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Cloudify vs OpenNebula comparison

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Comparison Buyer's Guide

Executive SummaryUpdated on Dec 17, 2024

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

IBM Turbonomic
Sponsored
Ranking in Cloud Management
4th
Average Rating
8.8
Reviews Sentiment
7.4
Number of Reviews
205
Ranking in other categories
Cloud Migration (5th), Virtualization Management Tools (4th), IT Financial Management (1st), IT Operations Analytics (4th), Cloud Analytics (1st), Cloud Cost Management (1st), AIOps (5th)
Cloudify
Ranking in Cloud Management
31st
Average Rating
8.0
Reviews Sentiment
7.2
Number of Reviews
12
Ranking in other categories
No ranking in other categories
OpenNebula
Ranking in Cloud Management
7th
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
15
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of May 2025, in the Cloud Management category, the mindshare of IBM Turbonomic is 5.6%, down from 6.2% compared to the previous year. The mindshare of Cloudify is 1.8%, up from 1.8% compared to the previous year. The mindshare of OpenNebula is 7.4%, up from 6.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Management
 

Featured Reviews

Keldric Emery - PeerSpot reviewer
Saves time and costs while reducing performance degradation
It's been a very good solution. The reporting has been very, very valuable as, with a very large environment, it's very hard to get your hands on the environment. Turbonomic does that work for you and really shows you where some of the cost savings can be done. It also helps you with the reporting side. Me being able to see that this machine hasn't been used for a very long time, or seeing that a machine is overused and that it might need more RAM or CPU, et cetera, helps me understand my infrastructure. The cost savings are drastic in the cloud feature in Azure and in AWS. In some of those other areas, I'm able to see what we're using, what we're not using, and how we can change to better fit what we have. It gives us the ability for applications and teams to see the hardware and how it's being used versus how they've been told it's being used. The reporting really helps with that. It shows which application is really using how many resources or the least amount of resources. Some of the gaps between an infrastructure person like myself and an application are filled. It allows us to come to terms by seeing the raw data. This aspect is very important. In the past, it was me saying "I don't think that this application is using that many resources" or "I think this needs more resources." I now have concrete evidence as well as reporting and some different analytics that I can show. It gives me the evidence that I would need to show my application owners proof of what I'm talking about. In terms of the downtime, meantime, and resolution that Turbonomic has been able to show in reports, it has given me an idea of things before things happen. That is important as I would really like to see a machine that needs resources, and get resources to it before we have a problem where we have contention and aspects of that nature. It's been helpful in that regard. Turbonomic has helped us understand where performance risks exist. Turbonomic looks at my environment and at the servers and even at the different hosts and how they're handling traffic and the number of machines that are on them. I can analyze it and it can show me which server or which host needs resources, CPU, or RAM. Even in Azure, in the cloud, I'm able to see which resources are not being used to full capacity and understand where I could scale down some in order to save cost. It is very, very helpful in assessing performance risk by navigating underlying causes and actions. The reason why it's helpful is because if there's a machine that's overrunning the CPU, I can run reports every week to get an idea of machines that would need CPU, RAM, or additional resources. Those resources could be added by Turbonomic - not so much by me - on a scheduled basis. I personally don't have to do it. It actually gives me a little bit of my life back. It helps me to get resources added without me physically having to touch each and every resource myself. Turbonomic has helped to reduce performance degradation in the same way as it's able to see the resources and see what it needs and add them before a problem occurs. It follows the trends. It sees the trends of what's happening and it's able to add or take away those resources. For example, we discuss when we need to do certain disaster recovery tests. Over the years, Turbo will be able to see, for example, around this time of year that certain people ramp up certain resources in an environment, and then it will add the resources as required. Another time of year, it will realize these resources are not being used as much, and it takes those resources away. In this way, it saves money and time while letting us know where we are. We've saved a great deal of time using this product when I consider how I'd have to multiply myself and people like me who would have to add resources to devices or take resources away. We've saved hundreds of hours. Most of the time those hours would have to be after hours as well, which are more valuable to me as that's my personal time. Those saved hours are across months, not years. I would consider the number of resources that Turbonomic is adding and taking away and the placement (if I had to do it all myself) would end up being hundreds of hours monthly that would be added without the help of Turbonomic. It helps us to meet SLAs mainly due to the fact that we're able to keep the servers going and to keep the servers in an environment, to keep them to where (if we need to add resources) we can add them at any given time. It will keep our SLAs where they need to be. If we were to have downtime due to the fact that we had to add resources or take resources away and it was an emergency, then that would prevent us from meeting our SLAs. We also use it to monitor Azure and to monitor our machines in terms of the resources that are out there and the cost involved. In a lot of cases, it does a better job of giving us cost information than Azure itself does. We're able to see the cost per machine. We're able to see the unattached volume and storage that we are paying for. It gives us a great level of insight. Turbonomic gives us the time to be able to focus on innovation and ongoing modernization. Some of the tasks that it does are tasks that I would not necessarily have to do. It's very helpful in that I know that the resources are there where they need to be and it gives