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OpenNebula vs OpenText Cloud Service Automation 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)
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
OpenText Cloud Service Auto...
Ranking in Cloud Management
34th
Average Rating
9.0
Reviews Sentiment
7.1
Number of Reviews
6
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 OpenNebula is 7.4%, up from 6.5% compared to the previous year. The mindshare of OpenText Cloud Service Automation is 0.7%, up from 0.6% 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.
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.
SunpritSingh - PeerSpot reviewer
A user friendly solution that makes it easy to submit and view jobs
The most valuable feature of Micro Focus Cloud Service is how user-friendly the solution is. Traditionally, when we use a mainframe system to submit jobs, we have to see the spool or any error we might get in the spool. It is very command-based and uses a green screen, which is not user-friendly. Micro Focus enterprise makes it easy to submit and view jobs. We just have to log into the particular portal, go to the catalog and view any files we want. The same can be said about submitting jobs. We know what JCL we want to submit, give it the path, and then submit it with no command required. It is very user-friendly.

Quotes from Members

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

Pros

"My favorite part of the solution is the automation scheduling. Being able to choose when actions happen, and how they happen..."
"The primary features we have focused on are reporting and optimization."
"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."
"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."
"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."
"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 most important feature to us is an objective measurement of VM headroom per cluster. In addition, the ability to check for the right-sizing of VMs."
"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."
"It makes maintenance very easy and stress-free for our teams."
"With a single click, we could set things up and initiate them."
"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."
"OpenNebula is easy to deploy and manage compared to other solutions like OpenStack."
"What's best about OpenNebula that people like is that it's easy to deploy. It's also easy to manage. It's interesting because people choose OpenNebula over other solutions because of the ease of management."
"OpenNebula is lightweight, stable, and easy to customize."
"I also like the ability to build custom functions. I can define a function where I have two types of views and configure the dependencies. The virtual data centers concept allows me to define users. If a user wants to join certain kinds of machines, the host and the other user won't see them. It gives me the flexibility to define multiple views and data centers in one place."
"The most valuable feature of OpenNebula is that it scales very well."
"The tool's most valuable feature is life cycle management."
"The most valuable feature of Micro Focus Cloud Service is how user friendly the solution is."
 

Cons

"The old interface was not the clearest UI in some areas, and could be quite intimidating when first using the tool."
"The way it handles updates needs to be improved."
"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."
"They could add a few more reports. They could also be a bit more granular. While they have reports, sometimes it is hard to figure out what you are looking for just by looking at the date."
"Turbonomic doesn't do storage placement how I would prefer. We use multiple shared storage volumes on VMware, so I don't have one big disk. I have lots of disks that I can place VMs on, and that consumes IOPS from the disk subsystem. We were getting recommendations to provision a new volume."
"Turbonomic can modernize the look and feel, making it more user-friendly to access and obtain information."
"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."
"I do not like Turbonomic's new licensing model. The previous model was pretty straightforward, whereas the new model incorporates what most of the vendors are doing now with cores and utilization. Our pricing under the new model will go up quite a bit. Before, it was pretty straightforward, easy to understand, and reasonable."
"The storage feature that they have is a bit confusing."
"It should have a simple REST API like most other tools. It's the industry standard format. An XML-RPC API gives you an XML document that you have to convert and then do something with that. REST API endpoint provides outputs in a JSON document. I would also like to see support for user data or heat templates, which OpenStack offers, but OpenNebula doesn't have this yet."
"Most of the competitors are offering some sort of billing software to transform their installation to work as a small-sized public cloud, but those offerings from OpenNebula are still missing."
"There are no payment gateways in OpenNebula."
"An area for improvement in OpenNebula is the number of features it has. The solution doesn't have that many cloud features compared to other solutions. You'd say, "Okay, simplicity over a rich feature list?" Some say, "No, I need a big machine or a cloud interface for my customers to manage resources. I don't have to go and do it for them." Some people do it that way, and it works, but I'd like to improve the limited features in OpenNebula."
"There are small things that are hard. For example, making sure that it is going to be installable on public clouds."
"Backup features are only available in the enterprise edition. The community version lacks a good solution for making backups."
"As with all enterprise software licensing, the pricing is not intuitive and must be negotiated; grandfathered contracts are better than anything offered today."
"I would like fewer restrictions as a software tester."
"OpenText Cloud Service Automation needs to incorporate easier installation. It should improve skills and quality of support."
 

Pricing and Cost Advice

"I consider the pricing to be high."
"It was an annual buy-in. You basically purchase it based on your host type stuff. The buy-in was about 20K, and the annual maintenance is about $3,000 a year."
"What I can advise is to trial the product, taking advantage of the Turbonomic pre-sales implemention support and kickstart training."
"I have not seen Turbonomic's new pricing since IBM purchased it. When we were looking at it in my previous company before IBM's purchase, it was compatible with other tools."
"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."
"The pricing is in line with the other solutions that we have. It's not a bargain software, nor is it overly expensive."
"It is an endpoint type license, which is fine. It is not overly expensive."
"In the last year, Turbonomic has reduced our cloud costs by $94,000."
"We use the Community Edition, rather than the Enterprise Edition."
"VRA is very expensive but OpenNebula is free."
"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."
"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 solution is open source so is free."
"OpenText Cloud Service Automation's pricing is average."
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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
22%
University
9%
Financial Services Firm
8%
Educational Organization
7%
No data available
 

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...
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...
What do you like most about Micro Focus Cloud Service Automation?
The tool's most valuable feature is life cycle management.
What needs improvement with Micro Focus Cloud Service Automation?
OpenText Cloud Service Automation needs to incorporate easier installation. It should improve skills and quality of s...
What advice do you have for others considering Micro Focus Cloud Service Automation?
We have large customers for OpenText Cloud Service Automation. I rate it a nine out of ten.
 

Also Known As

Turbonomic, VMTurbo Operations Manager
No data available
Micro Focus Cloud Service Automation, Cloud Service Automation Manager, HPE Cloud Service Automation
 

Interactive Demo

Demo not available
Demo not available
 

Overview

 

Sample Customers

IBM, J.B. Hunt, BBC, The Capita Group, SulAmérica, Rabobank, PROS, ThinkON, O.C. Tanner Co.
Akamai, BBC, Fermilab, Terradue, Surf Sara, Produban, Netways, ESA, China Mobile, BlackBerry, Deloitte, Fuze, Telefonica, Trivago, Nokia, Encore Tech, Beeks.
China Merchants Bank, Osiatis
Find out what your peers are saying about OpenNebula vs. OpenText Cloud Service Automation and other solutions. Updated: April 2025.
850,028 professionals have used our research since 2012.