We use the solution to host a self-hosted helpdesk.
Solutions Architect at CGI
An easy-to-use solution with good Spot model provisioning
Pros and Cons
- "The solution helps to direct SSH into the machine at the click of a button. It also helps to deploy container images right from the UI. There is no need to manage the containers on the machine. I also like the tool’s Spot provision model."
- "I would like to improve the solution’s UI while deploying a container. It is sometimes hard to figure out the container’s details and format that you want to deploy. The tool does not give you a guide to find out the error and why the container is not starting up which could be because you have configured it wrong. This is always a hit on the setup."
What is our primary use case?
What is most valuable?
The solution helps to direct SSH into the machine at the click of a button. It also helps to deploy container images right from the UI. There is no need to manage the containers on the machine. I also like the tool’s Spot provision model.
What needs improvement?
I would like to improve the solution’s UI while deploying a container. It is sometimes hard to figure out the container’s details and format that you want to deploy. The tool does not give you a guide to finding out the error and why the container is not starting up which could be because you have configured it wrong. This is always a hit on the setup.
For how long have I used the solution?
I have been using the solution for five years.
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October 2024
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What do I think about the stability of the solution?
The tool is stable.
What do I think about the scalability of the solution?
Our company has more than 1000 users for the tool.
How was the initial setup?
The initial setup is very easy. The deployment took two minutes to complete.
What other advice do I have?
I would suggest new users take a look at Spot instance since it can help you significantly reduce costs. I would like to see dedicated and better UX for container deployment in the tool’s future releases.
Google Compute Engine is easy to use and has great authentication management for Google APIs. The solution can directly escalate and it's easy to get started with.
Disclosure: My company has a business relationship with this vendor other than being a customer:
Engineer at SLT Visioncom Pvt Ltd
Beneficial temporary virtual machines, high availability, and simplified deployment
Pros and Cons
- "The support for ephemeral instances has been particularly valuable for me. It allows me to significantly reduce costs for temporary virtual machines by automatically destroying them once they are no longer needed, which can result in cost savings of up to 90 percent. Additionally, the solution is easy to use."
- "Google Compute Engine does not have many options at a lower tier level. If they had more options it will be better. For example, Amazon AWS or Microsoft Azure, have more options and different types of instances, of VMs we can select."
What is our primary use case?
We are using Google Compute Engine for deploying virtual machines for customers, as well as one or two internal uses. We use it mainly, as a managed service we offer customers.
What is most valuable?
The support for ephemeral instances has been particularly valuable for me. It allows me to significantly reduce costs for temporary virtual machines by automatically destroying them once they are no longer needed, which can result in cost savings of up to 90 percent. Additionally, the solution is easy to use.
What needs improvement?
Google Compute Engine does not have many options at a lower tier level. If they had more options it will be better. For example, Amazon AWS or Microsoft Azure, have more options and different types of instances, of VMs we can select.
For how long have I used the solution?
I have been using Google Compute Engine for approximately one year.
What do I think about the stability of the solution?
It is a highly stable solution.
I rate the stability of Google Compute Engine a ten out of ten.
What do I think about the scalability of the solution?
Google Compute Engine has a variety of instances, but for developing countries, such as Sri Lanka, we choose the lowest price ranges. We don't have many options for this solution.
My basic recommendation for people new to Google Compute Engine is to consider using it as it is a leader in the public cloud market. However, it's important to compare costs and options with other providers, such as AWS and Alibaba. While all of them offer competitive prices, Google Compute Engine is a simpler option for beginners.
I rate the scalability of Google Compute Engine an eight out of ten.
How are customer service and support?
The support from Google Compute Engine is good.
I rate the support from Google Compute Engine an eight out of ten.
How would you rate customer service and support?
Positive
How was the initial setup?
The initial setup of Google Compute Engine is easy. All the setups are straightforward. All the public cloud tools are now offering a simplified solution. The whole process of deployment can take a few minutes. In most cases, it will take under one hour if there are more virtual machines being installed.
The steps taken for the deployment are simple. We only need an account. Once we have an account, we will have access to the cloud console. There are two options for deployment, using the GUI or the console. Both are easy to use, we only need to open a few ports to keep the machine running and active.
I rate the initial setup of Google Compute Engine a nine out of ten.
