically, the terminal …
Cloud Foundry has lot of benefits because platform as a service provided for the developers to implement applications based on the use cases. Different use cases required different buildpacks to run on. It has flexibility to code, push, and run flexibility. Provided ease of use …
We have had to move our deployments to Kubernetes because we needed more reliability. We moved to Google because IBM rates and billing was so backward and expensive. Our client was also very angry at all the outages, lost revenue, production down time and inordinately expensive …
While we are still looking at kubernetes and other services, we will continue to use Cloud Foundry because of the advantages it provides. The support from IBM is good and take a lot of work that our developers and ops had to do away.
It is a cloud-based solution and for all my customers that want to migrate to cloud, this is the solution that we are proposing to customers, as it provides a lot of benefits over private cloud. Scalability and resiliency are not a major challenge and it can be used with other …
CF is what we initially went with to establish a development pipeline and start our cloud journey, now we are expanding this and although we are now pulling in many other tools and functions around CF, it is not being replaced. It stands out as having a key place working ‘with’ …
IBM Cloud Foundry (CF) is simpler and there is a service model that fits most of our internal services. We are going to Loopback for API and Node.js and we have an easy path to go with Bluemix. It's a very easy way to start if you are moving to the cloud and mainly if you are …
We chose to go with more bare metal options since Bluemix didn't really offer these at the time. It was simpler to get up and running with the bare metal service, and we felt that any problems we ran into would be a result of our own incompetence rather than problems with the …
Solution Analyst — Machine Assisted Service Enagagement
Chose IBM Cloud Foundry
I have use EC2 and Microsoft's Azure. To me, both Azure and Bluemix were fantastic, but they each had some pros and cons. Azure had more services to offer, but their biggest flaw was in their inability to integrate and work with external platforms, APIs, Programs, etc.. Like …
While IBM works well is when being used by large organizations, these other vendors work well with smaller organizations. We ended up being willing to pay more for Heroku, as they have such an easy-to-use service, and our deployments worked as expected every time.
Used AWS and Azure. AWS has more features and a far superior interface responsivesness. It's actually usable! That being said default configurations and menus in AWS are more cryptic then necessary. Azure seems to be the gold standard for pre-configuration and ease of use. …
Bluemix had a much easier route to get into the artificial intelligence side of things with Watson skills. It also seemed a lot more straightforward to use things like the Weather Channel data, sentiment analysis... etc., than the others. I'd also had a bad experience with AWS …
We have used Red Hat which does not do business in Australia with people like us. They were a promising service (PaaS) while we were able to use the free version but as soon as we needed access to serious mobile-first services we had to pay and their policy meant we had to …
I like when the provider offers cloud deployment via standard orchestration mechanisms (like Docker, Kubernetes, DCOS) This is currently well covered by Azure. Amazon also has good flexibility (supports Kubernetes, DCOS). It's good that Bluemix added support for Docker and …
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.
IBM Cloud Foundry is a solid service from the IBM Cloud platform. It is easy to learn, and does not usually require you to make drastic changes to your existing applications. It is especially good for new applications that are cloud native, or micro-services, that can be easily updated and deployed. With its blue/green deployment, you can achieve 0 downtime for your customers.
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.
Intuitive user interface makes it easy for anyone to use, regardless of their professional background.
A lot of the services integrate well with external platforms, APIs, and programs, not just IBM services. A lot of the competitors in this space lack this ability.
Maybe it is just our contract in particular, but support and help is always made available.
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.
Sometimes the API Connect GUIs don't cleanly disengage after attaching models or updating schema and it is hard to know what has been written successfully and which (if any) models or tables were missed. I shouldn't have to manually check through a list of 377 models to find the ones in and out of a list on either models, folder or database tables. Printing a summary even in logs which did a "diff" sort of thing between 'task-set' and 'task-completed' (referring to attaching models or updating schema as tasks here as 'tasks').
Provide access to Postgres Database in Sydney datacentre for Australia.
Clearer documentation around setting up a secure (referring to SSL and certificate setup here) server on eg, chubby1.au-sydney.mybluemix.net.
Allow a ramp in pricing onto the Blockchains. We will not be able to afford it until quite a few years into production, even if we launch successfully.
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.
IBM Cloud Foundry is our first choice industry-standard platform as a service (PaaS) which has always provided us with quicker, simpler, and more consistent ways for the deployment of the cloud-native applications which in result saved us lots of time and money.
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
This was the founding solution used to allow us to move in to and test out a cloud pipeline. This is what paved the way for a full production cloud solution to be possible.
Having Cloud Foundry at the base of our development and sandpit environment, segregated away from our standard on premise solution has moved away red tape and ensured an agile way forward.