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
per month GB
IBM Cloud Code Engine
Score 8.8 out of 10
N/A
IBM Cloud Code Engine is a fully managed, serverless platform that unifies the deployment of containers and applications including web apps, microservices, event-driven functions, or batch jobs. This serverless compute service aims to remove the burden of building, deploying, and managing workloads in Kubernetes so users can focus on writing code and not on the infrastructure that is needed to host it. With IBM Cloud Code Engine users can run any workload…
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Pricing
Google Compute Engine
IBM Cloud Code Engine
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
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Offerings
Pricing Offerings
Google Compute Engine
IBM Cloud Code Engine
Free Trial
Yes
Yes
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
No
Yes
Entry-level Setup Fee
No setup fee
Optional
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.
You can use Google Cloud Compute Engine as an option to configure your Gitlab, GitHub, and Azure DevOps self-hosted runners. This allows full control and management of your runners rather than using the default runners, which you cannot manage. Additionally, they can be used as a workspace, which you can provide to the employees, where they can test their workloads or use them as a local host and then deploy to the actual production-grade instance.
It would be a good solution for running serverless applications. Because infrastructure setup and maintenance expenses can be avoided, the investment will pay for itself. The time to value is short, allowing IT to respond to business demands quickly. It aided us in customizing security as well as operating a personal project using to autoscale up and down approach. Also, because there isn't much hassle, items can be pushed into production as soon as possible. Simply push a container, create an application, and you're ready to go. But, It is less suited when you have a static machine or need to keep data in some way and do not want to utilize network storage or a database.
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 structure is complicated, and the servers are expensive. I really think they should offer better pricing options and support for more languages
sometimes the servers go down, and they take too long to respond to support tickets
uploading documents is slow since I have to do it one by one, making the process much longer than it should be
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.
Consumers can purchase individual components as well as unlocking new bundles with special features and services including the extensive data management governance capabilities of the Automation range. Kubernetes containerizing for effective service implementation and an agile, flexible multi-cloud data program help both utilization expansion and deployment to be improved by this architecture.
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
It works great all the time except for occasional issues, but overall, I am very happy with the performance. It delivers on the promise it makes and as per the SLAs provided. Networking is great with a premium network, and AZs are also widespread across geographies. Overall, it is a great infra item to have, which you can scale as you want.
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.
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 IoT services provider, which helps with ease of integration and updates in the future.
What impresses me most about IBM Cloud Code Engine is the container workload management capability and the Cloud services and dataflow monitoring functionalities. Data security and network security control via IBM Cloud Code Engine is quite excellent and very responsive data integration functions and the first deployment is not very technical.