Google Compute Engine vs. IBM Cloud Virtual Servers for VPC

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.

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One scenario that immediately came to my mind was large-scale data processing, IBM Cloud Virtual Servers is well-suited for organizations that require high-performance computing capabilities, particularly when processing large amounts of data. It can also be useful for companies or organizations that wish to migrate their workplace to the cloud and it may suite companies that have strict compliance requirements since the servers have robust security features.

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• 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

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• Scalability: IBM Cloud Virtual Servers enable businesses to simply and quickly scale up or down the resources they require in response to changing business demands. This enables firms to respond to traffic spikes, requests for new services, or changes in business size without the need for additional hardware purchases or maintenance.
• Cost savings: By employing virtual servers in the cloud, enterprises can decrease capital expenditures for hardware and infrastructure while also lowering ongoing operational expenses by removing server maintenance and management costs. This can result in significant cost savings for enterprises, particularly those that need to raise or decrease their computer capacity fast and easily.
• High availability: IBM Cloud Virtual Servers is built with high availability in mind, giving enterprises the certainty that their applications and data will be available and accessible even if hardware fails or other disruptions occur. This assists enterprises in maintaining business continuity and lowering the chance of downtime, which is crucial for firms that rely on 24/7 access to their systems. Furthermore, IBM's comprehensive network and security features aid in the prevention of data breaches and other security risks, assuring the availability and reliability of their applications and data.

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• 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.

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• It would also be nice if there were more templates to choose from when creating a server. Right now there are only a few options, and we'd like to see more variety.
• We'd like to see the ability to create server groups. This would make it easier to manage a large number of servers since we could do all of the updates and management tasks for them at once.
• There doesn't seem to be a way to automatically install updates on all of the virtual servers. We have to go in and manually update each one, which can be time-consuming. It would be really nice if automatic updates can be done.

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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.

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It has a flexible and affordable pricing, easy to configure and manage. It is easy to spawn one or multiple instances and have them up and running in no time

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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.

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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

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Always available when you need an instance.

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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.

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Most of the instances work on hypervisors with good processors, but not all of them.

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• 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.

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It is adequate, but you need to be ready to argue your point - which is fair enough, I suppose, but being given the opposite of the benefit of the doubt every time does not necessarily result in an enjoyable user experience.

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We did not use IBM professional services to implement IBM Cloud Virtual Servers.

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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.

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IBM Cloud Virtual Servers offer more customization options than Amazon EC2, with the ability to select from a range of operating systems, storage types, and network configurations. IBM also provides a wide range of tools and services to help manage and optimize your virtual servers, including a web-based console, CLI, and API.

AWS EC2 is a more managed platform, with a focus on providing a simple and easy-to-use interface. Amazon provides a range of predefined instance types, each with different specs and pricing, to make it easy to find the right option for your needs. AWS also offers a number of management and monitoring tools, but these are often more basic than what is available from IBM.

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It works really well with other Google Cloud services, making it easy to build scalable solutions across different teams and locations.

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It worked well for us in the beginning, it works well for us when we have more instances.

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• 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.

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• Supports businesses who want compute power on demand (instances are ready within minutes).
• It can give you access to a 32-core CPU at $0.29 for short running or interruptible processes - enabling cost-efficient number crunching.
• Given me a taste of the powers of remote compute power for compilation and development.

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