Google Compute Engine vs. IBM Power Virtual Server

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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It is really impactful in terms of scenarios like ERP systems and Data Analytics where heavy data needs to be analysed in terms of volume and their needs to be high scalability offering so in that scenario it is a great asset and features like distribution of workload using AI capabilities by leveraging modern IBM offerings like Watson is really helpful the area in which it could improve is native development of application in terms of adoption of New cloud Technologies

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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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• It is good in managing our documents in a precise manner.
• It is a comprehensive tool and supports other languages like JAVA and Python and it is useful for us.
• It is quite a valuable tool available at a reasonable price in the market and it is a scalable tool.

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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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• The software appears to be geared for a no-programming approach, which implies that making changes is more difficult.
• The user base is small making it monotonous and difficult to come up with new methods.
• The number of rankings is not as large as competitors.
• The admin end is poorly designed, as they are unable to receive and respond to client feedback.

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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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Easy to understand the architecture, easy of implementation and support with perfect documentation. Results driven performance in terms of latency and speed. Able to perform heavy workloads and huge transformations, also integrated SAP systems and Oracle robust deployments. But looking more in terms of AI capabilities to achieve more innovation.

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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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It provides strong support for Terraform, Ansible, and API-based management gives power users flexibility and efficiency and IBM Cloud UI is modern and relatively easy to navigate. Interfaces and workflows are consistent with on-prem Power Systems management tools. Areas to be improved - Compared to AWS or Azure, the UI could be more streamlined in how it presents all related services (e.g., networking, logging, storage) that tie into PowerVS

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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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Very easy to use.

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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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While there’s room for improvement, it generally works very well.

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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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As with most IBM products the ongoing support for IBM Power Virtual Server is solid and consistent. IBM provides a clear roadmap for receiving support of their products. Both voice and online response is offered. It is obvious that IBM has the internal systems and culture to maintain support functions. This starts from the initial support call to the problem analysis and continues through the problem resolution. Documentation and communication are consistent within this process.

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It is economic.

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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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They both have their own ups and downs and it totally depends on the team which suits them best. IBM Power Virtual Server has Performance, Scalability, Reliability and Availability, Compatibility, and Good Vendor Support. The specific use case and workload requirements played a significant role. Some workloads may benefit from IBM Power Systems' architecture, while others may perform equally well on alternative platforms.

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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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Built to handle thousands of concurrent users, high query loads, and massive datasets especially in data-heavy industries like finance, healthcare, and manufacturing. In-memory processing, dynamic query optimization, and intelligent caching mechanisms help it scale efficiently under load. You can configure clusters of Cognos servers to distribute workload and ensure high availability, even during peak usage

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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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• We have had a return on investment of 30%.
• There have also been 80% fewer application crashes due to a lack of resources that previously ran on the X86 platform.
• Administration management has been simplified and staff can dedicate themselves to the development of applications, instead of providing support to users when the applications do not respond efficiently, this made staff 45% more productive.

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