IBM Turbonomic Reviews

We are in the healthcare industry and we use this solution for ensuring proper resource allocation for our virtual servers and our virtual desktops.

We use Turbonomic as a single platform to manage our full application stack, and having a single source of truth for application performance management is very important to us. The fewer places you have to go to make changes, the better. Having that available in a single pane of glass to make those changes makes it easier on our admins. Rather than having to go into multiple solutions to make changes, they do it all right there.

Turbonomic provides visibility and analytics in our environment from the application layer, all the way down the stack to underlying infrastructure resources. We don't use it as much on the application level as we do on the hardware and resources level.

This is a feature that's becoming more important to us. We're really starting to look at the analytics more nowadays and will in the future. It was not as important before but has become more so in the past year.

This visibility has definitely helped reduce our time to resolution. We have not quantified how much but it is due to having the visibility and the ability to monitor what's going on and make those changes in real-time. We just didn't have a baseline to compare and see how much it's improved.

With respect to any alerts that come up, it helps us to interpret those faster. This is something that is very important because it triages a lot of stuff that we don't have to then spend extra time doing, especially being a small team. It saves us at least a couple of hours per week.

Using this product helps us to reduce performance risk because it shows us where resources are needed but not yet allocated. Based on that, we're able to see whether those resources needed to be updated. In turn, that helps to limit application downtime or employees waiting for their jobs to get done.

It has definitely helped to reduce performance degradation. It helps us keep up with the changing environment and workloads that change over the course of days or weeks. Prior to this, it was all manual for us and we'd have to react. Now, we're able to be proactive.

This has also had a positive impactive on our applications' response time to SLAs. We're able to keep up and be proactive by fixing issues before the user even notices that there is a problem. This is important because it's great from a customer experience standpoint.

They never experience the problems they had in the past, where they would have to call us to say that their machine was running slowly, and then we'd have to figure out what was going on. Now, we know beforehand that they need additional resources, and many times, we're able to address that before they even realize it.

Generally speaking, using this solution has helped to eliminate resource constraints and it's helped us to understand what resources we need. In terms of that, we are able to modify our plans for the future concerning the acquisition of new hardware because we're able to satisfy the need with what we already have, rather than thinking we need to buy more. Turbonomic helps us to balance that out better, ensuring that we're not over-resourced in terms of hardware, and having resources sitting idle, which is very costly.

Turbonomic has helped our engineers focus on innovation because it has freed their time quite a bit. In the past, we had one person that would spend a lot of time trying to find where things were going wrong. This was precipitated by users saying that their machines were slow or not performing very well. Our staff would have to go in and figure out what was going on, then make the appropriate changes. Now, Turbonomic does that and our staff can focus on other tasks that need to be done.

The resource allocation features are the best for us. They have a lot of different features, but we had it at first in notification-only mode, or recommendation mode it may be called. In that mode, they would recommend what we should do, and then we would manually do it.

Once we realized that we could trust their recommendations, we set it into the automated mode, so it makes those changes on the fly for us. Especially during the pandemic, that really helped as we were scaling up our virtual desktops quite a bit. We almost tripled the number of desktops we had on there within the course of two and a half to three months.

In the automation engine, it is really quick to change things when it needs to scale up. However, scaling back is a little bit slower. Recovering resources when they're not needed is not as optimized as it could be.

I have been working with Turbonomic for approximately four years.

This is a very stable solution. Even when we have to perform upgrades, it's seamless. With other solutions, updates can sometimes be a problem, but with Turbonomic, it's been pretty easy.

Turbonomic is a scalable product.

We have about 280 servers and close to 550 virtual desktops being managed by Turbonomic. It is in a mode to increase resources as needed and then decrease them as the demand goes away.

At this point, we don't have any plans to increase usage. We have it covering all of the workloads that we need.

We only have two people that use it, and they are system analysts. They are in charge of deployment and maintenance.

The customer support has been very positive, although we've had very limited need for it. That said, whenever we've had to call in, they've been able to help us out very quickly.