me an idea of what changes need to be made or what suggestions it's making. Even if I don't take them, I'm able to get a good idea of some best practices through Turbonomic. One of the ways that Turbonomic does to help bring new resources to market is that we are now able to see the resources (or at least monitor the resources) before they get out to the general public within our environment. We saw immediate value from the product in the test environment. We set it up in a small test environment and we started with just placement and we could tell that the placement was being handled more efficiently than what VMware was doing. There was value for us in placement alone. Then, after we left the placement, we began to look at the resources and there were resources. We immediately began to see a change in the environment. It has made the application and performance better, mainly due to the fact that we are able to give resources and take resources away based on what the need is. Our expenses, definitely, have been in a better place based on the savings that we've been able to make in the cloud and on-prem. Turbonomic has been very helpful in that regard. We've been able to see the savings easily based on the reports in Turbonomic. That, and just seeing the machines that are not being used to capacity allows us to set everything up so it runs a bit more efficiently.
Mark Wittling - PeerSpot reviewer
Works very well for advanced service chaining requirements and has extremely advanced engineers for support
We had a manager who thought that Cloudify could be used as a replacement for Horizon in OpenStack, but we found that Cloudify lacked the user interface or GUI for doing multitenancy and basic platform management tasks. Cloudify was really good at launching, for example, firewalls and configuring them and doing service chaining and rather advanced things like that, but it didn't meet the requirements for a basic platform management solution. It is something that seems to work better as a bolt-on or an augmented solution. It is a bit mis-marketed as a Cloud Management solution. It is not that. It is more of a service orchestration and automation tool. It is very good at doing that, but it fails to meet basic platform management requirements. Once you have it running, you can't really do anything with it without writing code and scripts. It requires a full-time DevOps person to use it. We deployed a Palo Alto firewall with it. That's basically what the project was for us, and it worked flawlessly once we got it finished, but it took another 12 weeks to get all of the automation and everything else coded, tested, and working. There is certainly a place for this technology, but when we got rid of OpenStack and moved to VMware, we either had to go with the vRealize Automation Suite to do this kind of automation, or we had to find an alternative solution to manage the private cloud. So, we put Cloudify in, but we really couldn't find it useful for basic platform administration tasks.
FOURES Jean-Philippe - PeerSpot reviewer
Reliable, simple to manage, and offers great technical support
The support of VXLAN fits with our network management. Thanks to this we can propose mixed solutions using virtual resources on OpenNebula and bare metal servers hosted in our facilities linked to each other on the sale network. This use case is very useful when some applications need bare metal power (Kubernetes workers, huge databases, AI models computations, et cetera). The cluster management is very useful for splitting our different clusters (mutual vs dedicated). We can manage deployments and capacity planning without pain. The API is also really simple and it helped us to develop the Terraform provider to manage OpenNebula like any other cloud infrastructure.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"We have seen a 30% performance improvement overall."
"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."
"I only deal with the infrastructure side, so I really couldn't speak to more than load balancing as the most valuable feature for me. It provides specific actions that prevent resource starvation. It always keeps things in perfect balance."
"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."
"I like Turbonomic's built-in reporting. It provides a ton of information out of the box, so I don't have to build panels for the monthly summaries and other reports I need to present to management. We get better performance and bottleneck reporting from this than we do from our older EMC software."
"Using this product helps us to reduce performance risk because it shows us where resources are needed but not yet allocated."
"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."
"The tool provides the ability to look at the consumption utilization over a period of time and determine if we need to change that resource allocation based on the actual workload consumption, as opposed to how IT has configured it. Therefore, we have come to realize that a lot of our workloads are overprovisioned, and we are spending more money in the public cloud than we need to."
"Extensible internal functions and plugins. Can implement custom plugins to fit your scenario. Python based plugins."
"It enables a single platform to communicate with the entire infrastructure."
"Cloudify works in cases where you have very advanced service chaining requirements. It really works well there, and it fits the best. They have a standardized markup that's based on TOSCA, which is a standard. I like the fact that they're standards-based. Their solution works extremely well if you have the talent and the manpower to write TOSCA descriptors to deploy and interchange services or to automate the configuration and turn up of services."
"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)."
"Product has given us the ability to catch early scaling issues that many companies hit on with private clouds."
"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."
"Has great extendability which means you can build your own custom logic."
"For the entire data center, as a private cloud, I believe that user management, expert management, and the virtual data center is completely magic for the users."
"The solution provides templates for configurations that can easily be exchanged to VMs."
"It is quite easy to deploy."
"OpenNebula is lightweight, stable, and easy to customize."
"It's easy to integrate OpenNebula with our IT systems."
"The service feature appeals most to us, thus it is the most valuable."
"The live migration feature has been great and is something we use very often."
"OpenNebula is easy to deploy and manage compared to other solutions like OpenStack."
 