What about the implementation team?
We use one person for the deployment of the solution.
What was our ROI?
The return on investment is good for Google Compute Engine because using this option, we can save more than 90% of the initial investment compared to alternatives. It's ideal for development and testing. In production, it can result in a saving of 60 to 70 percent when compared to other services.
What's my experience with pricing, setup cost, and licensing?
Google Compute Engine is not the least expensive solution. Microsoft Azure, and Microsoft One, are offering a less expensive solution. The price is based on usage. Whenever we use it, we have to pay for only usage. It is a pay-as-you-go model.
I rate the price of Google Compute Engine an eight out of ten.
What other advice do I have?
I rate Google Compute Engine a nine out of ten.
Disclosure: My company has a business relationship with this vendor other than being a customer: Partner
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Google Compute Engine
October 2024
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Associate Consultant at a tech vendor with 10,001+ employees
Helps to choose security by creating customized firewalls
Pros and Cons
- "The main motive for choosing Google Compute Engine is pricing."
- "I rate the product's stability around five to six out of ten."
What is our primary use case?
We use Google Compute Engine as a VM.
How has it helped my organization?
The main motive for choosing Google Compute Engine is pricing.
What is most valuable?
The solution is highly available, and you can choose your security, such as creating firewall rules.
For how long have I used the solution?
I have been working with the product for eight years.
What do I think about the stability of the solution?
I rate the product's stability around five to six out of ten.
What do I think about the scalability of the solution?
The node can be scaled 70 to 80 percent.
How was the initial setup?
Two people are enough to handle the tool's deployment. The deployment takes one hour to complete.
What other advice do I have?
I rate the product a ten out of ten.
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Google Certified Professional Data Engineer at a tech vendor with 201-500 employees
You can use Google Cloud Datalab to explore, analyze, transform and visualize data and build machine learning models using existing data in Google Cloud Storage.
What is most valuable?
One of the most valuable features that Cloud Datalab has is that it integrates seamlessly with other Google Cloud Platform products. You can use Google Cloud Datalab to explore, analyze, transform and visualize data and build machine learning models using existing data in Google Cloud Storage or BigQuery. Cloud Datalab is interactive, so you can run portions of your code and see the results immediately as you work through your Datalab notebook.
How has it helped my organization?
Google Cloud Datalab has made it really easy for me to perform data exploration and analysis. Previously, I would have to wait for my data to transfer to a local server with a SQL database before beginning exploration. With larger data sets, the entire data transfer and analysis process could take hours if not days. With Google Cloud Datalab and Google Cloud Platform, I can receive processed results in seconds, not hours or days, without significant delays transferring data, since my data is already in Google Cloud Storage and easily accessible for consumption in Google Cloud Platform. In addition, I am starting to leverage the Google Cloud Machine Learning APIs built into Google Cloud Datalab to receive better insights on my data.
What needs improvement?
You can already run BigQuery SQL queries in Google Cloud Datalab but one thing I would like to see improved is the user experience when constructing these SQL queries, similar the tools that the Big Query web console offers. For example, I would like to see improved support for automatically formatting SQL queries. It would also be helpful to have a button that will check a query for SQL syntax errors before running the query which is also available in the BigQuery web console.
For how long have I used the solution?
I've used Google Cloud Datalab for about 18 months. In February 2016, I ran into an issue while configuring Datalab and opened a new issue on the Datalab Github page. I received a response on the same day from a Google employee on the core Datalab development team. After resolving my issue with the help of a Cloud Datalab development team member on Github, I became more interested in Cloud Datalab to the extent that I decided to download the source code and build Datalab locally. I learned a lot in the process.
What do I think about the stability of the solution?
There have been a few (rare) instances where I've encountered a stability issue during the beta pre-production stage of the product. I should mention that it was pretty easy to revert back to a previous stable build. The stability issues are even more rare with the production version and since there is a very large user base the development team is very quick to fix regressions and troubleshoot performance issues.
What do I think about the scalability of the solution?
No, and I don't expect any issues with scalability as the Datalab Kernel is running in a Google Compute Engine (GCE) virtual machine which can be scaled according to the developer's needs. In addition, Google Cloud Platform is designed around scalability at the Petabyte-scale.
How are customer service and technical support?