One of the best parts about this solution is that there are so few issues that we simply don't need to use support very often.

Positive

We did not use a similar solution prior to this one. All of the work was done manually. We knew that our workload was increasing and the time spent on managing these types of workloads throughout our server stack was also increased. We implemented Turbonomic because we found it was a good way to free them up from a lot of that busy work.

Compared to what we were doing before, Turbonomic has given us full visibility. Prior to this, we had to look in multiple locations, and in some cases, we didn't have any visibility at all. 

The initial setup was very straightforward, and it was done within a couple of days.

Resources from Turbonomic assisted us with the deployment. They were very knowledgeable and were able to help our staff, who had never used the product before, understand it very quickly.

We have not measured ROI, although application performance has improved because we're not resource-constrained. We're not running into situations where our applications are failing due to a lack of resources, so it's helped us most with uptime and customer experience.

It has definitely helped in terms of CapEx because we've been able to avoid purchasing hardware that we originally thought we needed.

The pricing is in line with the other solutions that we have. It's not a bargain software, nor is it overly expensive.

I do not recall evaluating other solutions.

I believe that we use version 8.3, and we may be a couple of versions behind the latest.

Turbonomic has tools for optimizing and monitoring cloud-based environments, although, at this point, we use it mainly for our on-premises environment. We used it to help estimate what our cloud costs would be. Consequently, we realized that we were much better, at the time, not migrating to the cloud from a monetary standpoint.

Using the cost estimate to run our workloads in the cloud, we found 25% to 30% savings by staying on-premises versus going to the cloud. This is because our workloads are not optimized for the cloud. We'd have to retool a lot, which becomes very expensive.

The problem with moving is based on our application stack, rather than something that can be changed in Turbonomic. They saved us money in this regard because their estimates are very well thought out and very informative.

My advice for anybody who is looking into Turbonomic is that it's a great product. There are other options on the market but from what I've seen, this is one of the better ones. I'd suggest starting slowly when it comes to the recommendations. Make sure that you're verifying what their recommendations are and building that trust up before going into a more automated mode. Once it is automated, it can move pretty quickly and if you're not ready for it, it can cause some issues.

If somebody were looking into Turbonomic but already has a process automator and does monitoring, it would really come down to whether they are looking for better ease of use, or having an all-in-one platform if they currently use multiple tools. It's going to do a lot of the same tasks and they would have to do their own research to see what is better for them. I like that it gives that single pane of glass visibility, whereas they might have multiple vendors and multiple applications in their current use case.

In summary, it's a good product. There are things that they're working on and they keep adding new features, so we're happy to see that.

I would rate this solution a nine out of ten.

Currently, we're doing migrations for older versions of Windows, both in the Azure Cloud and on-prem in our VMware vCenters. We use this tool to do comparisons between the current and future workloads and what would they look like, based on the usage. So, it is kind of a rightsizing exercise or rightsizing, either downsizing or upsizing, depending on the requirements. We just put all that information into Turbonomic, and it builds us out a new VM, exactly the size that we need, based on the trending and analysis. Then, you can also put in some factors, saying, "Look, it was Windows 2008, and we're going to windows 2019, or whatever. We're going to grow the database by X amount." This tool helps you do some of the analysis in order for you to get the right size right out-of-the-box. We love that.

I oversee a lot of stuff, so I don't really get an opportunity to go in there to point and click. We have people who do that.

It is doing Azure Cloud and VMware. Turbonomic understands the resource relationships at each of these layers and the risks to performance for each. You can compartmentalize your most critical workloads to make sure that they are getting the required resources so the business can continue to run, especially when we get hit by a lot of work at once. 

