Filter Ratings and Reviews
Filter 105 vetted Google Compute Engine reviews and ratings
Reviews (1-25 of 25)
April 23, 2020
Why GCE can be considered as a DR multicloud scenario
For hybrid cloud solution we decided to use the separated cloud provider as a DR (pilot light model) in our project. Compute Engine was created in one Region with general purpose machine family. The project requirements were set - one of the first priorities - cloud provider independence.
- Project base access.
- Well tested DR scenario.
- Competitive overall prices.
- Less flexible machine type selection.
- Sometimes non-intuitive interface.
- Limited network configuration.
October 04, 2019
Best in breed mid market cloud compute: GCE
Google Compute Engine (GCE) is used for most of the AI workload spanning both on-prem private cloud and public cloud. It is used for both onetime training phase for our Deep Learning workload as well as ongoing Deep Learning inference for customer facing applications.
- East interface to scale up and down the compute capacity
- Easy, straight forward billing and chargeback capabilities
- Reliability / uptime is great and had no issues so far on uptime
- Works well in multi cloud environments
- Although not always used, there is room for adding more detailed and granular management console when things go wrong (and sometime they do)
- Documentation can sometime be hard to find especially for using GCE for time critical, large scale deployments
- There are also some compatibility issues when running custom libraries over GCE. Support for third party drivers and libraries can be improved.
August 22, 2019
Google Cloud Engine -- a cost-benefit comparison is sorely needed. Because everything else is there.
We use Google Compute Engine for staging deployments in the web development department. We are operating off an external assessment that competitor services offer better pricing on production units, so we've agreed to keep Compute Engine in a low tier staging system only. We have yet to do our own audit from an internal efficiency perspective, and how that will impact pricing assessments.
- Compute Engine is gaining traction, and documentation is getting easier to find.
- Menus and services are structured more intelligently.
- The idea of poor Support from the Google brand prevents my technicians from picking up the phone.
- It's easier to find EC2 experts to consult and support mission-critical operations.
August 19, 2019
Google's Compute Engine is Good if You Like the Google Ecosystem, and Probably Even if You Don't Like Google
Google Cloud Compute Engine is used by the organization to do automated advanced analytics for clients across the world. The software addresses two important aspects of our business: first, it runs in the background and with speed and accuracy that works well for the analyst as well as others; second, the software runs in the cloud, which makes analyzing the data generally easier.
- Google Cloud Compute Engine does a good job at crunching numbers.
- Google Cloud Compute Engine is great at always being available, and I have yet to find any latency.
- Google Cloud Compute Engine is great for doing advanced analytics (machine learning) without needing the software on my desktop.
- Google Compute Engine is in the cloud, which means that it is probably less secure than on-premise options. With that said, I have never had a problem.
- Google Compute Engine seems fine at running machine learning models, but is in no way as good as competing tools that are not run in the cloud.
- Google Compute Engine is less user friendly than AWS or Azure, at least that's my experience.
We use compute engine across a number of departments at our company. We deploy temporary workloads to VMs on a daily basis and have deployed our production systems to GCE for deployment and CI/CD pipelines, ETL for data projects, and for large-scale customer engineering.
GCE is in play primarily for our engineering department as well as our customer engineering and sales teams.
GCE is in play primarily for our engineering department as well as our customer engineering and sales teams.
- GCE is excellent at cost management. We are able to manage billing to the second and set up rules to manage those expenses easily.
- GCE is fast! Our teams constantly provision/de-provision workloads and GCE is able to keep up well, no matter the type or number of servers that need to be spun up.
- The configuration is extremely easy. The UI is being improved and tweaked on a regular basis to keep up with UI/UX trends and make it easy for users to do everything from the console. That said, the API is extensive and powerful. Many of us prefer the CLI for bulk actions.
- Windows management is lacking. When managing a Windows machine, it's nearly always necessary to RDP into the machine and an agent would be very helpful for system-level API calls.
- Stackdriver integration could be rolled out better. We would like to see more standard monitoring functionality and metrics built-in for instant deployment when using a new project.
- Inter-project organization. It's difficult to connect different GCP projects in order to share a VPC. Once that is complete, it's nearly impossible to extricate them.
August 12, 2019
Reliable and user-friendly IaaS platform
We use Google Compute Engine as IaaS provider across the whole organization. Almost all of our servers are deployed in this environment. We also help some of our customers to deploy virtual machines due to our expertise in cloud computing. We think it is a reliable platform that delivers everything we need regarding IaaS.
- A friendly and intuitive graphical interface is available
- There are several resources available, such as networking and snapshots.
- The performance is amazing and you can select the region/zone close to your region.
- There is a shell environment that helps a lot
- Better price for Windows Server virtual machines
- The graphical interface to manage a specific VM could be improved.
August 12, 2019
Google Compute Engine: A Great "First Cloud"
Google Compute Engine is being used for Google Cloud Platform centralized workloads. With AWS as a primary cloud, GCE and GCP are used to support customers centralized in those systems. It is used by the entire organization, primarily to support customers in those environments with minimal latency. Since G Suite is also deployed, the tight integration is a benefit.