10/10. The Datalab development team is very responsive on both StackOverflow and Github. I encourage you to make use of the free support that is available from the online Datalab Community. You can even build/run Datalab from source code if you have the interest to tinker around and learn more about Datalab on your own. If you prefer Google specific support, there are three support tiers available. You can also submit feedback directly from the Datalab user interface.
Which solution did I use previously and why did I switch?
Previously I used Jupyter (formerly IPython) as a tool for interactive data analysis. My primary reason for switching is that Datalab has built-in integration and high level magic commands for certain Google Cloud Platform products, such as Google Cloud Storage and Google BigQuery. In addition, Datalab has built in charting capabilities.
How was the initial setup?
Yes, the initial setup is very straightforward because the Datalab kernel is installed on a virtual machine in the cloud rather than on your local machine. In addition, the quick start documentation was very easy to follow. Google Cloud Datalab is installed using Google Cloud Shell which is accessible from a web browser which means that you can have access to the full Google Cloud Datalab user interface from a light-weight laptop such as a Chromebook.
What's my experience with pricing, setup cost, and licensing?
Google Cloud Datalab is an open source product (Apache 2.0 License). There are costs associated with having the Datalab Kernel running in a Compute Engine Virtual Machine, however you will only pay for the cloud resources you use. To save on costs, you can stop the GCE Virtual machine and start it when it is needed again. There may be other costs for additional resources that you decide to use, such as Google BigQuery or Google Cloud Storage.
Which other solutions did I evaluate?
Yes, previously I used Jupyter Notebook. Google Cloud Datalab is built on Jupyter (formerly IPython) so it was easy to transition to Google Cloud Datalab.
What other advice do I have?
Don't hesitate to try Google Cloud Datalab if you are in need of an interactive data visualization tool. Follow the quick start documentation and don't be afraid to get your feet wet. If you prefer a structured learning environment, there are also Google Approved paid courses available.
I could not have found a better product to perform interactive data analysis and begin my career as a Data Engineer. The are so many sample Datalab notebooks which makes it really easy for someone new to run and modify a Datalab notebook regardless of their level of knowledge of big data or python. After launching Datalab, simply click on the help icon in the navigation bar and then click the "Samples and Tutorials" link. Google Cloud Datalab is an open source project so reporting bugs and submitting feature requests is easy. If you're feeling brave, you can even submit a pull request in the GitHub project to fix a bug or modify Datalab functionality. The project maintainers are really welcoming and encourage participation from new contributors. In addition, the Cloud Datalab community is very responsive on StackOverflow.
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Customizable, particularly when using the Command Line Interface (CLI) but limitations in terms of layer two connectivity between VMs on the same subnet
Pros and Cons
- "It's the most engineer-friendly product compared to Amazon AWS or Azure."
- "It has some limitations. For example, you don't get through layer two connectivity. So I've had some difficulty deploying custom VMs. For example, you can't deploy a KVM file to file directly on GCP."
What is our primary use case?
We use it primarily for our testing. For example, if you want to deploy a laptop or something to test before deploying something on our appliance site. And we use GCP.
I'm just using it for testing and lab deployment setups.
What is most valuable?
Documentation is the best feature of Google Compute Engine. For example, the other day, I wanted to get something running with Nested Virtualization. So, I was able to do that just by going through Google's documentation. That's pretty good.
What needs improvement?
The solution could be more similar to something like ESXi. For example, in GCP, you don't get layer two connectivity between two VMs on the same subnet. So that could be great. Between two VMs on the same subnet in the same VPC.
Another area of improvement is the support. They did respond very fast, but they did not find a solution to our problem.
For how long have I used the solution?
I have been using this solution for more than four months.
What do I think about the stability of the solution?
It is a stable product. I haven't had any issues.
What do I think about the scalability of the solution?
It is scalable. There are around ten end users using this solution.
How are customer service and support?
The response time is good, but ultimately, if they weren't able to help, it's not the best, but it's okay because at least they respond quickly.
How would you rate customer service and support?
Neutral
Which solution did I use previously and why did I switch?
It's the most engineer-friendly product compared to Amazon AWS or Azure.
How was the initial setup?
The initial setup is pretty straightforward.
What's my experience with pricing, setup cost, and licensing?
The pricing is comparable to the competitors. I haven't noticed any difference.