The solution provides us with a single platform that manages the full application stack. In our decision to go with this solution, this was critical. We had so many vCenters and physical clusters out there. We had virtual and physical machines all over the place. Turbonomic was the way we were able to centralize all our vCenters and get a good picture of what is going on in the environment. It was all over the place without it, so there was no way that we could centralize and work on getting off of some of the older hardware platforms that we were on and start moving to converged, then eventually hyper-converged. This tool allowed us to take a good look at our environment and decide how we were going to size those workloads into those new areas, off of the old blade chassis and old standalone systems, to the more modern hyper-converged systems.

In our organization, it is optimizing application performance as a continuous process that is beyond human scale. The reason is because there are times of the year that we have these big hits. It is like if you were Verizon and you were to sell all your cell phones during the Christmas time. Well, we have a very similar thing here at our company, where we have a period of time we basically shut the business down. We have to give critical resources to critical applications, giving them the resources that they need in order to function. In order for us to do that, we are able to take critical workloads and put them off into their own area, then determine how much we have to take from the rest of the resources, which we take from the rest of the systems in order to put it into new clusters or systems. That is super critical for us every year.

We use it for management and rightsizing of our platforms, specifically for migration activities, because we're always doing it. The migration has been the biggest thing that I personally use.

There are a number of tools that we use in it. Some of the things that I request are the data dumps. They write some kind of scripts or something inside there where they are actually able to pull for me CSV files. Then, I can go in, take all that information, and build a master gold list for my migration activities. 

Everything that I ask for, I get. I don't know what they are clicking nor do I know what they're doing, but when I request it, I get it. There are all sorts of different ideas and scenarios that I put forth to the developers.

Turbonomic provides specific actions that prevent resource starvation. While I'm not in there banging around on the tool all the time, I can tell you that I do very much benefit from it. On Monday, I was getting additional information from the Turbonomic guys.

We use the solution’s automation mode to continuously assure application performance by having the software manage resources in real-time. 

There are a few things that we did notice. It does kind of seem to run away from itself a little bit. It does seem to have a mind of its own sometimes. It goes out there and just kind of goes crazy. There needs to be something that kind of throttles things back a little bit. I have personally seen where we've been working on things, then pulled servers out of the VMware cluster and found that Turbonomic was still trying to ship resources to and from that node. So, there has to be some kind of throttling or ability for it to not be so buggy in that area. Because we've pulled nodes out of a cluster into maintenance mode, then brought it back up, and it tried to put workloads on that outside of a cluster. There may be something that is available for this, but it seems very kludgy to me.

I would like an easier to use interface for somebody like me, who just goes in there and needs to run simple things. Maybe that exists, but I don't know about it. Also, maybe I should be a bit more trained on it instead of depending on someone else to do it on my behalf.

There are some things that probably could be made a little easier. I know that there is a lot of terminology in the application. Sometimes applications come up with their own weird terminology for things, and it seems to me that is what Turbonomic did. 

Three years.

I have never had a problem with it. The product is a little over anxious at times.

When we did the rollout in that phased approach, it was not difficult at all to roll in new technologies. They converged and hyper-converged into Turbonomic. So, it's definitely scalable. It moved right into the company pretty easily.

There are quite a few people using it, mostly for operations type of work. There are probably 25 users from operations, support, the performance team, and performance planning.

I have worked personally with Turbonomic, one of their guys, on some of this stuff. I haven't talked to him in a while, but he helped us develop a lot. The support for Turbonomic is incredible. 

Their technical support is excellent. By far, they are probably the best. It's probably why I am sitting here talking today, because I have to give these guys top props. I think the employee enthusiasm about this product is absolutely top-notch. It would probably be a great place to work.

I've worked with the Tier 1 support and their consultants. We had a consultant here for a year who was absolutely a top-notch fellow. He just became part of the team. He wanted to learn how we were doing things and tool the application to do what we needed it to do, which he did. He also left great instructions. A lot of his legacy is still there and being used today. 

We were using a combination of vROps and VMware. We were also using BMC TrueSight, which we still use today. There are a couple of others out there, because the network team uses a few things. There is all sorts of stuff that I think they were kind of hog-tying together to make them work.