Cons

"Some features are only available via changes to the deployment YAML, and it would be better to have them in the UI."
"Recovering resources when they're not needed is not as optimized as it could be."
"Before IBM bought it, the support was fantastic. After IBM bought it, the support became very disappointing."
"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."
"The issue for us with the automation is we are considering starting to do the hot adds, but there are some problems with Windows Server 2019 and hot adds. It is a little buggy. So, if we turn that on with a cluster that has a lot of Windows 2019 Servers, then we would see a blue screen along with a lot of applications as well. Depending on what you are adding, cores or memory, it doesn't necessarily even take advantage of that at that moment. A reboot may be required, and we can't do that until later. So, that decreases the benefit of the real-time. For us, there is a lot of risk with real-time."
"I like the detail I get in the old user interface and will miss some of that in the new interface when we perform our planned upgrade soon."
"I would like Turbonomic to add more services, especially in the cloud area. I have already told them this. They can add Azure NetApp Files. They can add Azure Blob storage. They have already added Azure App service, but they can do more."
"The old interface was not the clearest UI in some areas, and could be quite intimidating when first using the tool."
"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."
"The upgrading process could be simplified."
"Install of the product itself could be improved and I would like to see better event monitoring."
"Error handling could be improved; GUI is lacking with respect to user privileges and connectivity."
"Unlike the Docker environment, Cloudify takes time for configuration and its learning curve."
"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."
"The solution is a bit of a headache because mistakes happen in the blueprint every time we deploy and they require modifications."
"There are no payment gateways in OpenNebula."
"The protocol for clusterization is rough and doesn't work well."
"The web interface could be better. It's not very difficult to use, but there's room for enhancement."
"Backup features are only available in the enterprise edition. The community version lacks a good solution for making backups."
"The front-facing API can be improved to support lots of requests when the platform is huge with lots of virtual resources."
"The UI, monitoring, and alerting could benefit from further improvements."
"They should add more features like object storage."
"There are small things that are hard. For example, making sure that it is going to be installable on public clouds."
 