What other advice do I have?
As long as you stick to the actual web console, the GUI, you can use it even if you have little understanding about what is sectionally going on.
Overall, I would rate the solution a seven out of ten. It's pretty customizable; for example, when you are using the CLI, you can get pretty much anything done.
But I didn't give it a ten because it has some limitations. For example, you don't get through layer two connectivity. So, I've had some difficulty deploying custom VMs. For example, you can't deploy a KVM file to file directly on GCP.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Google
Disclosure: My company has a business relationship with this vendor other than being a customer:
IT Support at a tech services company with 51-200 employees
Offers good scalability but it is has a very arcane and complex security environment and projecting costs can be difficult
Pros and Cons
- "The initial setup is reasonably straightforward. It's a handful of networks and a handful of computers."
- "The biggest problem is that it's got a very archaean and complex security environment that has to be very carefully set up and is easy to break."
What is our primary use case?
This is a web application and deployment is moving to GCP for disaster recovery purposes .
How has it helped my organization?
It has dramatically increased our costs over running dedicated hardware.
What is most valuable?
All of the cloud solution providers are basically the same. There's a little bit around the edges that is different. Each provider has its own kind of unique products but for the most part, 90% of the coverage between all of them is the same.
What needs improvement?
The biggest problem is that it's got a very arcane and complex security environment that has to be very carefully set up and maintained. Because GCP has is such a huge attack surface and is so prominent it any security lapses can quickly become fatal.
The problem with good security is that it more difficult to use the GCP features. Faced with a difficult to use interface people will find ingenious ways to circumvent the security.
Because GCE is tied into the overall Google services security model I do not believe that it can be improved without making the user experience more difficult.
For how long have I used the solution?
I have been this solution over the last three or four months.
What do I think about the stability of the solution?
GCP/AWS... have had more downtime in the last 5 years than the current implementation has had.
What do I think about the scalability of the solution?
It's scalable.
Which solution did I use previously and why did I switch?
I have used 4 other cloud providers over the years and have been using one provider for some applications for over 10 years.
The switch from internally managed services to a cloud environment was a management decision.
How was the initial setup?
The initial setup is reasonably straightforward.
The existing environment is fairly flat and static.
What about the implementation team?
An external firm has been contracted to provide the design and implementation of a DR solution which includes moving existing components to GCP.
They have little understanding of the existing environment and that lack of understanding has caused several roll backs on requirements to keep the operational cost manageable.
What was our ROI?
At this point there is no ROI unless the business model fundamentally changes.
For the foreseeable future this will be a significant budget deficit.
What's my experience with pricing, setup cost, and licensing?
It's $60,000 to $70,000 a month to replace about $10,000 a month in data center costs.
Which other solutions did I evaluate?
The choice was not mine so
What other advice do I have?
The advice that I would give to someone considering this solution is that you have to take a close look at what your costs are, where you want scalability and consider the reliability issues because it's not always obvious where . There are a number of places where commercial cloud applications work very well. There are places where it doesn't. For applications where you have large dynamic changes in load and storage, the cloud environment can be great because you pay for what you use and can take advantage of running up resources on demand. For static environments where you've got a reasonable amount of infrastructure, a cloud solution can be highly expensive and no more reliable.
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Software Engineer at a tech services company with 201-500 employees
Completely customized virtual machines with low prices
What is our primary use case?
I used GCE as simple virtual machines to run applications such as sonar and logstash as I also used to create robust clusters to scale applications with kubernetes.
How has it helped my organization?
The GCE, with its versatility, allows us to create virtual machines for any situation. We can either put an application in production, or run software like Sonar to guarantee the quality of the code.
What is most valuable?
Compared to other IaaS providers, I believe that Google Compute Engine (GCE) stands out with the ability to customize the virtual machines. With other providers, these are pre-determined specifications. With this you can create machines specific to your application.
What needs improvement?
The GCE only has virtual machines with processors and video cards of the new generation in the North American region, the GCE has expanded in new areas, like Latin America, but it does not carry powerful hardware.
What other advice do I have?
If the focus is cost reduction, they can migrate to the GCE without the fear that it will not bring results. The migration is simple and fluid, and there is nothing complex about it.
Disclosure: I am a real user, and this review is based on my own experience and opinions.
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