Some of these solutions are ingrained in our processes and have been around literally forever. So, there isn't the staff or the resources right now to rewrite a lot of these things. Currently, we do kind of a side-by-side comparison, and I believe some folks have written some ways to integrate the new data from Turbonomic into the old way of doing things. That's just a culture change at the company. It's just a big place that has been around for a long time, which works slowly.

This solution was brought to us by one of our AVPs. She had worked at HPE, and we didn't know about it. She said, "Let's look at this," because apparently she used it at HPE. We looked at it, and said, "Ah, this is great." Then, we went with it.

Turbonomic is more customizable with a lot more features. 

Even though you can turn on automation in VMware, it's not very good. It's kludgy and has a tendency to break things, where the autobalance of workload management that Turbonomic does within VMware is much better than the VMware tools which are designed for this. That may change, because VMware seems to be doing great with this. However, for right now, Turbonomic is the only way to go. 

TrueSight is just straight up what you see is what you get.

I went to the training when they first rolled it out, but I wasn't involved in the setup.

They did the setup in sections. So, they started off with the lower environments and some of the clusters out there that really needed a lot of attention, mostly blade servers and such. So, it was a gradual rollout. I think the entire rollout was somewhere in the area of a year to a year and a half. However, to get it fully running, where we could use this solution to our benefit, that was at least six months.

We use scheduling in real-time for implementing the solution’s actions as well as manual execution, which is when we schedule for a later date to change activities. We have had to enable or disable certain things. It seems to do that just fine.

We used Turbonomic for everything to do with the setup. On our side, it required about five FTEs, who were engineering and operations personnel. There were folks who were creating the design and where it would be rolled out. That design was passed down to the operations folks who were actually implementing everything. So, it was done in phases.

We only have two engineers doing maintenance, a primary and a backup, and this is like their extracurricular activity.

The ROI would be in the return of hardware, specifically for a lot of the older hardware where we start to go into the converged systems. That is where we are seeing our ROI. We are getting rid of that old, junky hardware, starting to integrate and align things into one specific way of managing all our workloads, but not on old hardware. If anything, the ROI is end of life hardware elimination.

Also, we see ROI in extended support agreements (ESA) for old software. Migration activities seem to be where Turbonomic has really benefited us the most. It's one click and done. We have new machines ready to go with Turbonomic, which are properly sized instead of somebody sitting there with a spreadsheet and guessing. So, my return on investment would certainly be on currency, from a software and hardware perspective.

Turbonomic provides a proactive approach to avoiding performance degradation. Our capacity and performance team use this solution as part of other tools that they utilize.

The solution provides application-driven prioritization, with its AppDynamics integration, to show us how top business applications and transactions are performing. If Turbonomic comes back and tells us, "Hey, this application needs more resources. Or, you're coming up onto a period where it will need more resources. Start planning now." We have certainly used it for that and will continue to use it for that. We have actually used it for troubleshooting a couple of times, saving us 25 percent when it comes to performance-based issues.

We have seen a 25 percent reduction in tickets opened for application issues.

Turbonomic has definitely helped to save human resource time and cost involved in monitoring and optimizing our estate. 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 did an architectural review. We had to look at other options, but I don't know exactly what those were.

Some of the tools which already exist are not that great. They really need to up their game if they're going to keep up with something like Turbonomic.

If you have a big shop, and it's scattered all over the place, then definitely take a look at this tool. Make sure you take a look at this tool because there is probably fit for purpose licensing for any size organization. It's a great automation process.

Turbonomic shows application metrics and estimates the impact of taking a suggested action based on its input from AppDynamics. So, we plug it into AppDynamics, then AppDynamics and Turbonomic seem to work together for that. 

It knows what business-critical applications we have, but I don't think it manages anything specifically within the application itself. It is mostly just resource-driven.

As money starts to get tight and budgets start to get really scrutinized, I think people are going to have to start looking at using Turbonomic to help optimize cloud operations to reduce cloud costs.

