Security controls (27)
Operating system support (27)
Pre-defined machine images (27)
Monitoring tools (27)
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Preemptible Price - Predefined Memory
0.000892 / GB
Three-year commitment price - Predefined Memory
$0.001907 / GB
One-year commitment price - Predefined Memory
$0.002669 / GB
Entry-level set up fee?
- No setup fee
- Free Trial
- Free/Freemium Version
- Premium Consulting / Integration Services
Starting price (does not include set up fee)
- $0 GB
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.
Predefined Machine Types
Virtual machine configurations for micro instances to instances with up to 160 vCPUs and 3.75 TB of memory
Custom Machine Types
Or create and customized, virtual machines with the shape (i.e. vCPU and memory) needed for each project
Network storage, up to 64 TB in size, can be attached to VMs as persistent disks. Create persistent disks in HDD or SSD formats. If a VM instance is terminated, its persistent disk retains data and can be attached to another instance. Take snapshots create new persistent disks from that snapshot.
Always-encrypted local solid-state drive (SSD) block storage. Local SSDs are physically attached to the server hosting the virtual machine instance. Local SSD sizes up to 3 TB are available for any VM with at least 1 vCPU.
Global Load Balancing
Distribute incoming requests across pools of instances across multiple regions.
Cost effectively run large compute and batch jobs using Preemptible VMs. Fixed pricing and no contracts or reservations make it easy: simply check a box when you create the VM and turn them off when the work is done.
Run, manage, and orchestrate Docker containers directly on Compute Engine VMs or with Google Kubernetes Engine.
- Being able to leverage Google's pricing has saved us considerable sums of money
- Being able to scale up on demand saves our customers a considerable amount of time
- It acts as a fantastic resource for multi-cloud strategies including backups
- It helps us deploying the services faster.
- Better monitoring and alerting to monitor the systems.
- Cost reduction with VMs usage recommendations.
- All of our work is R&D right now, so none. We started our workloads in the cloud so we don't have any on-prem to compare to.
- Some of the automated infrastructure deployments we have been able to do on GCE have saved us hassle for our production deployments and allowed us to have periods of downtime for our automated deployment testing environment saving compute resources
- We are able to run several production deployments for several different customer facing products at a comparable cost to what it cost to run one production deployment at a competitor. This is likely due to a combination of the savings mentioned in my earlier point, better pricing on GCP, (and likely Moore's law to some extent where the necessary compute just gets cheaper over time).
- GCP deployments streamline some of the tasks that I do frequently. That's gotta count for something.
- The best price/performance factor in cloud providers (AWS, Azure, GCP).
- Anticipated costs.
- Time to market - due to reused scenario.
- Allowing GCE to handle the infrastructure has allowed us to focus our time on our product.
- The ease of spinning up new instances for development and testing has allowed us to be more productive.
- Positive impact on the OpEx with reduction in CapEx resulting from reducing the time to move a workload from on-prem to the cloud
- Incased RoI by reducing need for on-prem compute
- Improved agility by providing the option to take on new AI workloads for test and dev without the need for upfront investment in
- Dynamic allocation of computing when we need them.
- Faster experimentation.
- Reduced time troubleshooting.
- Because GCE is not mission-critical for us, I would not be able to speak to ROI. Since our machines and instances are almost a match, once configured, there's really no difference.
- Bean counters will be able to speak to ROI.
- Saves time.
- Cost management.
- Manage computing resources.
- Avoid the high costs.
- Assure business continuity
- Google Compute Engine has had a positive return on investment in that it has expanded the offerings of the business, and clients seem to like the shift towards Google services.
- Google Cloud Compute Engine was a poor return on investment at first because it required a good deal of effort to figure things out.
- Google Cloud Compute Engine is a positive return on investment by allowing multiple users to work on the same project in the cloud.
- Preventing the necessity of any on-prem systems or hardware.
- Reduction in complexity from AWS. We no longer need to maintain custom images.
- Reduction in costs from AWS.
- Reduce costs
- Management the resources
- Assure redundancy
- Be in compliance with the business needs
- We have reduced our costs with local/physical servers.
- We have improved our performance from planning to projects execution.
- We have been able to create server instances in regions of the US where AWS doesn't have a data center, which has allowed us to secure customers with the highest performance possible, instead of having them connect to AWS data centers much further away.
- Positive: We had good cost savings
- Positive: Very good stability and reliability compared to hosting in on-prem.
- Negative: Had to re-architect some part of the application to fit the limitations.
- Positive. Suggestions on re-configuring specs. If you aren't using all the RAM or CPU threads, suggestions are sent to re-configure your virtual machine to minimize your bill at the end of the month.
- Negative. Expensive custom machines. If you're looking for a more exact figure of RAM or CPUs, the virtual machines get quite expensive fairly quickly.
- Negative. Internet bandwidth variability. The internet bandwidth you get, from my experience, is all dependent on your luck. :(
- Less worry about infrastructure
- Cheaper than competitors
- Good customer support
- 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.
- Google Compute Engine's startup prices are quite reasonable to get started.
- Started with $300 free credits that help to sustain the business structure.
- Our primary servers hosted at our nearest locations that help to reduce time to load. Also getting good feedback from users server speed is overall because of closest location.
- We can spawn up almost any amount of "cores" at anytime, which is very helpful for data processing.
- GCE has had a positive impact on our ROI. We made the switch from Rackspace and saved something like 40% off our monthly VM costs.
- It's allowed us to have almost 100% up time since switching to it.
- 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.