Pricing and Cost Advice

"I don't know the current prices, but I like how the licensing is based on the number of instances instead of sockets, clusters, or cores. We have some VMs that are so heavy I can only fit four on one server. It's not cost-effective if we have to pay more for those. When I move around a VM SQL box with 30 cores and a half-terabyte of RAM, I'm not paying for an entire socket and cores where people assume you have at least 10 or 20 VMs on that socket for that pricing."
"The product is fairly priced right now. Given its capabilities, it is excellently priced. We think that the product will become self-funding because we will be able to maximize our resources, which will help us from a capacity perspective. That should save us money in the long run."
"We felt the pricing was very fair for the product. It is in no way prohibitive for larger deployments, unlike other similar product on the market."
"Licensing is per socket, so load up on the cores rather than a lot of lower core CPUs."
"It is an endpoint type license, which is fine. It is not overly expensive."
"The pricing and licensing are fair. We purchase based on benchmark pricing, which we have been able to get. There are no surprise charges nor hidden fees."
"Contact the Turbonomic sales team, explain your needs and what you're looking to monitor. They will get a pre-sales SE on the phone and together work up a very accurate quote."
"It's worth the time and money investment if you can afford it."
"I wasn't involved in the pricing of it because we were just doing prototype work with it, but I was told by the upper management team that it was quite expensive. That was another reason we switched to Morpheus."
"OpenNebula gives good value for money."
"OpenNebuoa has recently come up with a new subscription model that is economical and a lot of new customers are choosing this as it is an easy subscription model."
"The licensing for OpenNebula used to be free, but now it's no longer free. A customer contacted me asking to move to another provider because of the changes in the licensing terms for OpenNebula. I have no information on how much the OpenNebula license is because the customer pays for it, and I only do the integration."
"The solution is open source so is free."
"VRA is very expensive but OpenNebula is free."
"We use the Community Edition, rather than the Enterprise Edition."
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Top Industries

By visitors reading reviews
Financial Services Firm
15%
Computer Software Company
14%
Manufacturing Company
9%
Insurance Company
7%
Computer Software Company
18%
Financial Services Firm
14%
Retailer
8%
Educational Organization
7%
Computer Software Company
22%
University
9%
Financial Services Firm
8%
Educational Organization
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What is your experience regarding pricing and costs for Turbonomic?
It offers different scenarios. It provides more capabilities than many other tools available. Typically, its price is...
What needs improvement with Turbonomic?
The implementation could be enhanced.
What is your primary use case for Turbonomic?
We use IBM Turbonomic to automate our cloud operations, including monitoring, consolidating dashboards, and reporting...
Ask a question
Earn 20 points
What do you like most about OpenNebula?
The live migration feature has been great and is something we use very often.
What needs improvement with OpenNebula?
The web interface could be better. It's not very difficult to use, but there's room for enhancement. Another area for...
 

Also Known As

Turbonomic, VMTurbo Operations Manager
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Interactive Demo

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Overview

 

Sample Customers

IBM, J.B. Hunt, BBC, The Capita Group, SulAmérica, Rabobank, PROS, ThinkON, O.C. Tanner Co.
Proximus Partner Communications (Israel) VMware NTT Data Metaswitch Spirent Communications Lumina Networks Atos Fortinet
Akamai, BBC, Fermilab, Terradue, Surf Sara, Produban, Netways, ESA, China Mobile, BlackBerry, Deloitte, Fuze, Telefonica, Trivago, Nokia, Encore Tech, Beeks.
Find out what your peers are saying about Cloudify vs. OpenNebula and other solutions. Updated: April 2025.
849,686 professionals have used our research since 2012.