We are going to continue to use it going forward. I just don't know at what level. There are a lot of changes being made to the infrastructure, so it's going to depend on the tools and things that become available, like VCF as well as all the products that they have built-in through vROps, enhanced vROps, and things that already come with the software.

I would rate it an eight (out of 10). Personally, there is a lot that it does that a regular person like me does not have the time to sit down and dig into it. We expect things to be a little bit more automated. That is why I gave it an eight. I would give it a 10 (out of 10) if I got in there and it's like, look, click, click, and click. However, I don't know if there is that kind of a comfort level here yet to just let this thing go and have its day with the place.

The product is looking at things in the cloud or in Azure and it gives us reports of things that it could possibly do in Azure, however, we mainly use it on-prem for our VMware environment. 

The use case for Turbonomic really began with us trying to reduce a lot of the costs, and a lot of the CPU, and RAM. We had an idea that we could possibly save some money, however, it was theoretical and something that we really couldn't put our hands on or touch. Turbonomic was the solution that really gave us a tangible way of being able to see what we could do and to see those changes made in an efficient manner while also having the reports behind it to back up the changes.

That, and the placement that it does in VMware, where it places machines where it best sees fit on different hosts, is how we use the product. 

We've been able to separate different applications into groups in Turbonomic and see how many resources they take. We can see what resources we need and which resources may need to be increased or decreased in certain places. The grouping and analytics enable me to be able to take everything back to my application owners and say to them "your application or your list of servers did this type of work in our environment." It really gives me an opportunity to be able to show a cost. I can show how many resources we're using and how many need to be used.

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.

The way it handles updates needs to be improved. That would be one of the areas I would focus on.

I wish that the upgrades and updates were more easily accessible. Some of that is based on my environment and how my environment is set up. Due to the fact that we are in such a lockdown environment, I wish that it would be better or easier to perform the updates.

I've used the solution for about three years now.

It's been very stable and we've had no issues with it. We did have an issue with the update, however. Turbo was really, really helpful and just involved right away and we were able to get that problem resolved. That said, in terms of general stability, it has been greatly stable.

We haven't really scaled out with it. We realized we probably needed to scale back in due to the savings that we were able to do thanks to Turbonomic. It is scalable. Our environment is very large and it was able to handle all of it. It can handle scaling your environment out or back in.

We have about eight people on my team. We work in converged infrastructure server engineering. We handle VMware and anything inside of the infrastructure.

It is being used extensively. Our usage would probably stay where it is as the environment is changing a little bit. It will probably hold steady with where we are.

The technical support is excellent. If the problem gets too complex, I've been able to speak to somebody in development for help even if I've had issues with one of the updates.

Positive

We were using VMware beforehand. We switched due to the fact that somebody in the environment had used Turbonomic at a previous engagement or a previous location. We decided just to give it a try and it worked amazingly well.

The initial setup was straightforward. I worked with some engineers and they were really helpful and really kind. They guided me along the path. 

We actually deployed a proof of concept first, over a couple of days. Then we took the proof of concept and applied for a license and then just put it in an environment. The deployment process took a couple of days.

In terms of pricing and licensing, I wasn't involved too much in that portion. In terms of the licensing, I would say it's definitely worth the investment. Even initially, if it seems out of range, the cost savings will make up for it.

We did look at some other options. We had issues with some of the other options and they weren't able to do tasks as efficiently. Turbonomic had a different environment just for testing it out. Another coworker also had used Turbonomic, so we tested it out in the environment.

We looked at VMware, the cost of using some of the VMware products, and how much it costs to do that. I don't remember the names of the other products. I just remember Turbo was high on a couple of our lists and we reached out. Cisco had a relationship with Turbo so they brought them in and we decided to test it out.

I've been using Turbonomic as it moved from different versions for about three years. Right now, we're on the CWOM version of Turbonomic and its version 3.7. We're using it on-prem and we also are using Turbonomic for just cloud reporting.

Turbonomic would be one of the best in terms of application awareness. Just being able to see different applications and see their usage is great. 

