We performed a comparison between Cloudify 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."Product has given us the ability to catch early scaling issues that many companies hit on with private clouds."
"Cloudify provides the infrastructure-as-code, as well as operational action capabilities (orchestrated startups or upgrades, and more)."
"TOSCA model allows modeling the application rather than the automation. It is a machine-readable representation of the application and its infrastructure, which can be used for other things too, not just for the orchestration (e.g. enterprise architecture big picture, who connects to whom)."
"You can use only what you need. You can remove certain Cloudify functions from the framework to create a "minified" version of what you need. This might only consist of the messaging delivery system, and the orchestration functions."
"Valuable features are auto-scaling and load balancing."
"The solution includes the option to run background scripts and processes from a connected API."
"Extensible internal functions and plugins. Can implement custom plugins to fit your scenario. Python based plugins."
"Has great extendability which means you can build your own custom logic."
"The ability to monitor and automate both the right-sizing of VMs as well as to automate the vMotion of VMs across ESXi hosts."
"Turbonomic has helped optimize cloud operations and reduced our cloud costs significantly. Overall, we are at about 40 percent savings, and we spend about three million a year just in Azure. It reduces the size of the VMs, putting them into the right template for usage. People don't realize that you don't have to future-proof a virtual machine in Azure. You just need to build it for today. As the business or service grows, you can scale up or out. About 90 percent of all the costs that we've reduced has been from sizing machines appropriately."
"The biggest value I'm getting out of VMTurbo right now is the complete hands-off management of equalizing the usage in my data center."
"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."
"We like that Turbonomic shows application metrics and estimates the impact of taking a suggested action. It provides us a map of resource utilization as part of its recommendation. We evaluate and compare that to what we think would be appropriate from a human perspective to that what Turbonomic is doing, then take the best action going forward."
"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."
"The automation and orchestration components are definitely the best part, as you can tell it what it can do and when, and just let it be."
"The automated memory balancing, where it looks at whether it's being used in the most efficient way and adds or takes away memory, is the best part. If it didn't do that, it would be something that I would have to do. We have too many machines for one person to do that. The automation helps me in that it is done in a really efficient way and a balanced way because of the policies. It really helps."
"Certainly the UI could use some intensive work, but nevertheless, overall, it’s a complete product with its 3.4 version and much better features are available with 4.0."
"Error handling could be improved; GUI is lacking with respect to user privileges and connectivity."
"The solution is a bit of a headache because mistakes happen in the blueprint every time we deploy and they require modifications."
"Unlike the Docker environment, Cloudify takes time for configuration and its learning curve."
"The upgrading process could be simplified."
"Install of the product itself could be improved and I would like to see better event monitoring."
"It lacked the user interface for multitenancy and basic platform management tasks. It is a leader in the niche area that they like to perform in, but it only does about 30% of top-tier advanced functions of platform management. It doesn't meet about 70% of what you need to manage a private cloud platform."
"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."
"Remove the need for special in-house knowledge and development."
"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."
"It can be more agnostic in terms of the solutions that it provides. It can include some other cost-saving methods for the public cloud and SaaS applications as well."
"They have a long road map when we ask for certain things that will make the product better. It takes time, but that's understandable because there are other things that are higher on the priority list."
"There is room for improvement [with] upgrades. We have deployed the newer version, version 8 of Turbonomic. The problem is that there is no way to upgrade between major Turbonomic versions. You can upgrade minor versions without a problem, but when you go from version 6 to version 7, or version 7 to version 8, you basically have to deploy it new and let it start gathering data again. That is a problem because all of the data, all of the savings calculations that had been done on the old version, are gone. There's no way to keep track of your lifetime savings across versions."
"Enhanced executive reporting standard with the tool beyond the reports that can be created today. Something that can easily be used with upper management on a monthly or quarterly basis to show the impact to our environment."
"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."
Cloudify is ranked 20th in Cloud Management with 12 reviews while IBM Turbonomic is ranked 4th in Cloud Management with 204 reviews. Cloudify is rated 8.0, while IBM Turbonomic is rated 8.8. The top reviewer of Cloudify writes "Works very well for advanced service chaining requirements and has extremely advanced engineers for 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 ". Cloudify is most compared with Morpheus, VMware Aria Automation, CloudStack, OpenNebula and Scalr, whereas IBM Turbonomic is most compared with VMware Aria Operations, Azure Cost Management, Cisco Intersight, VMware Aria Cost powered by CloudHealth and VMware vSphere. See our Cloudify vs. IBM Turbonomic report.
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