We performed a comparison between IBM Spectrum Computing and IBM Turbonomic based on real PeerSpot user reviews.
Find out in this report how the two Cloud Management solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The most valuable aspect of the product is the policy driving resource management, to optimize the computing across data centers."
"Spectrum Computing's best features are its speed, robustness, and data processing and analysis."
"This solution is working for both VTL and tape."
"Easy to operate and use."
"We are satisfied with the technical support, we have no issues."
"The most valuable feature is the backup capability."
"We can manage multiple environments using a single pane of glass, which is something that I really like."
"Turbonomic helps us right-size virtual machines to utilize the available infrastructure components available and suggest where resources should exist. We also use the predictive tool to forecast what will happen when we add additional compute-demanding virtual machines or something to the environment. It shows us how that would impact existing resources. All of that frees up time that would otherwise be spent on manual calculation."
"I like the analytics that help us optimize compatibility. Whereas Azure Advisor tells us what we have to do, Turbonomic has automation which actually does those things. That means we don't have to be present to get them done and simplifies our IT engineers' jobs."
"It has automated a lot of things. We have saved 30 to 35 percent in human resource time and cost, which is pretty substantial. We don't have a big workforce here, so we have to use all the automation we can get."
"I like Turbonomic's automation and AI machine learning features. It shows you what it can do, but it can also act on recommendations automatically. Integration with an APM system makes the AI/ML features truly effective. Understanding what the application is doing and the trends of application behavior can help you make real-world decisions and act on that information."
"The proactive monitoring of all our open enrollment applications has improved our organization. We have used it to size applications that we are moving to the cloud. Therefore, when we move them out there, we have them appropriately sized. We use it for reporting to current application owners, showing them where they are wasting money. There are easy things to find for an application, e.g., they decommissioned the server, but they never took care of the storage. Without a tool like this, that storage would just sit there forever, with us getting billed for it."
"The primary features we have focused on are reporting and optimization."
"It also brings up a list of machines and if something is under-provisioned and needs more compute power it will tell you, 'This server needs more compute power, and we suggest you raise it up to this level.' It will even automatically do it for you. In Azure, you don't have to actually go into the cloud provider to resize. You can just say, 'Apply these resizes,' and Turbonomic uses some back-end APIs to make the changes for you."
"This solution is no longer managing tapes correctly."
"Lack of sufficient documentation, particularly in Spanish."
"We have not been able to use deduplication."
"Spectrum Computing is lagging behind other products, most likely because it hasn't been shifted to the cloud."
"We'd like to see some AI model training for machine learning."
"SMB storage and HPC is not compatible and it should be supported by IBM Spectrum Computing."
"There is an opportunity for improvement with some of Turbonomic's permissions internally for role-based access control. We would like the ability to come up with some customized permissions or scope permissions a bit differently than the product provides."
"We don't use Turbonomic for FinOps and part of the reason is its cost reporting. The reporting could be much more robust and, if that were the case, I could pitch it for FinOps."
"While the product is fairly intuitive and easy to use once you learn it, it can be quite daunting until you have undergone a bit of training."
"The way it handles updates needs to be improved."
"It would be nice for them to have a way to do something with physical machines, but I know that is not their strength Thankfully, the majority of our environment is virtual, but it would be nice to see this type of technology across some other platforms. It would be nice to have capacity planning across physical machines."
"The reporting needs to be improved. It's important for us to know and be able to look back on what happened and why certain decisions were made, and we want to use a custom report for this."
"Recovering resources when they're not needed is not as optimized as it could be."
"It sometimes does get false positives. Sometimes, it'll move something when it really wasn't a performance metric. I've seen it do that, but it's pretty much an automated tool for performance. We've only got about 500 virtual machines, so lots of times, I'm able to manage it physically, but it's definitely a nice tool for a larger enterprise that might be managing 2,000 or 3,000 virtual machines."
IBM Spectrum Computing is ranked 9th in Cloud Management with 6 reviews while IBM Turbonomic is ranked 4th in Cloud Management with 204 reviews. IBM Spectrum Computing is rated 7.8, while IBM Turbonomic is rated 8.8. The top reviewer of IBM Spectrum Computing writes "Provides stable backup for our databases and has good technical support ". On the other hand, the top reviewer of IBM Turbonomic writes "The solution reduced our operational expenditures and is able to identify points before we even noticed them ". IBM Spectrum Computing is most compared with Apache Spark and HPE Ezmeral Data Fabric, whereas IBM Turbonomic is most compared with VMware Aria Operations, Azure Cost Management, Cisco Intersight, VMWare Tanzu CloudHealth and VMware vSphere. See our IBM Spectrum Computing vs. IBM Turbonomic report.
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