- Strong G Suite integration.
- Strong Infrastructure as Code (IaC) features.
- Easy to configure.
- Less availability than AWS.
- Can hide critical configuration features necessary for detailed performance tuning.
- Features can remain in beta for a long time.
The big advantage of using Google Computer Engine is that pricing is much less than if you bought your own hardware. You are only paying for what you need, there's no over-spend required for redundant systems. Google Compute Engine is one of the best IaaS cloud solution at the moment.
- Provides resizable compute capacity
- Great scalability and elasticity
- Very customizable
- Generous free tier
- Some loading issues
- Setup can be tricky
- No other problems
We use Google Compute Engine to host a variety of services including proxy servers, small websites, and peripheral services. Additionally, we make use of the Google Compute Engine to quickly spin up instances for testing and experimentation and then destroy them once finished without incurring a lot of costs, both money and time.
- GCE is well suited for multi-environment testing, development, and experimentation.
- Very cost effective.
- If you want to do something outside of a standard image it can be a little cumbersome.
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.
Using Google Compute Engine, you can manage your costs. It helps to avoid the high costs of buying hardware and setting up a new server infrastructure on your physical location. Also, Google Computer Engine offers you the possibility of accessing your files and data with higher security, and save days worth of time spent on setup and installation. We migrated from hardware to visualized servers hosted to Google Compute Engine. We made Windows and Linux servers and hostel our core-services: ERP, accounting, marketing app.
- Access files and data with higher security.
- Easy to manage.
- Create virtual machines very easily.
- Google Compute Engine is user-friendly.
- The price is good.
- Documentation can be more detailed.
- More costs options.
- No other recommendations.
August 23, 2019
Compute Engine supports all of our needs
We use Google Compute Engine to support almost all of our in house computer. We have a web application that has a distributed backend of various workloads, all of which run on Compute Engine. Some of these workloads are even containerized. These workloads support the whole organization and provide analysis for research and development.
- It can run containers.
- It is completely flexible in terms of CPU, memory, etc.
- It's APIs are useful for spinning up machines computationally.
- Running multiple containers on one VM.
We use Google Compute Engine for creating cloud virtual machines that are GPU-accelerated. Because we have centralized most of our backend services to DigitalOcean, we use Google Compute Engine for most of the services that DigitalOcean doesn't offer. Additionally, we use the custom image functionality that GCE offers to create VMs with custom images.
- Great scalability. The cloud VMs all have elastic specs functionality, but re-scaling some VMs may create a significant amount of downtime for your backend.
- GPU offerings. Google Cloud offers NVIDIA Tesla K80s, P4s, and P100s, which some of the cloud computing competitors don't offer.
- Downtime, Google's SLA is very good. I've never had a poor experience with downtime or maintenance on their services.
- Internet speed can be quite variable. The bandwidth for different instances ranges a lot. Some instances have had internet bandwidth that is in the range of 5-10x the speed of other instances.
- Customizability. Customizing the number of cores, RAM beyond what Google offers in their standard compute plans can get quite expensive.
- Firewalls/networking. Figuring out how to use these took way longer than necessary. Getting the right ports opened and forwarded took lots of reading, something that other services included in the creation/initialization process of virtual machines.
Google Compute Engine is used by the DevOps team for hosted Windows servers. This alleviates countless concerns with having a server on-site, and is very comparable to other hosting providers.
- We are able to select a custom amount of vCPU and Memory resources.
- It provides pricing estimates on the page when configuring a new instance (versus having to reference separate documentation).
- We are able to tie into G-Suite User Directory for access control to the Google Compute Engine console.
- It would be nice to move a Google Compute Engine Server to a different project without having to recreate it.
May 24, 2019
Host scalable and globally distrubuted compute systems to get best value for money in cloud
We use Compute Engine for one of our main consumer and business products. We have a globally distributed infrastructure for this. I believe we are using almost all the features/functionalities offered by GCE. e.g Instance, groups/templates with full rolling updates capability coupled with CI/CD. We also host part of our monitoring systems in GCE. Other than that, some other teams are on the POC phase for some critical backend products as well. Moreover, we experiment with some of our machine learning on Compute Engine. The benefit we get by using GCE is the combination of the autoscaling, rolling updates, preemptability, and global network.
- Advanced autoscaling logic to cater scenarios that involve high load at the global level.
- Seamless and reliable rolling updates with support for releases.
- Backup data via very fast snapshots helps to quickly back up systems
- Good support for things like metadata (pre-defined and custom).
- Ability use Windows client OS VMs (or support import capability)
- Increase the offered default monitoring metrics set.
- Adjustable shutdown cooldown period (instead of fixed 30 seconds window).
We use it for running managing docker containers inside clusters. GCE provides the flexibility for auto scaling and managing application performance easily. It used for running all the applications across departments
- Custom machine types gives us the flexibility of defining the right cpu and memory
- Load balancers are efficient
- Easily create instances using gCloud SDK
- Very little programming languages support
- Charged before usage
- Changing platforms is not easy
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.
Compute Engine is a general purpose VM on top of which you can run basically any software you want, including Windows. They are priced on per-hour basis with discounts when you use it for a long time, and also with an option to run a VM for a short time with significant discount, but at a risk that it could be terminated at any time (Preemptible VM) – it's very useful for data processing since you can spawn tens of VMs for cheap and even if they are terminated you can just do it again later.
- Per-hour pricing with sustained use discounts -- you'll get a good discount if you run a VM for a long time.
- Always free usage limits -- you can run a small VM on it completely free of charge!
- Preemptible VM – huge discounts when you only want to run it for a short time, but it could be terminated if there's a demand.
- GPU support -- useful if you want to control your ML training jobs by yourself instead of using their Cloud ML APIs.
- Sustained use discounts could be combined with committed use discounts -- just give me cheaper price if I'm running a VM for a year
October 11, 2017
My two years experience with Google Compute Engine
Google Compute Engine is for maintaining our organizational department wise projects such as online training applications, online student registrations, blog posts, tutorials, etc.
We need to separate our organization projects in the various department because these applications are developed for solving several problems for filtered users. Google Compute Engine is used for hosting our online students' maintenance and other related tasks.
We need to separate our organization projects in the various department because these applications are developed for solving several problems for filtered users. Google Compute Engine is used for hosting our online students' maintenance and other related tasks.
- Google Compute Engine gives us easy ability to maintain the servers including live statistics about what is going on.
- Easy single click to extend server system including network changing. Easy to clone servers between multiple regions.
- Google Compute Engine has one-click installer (pre-built) applications including Bitnami launchpad.
- Easy to integrate with cloud storage and backup periodically source codes and database to storage facility
- Sometimes it is hard to remember the settings menus because these are separated into various sections.
- Inviting external users to projects or maintainers are also a little complex
- Server images have limited facilities. I mean some of the sections are disabled and had to be re-enabled on my own. Especially for Debian or Ubuntu images.
- SMTP service is disabled by system and needs to be configured Postfix on my own.
- UI is little complicated.
March 29, 2017
Wonderful IaaS for small businesses with room to grow
We're a small custom software company with one main web-based program which we host on Google Compute Engine. Over the years we've gained more and more users and we were having issues scaling up as we grew, sometimes slowly and sometimes rapidly. Finally our old hosting solution had a bad down period and we were forced to look elsewhere to get our software back online. Since switching to Compute Engine, we've been able to save money while scaling up as needed. It has been very reliable and overall a perfect fit for us.
- Compute instances can be resized with quite minimal down time.
- They offer recommendations when an instance might need to be upgraded to improve performance or downgraded to save you money.
- The ability to SSH into any of your instances from any browser or mobile device works extremely well and is very useful!
- The cost of bandwidth is somewhat high.
March 24, 2017
GCE - the underrated underdog of the market
It is being used across the whole organization. It addresses the problem of providing solutions to customers who need an all-inclusive infrastructure solution for web services and apps. It has a lot of systems that are managed by Google which people commonly build themselves without knowing that they are reinventing the wheel.
- Clean and well-designed API
- Simple, yet transparent reporting of usage
- Generous and straightforward pricing
- Missing GPUs for cloud instances
- Excessively lean customer service department
- Confusion as to how the container environment works in relation to GCE
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.
Google Compute Engine (GCE) is Google's answer to AWS. We use GCE as a low-cost virtual host solution, and we purposefully migrated off AWS and Rackspace to GCE. We made the decision mostly based on cost, but also the flexibility of the toolkit and deployment. GCE is a one-stop shop for hosting virtual and scalable environments in the cloud.
- GCE is an excellent tool for quick deployment of on demand servers.
- GCE offers the ability to snapshot servers, create host clusters, and auto-scale based on demand.
- GCE is the most cost effective virtual hosting environment we've used. They give up front pricing which is a major plus for us.
- I can't think of any immediate areas GCE could improve on.
September 21, 2016
Benefits of Google Cloud for bespoke green-field applications
We use Google Compute Engine to support public facing clinical research patient recruitment services, the service is scalable to accommodate increase in capacity due to news items that sign post patients to the services. The platform is IaaS and data is shared with major health charities.
- Google Compute Engine provides rapid scalability without the need to worry about the infrastructure itself, this means we can focus on core development of the service.
- The platform makes it easy to link in to other Google apps and APIs.
- Google does not lend itself to legacy technologies where you may require a cloud migration strategy.
- While Google tends to solve their own problems and share solutions it can feel in bit one-way.
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
Google Compute Engine Scorecard Summary
Feature Scorecard Summary
About 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.
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
Persistent Disks
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.
Local SSD
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.
Batch Processing
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.
Containers
Run, manage, and orchestrate Docker containers directly on Compute Engine VMs or with Google Kubernetes Engine.
Categories: Platform-as-a-Service (PaaS), Infrastructure-as-a-Service
Google Compute Engine Competitors
Amazon Web Services, Microsoft Azure, Amazon S3 (Simple Storage Service)
Google Compute Engine Technical Details
| Deployment Types: | SaaS |
|---|---|
| Operating Systems: | Unspecified |
| Mobile Application: | No |