I'd advise potential new users to do a proof of concept and try it. It's an excellent product and the level of savings, as well as the reports, will really give them hands-on experience in the environment to get arms wrapped around everything. It's an excellent product that has paid for itself.

For someone looking into Turbonomic that already has a process to optimize their environment and monitoring, it's a good idea to work with somebody in technical support to see if there's something that you could get Turbonomic to help you with. You should evaluate it for savings, test it out and do a proof of concept as well. Turbonomic is hands down one of the best products.

I'd rate it ten out of ten. It does a really excellent job of reporting, handling placement, measuring resources, and increasing or decreasing those resources. Overall the product just sells itself. It has been very helpful in the cloud and on-premise. 

We use Turbonomic for workload placement. We've leveraged it for workload migrations, so if we get a new storage array or a new cluster, and we need to migrate workloads over to it, we can set up a policy and let it just run along as it can. It is especially valuable with storage array migrations, which can be very time-consuming if being done manually.

The biggest thing that we leverage it for is the right-sizing of virtual servers. This is relevant for both hot-add, and during an improvement-maintenance window where resource reclamation of the virtual servers takes place.

Turbonomic provides visibility and analytics into our environment from the application layer all the way down the stack to underlying infrastructure resources. The app dynamics information is a little newer to us but we do have that information there. Utilizing it is a matter of getting the right teams within the consult to understand and essentially automate or utilize the actions that it's suggesting from an application perspective. This capability is something that's important to us as an organization, and this product is helping to show the value of that data.

The visibility and analytics capabilities have helped bridge the data gap between disparate IT teams, which is a never-ending work in progress. Better collaboration between these teams is definitely something that is important to me.

Our mean-time-to-resolution has been improved by the visibility and analytics capabilities that Turbomoic provides, although it is difficult to approximate by how much because it varies on a case-by-case basis. As an example, with the right-sizing feature, a lot of what it's doing is hyper-reactive. I wouldn't call it completely proactive, although it could certainly be in some cases. Essentially, it's providing resources before the app team even knows they need them. As a result, it's preventing a problem from ever happening.

This product helps us to interpret our data alerts and spreadsheets, which is something that's important to us.

With the help of Turbonomic, we are better able to understand where performance risk exists. A lot of it has to do with the automation that we have enabled on the platform. Performance risk isn't necessarily something that we look at every day, waiting for something to start blinking red and then manually addressing it. The real success is turning on automation and having it try to fix the problems as much as it can without human interaction.

Another thing that this solution helps us with is reducing performance degradation. Again, it's on a case-by-case basis and it's difficult to estimate how much it's saved us. In the past, where we were given proactive notification about upcoming work and were able to capture the baseline, and then watch the product handle it using automation, we've seen where it was successful and did show value. However, a lot of those situations may be happening every day or at least every week, and we don't have proactive notifications. This is because we're not day-to-day working with the end-users or business units. It all ties back to the infrastructure that we support.

This product is certainly helping to improve our applications' response time SLAs, although we haven't focused on establishing that baseline and understanding how much things have improved from that perspective. This is a very important aspect for us and if we had a baseline then it would help to show more value because we could relate the improvement back to Turbonomic.

One thing that we are able to assess is savings from an OpEx perspective as a result of right-sizing. We understand how much an administrator would charge back to the company per hour to troubleshoot a particular issue. Every time a right-size action is performed, whether it's giving more resources or turning down more resources, a ballpark estimate of how much time an administrator would spend troubleshooting, and ultimately providing those additional resources, is approximately 30 minutes. Those actions happen a lot, and we're able to estimate and capture the savings from an OpEx perspective by right-sizing in place rather than having an administrator perform those actions each and every time. We have a dashboard to show the value from an OpEx savings perspective with the automation that it's doing. Last year, for example, we had $188K in operational savings due to automation, and we have saved $16K so far this year.

In general, Turbonomic has helped to reduce our CapEx and OpEx. In terms of CapEx, the right-sizing of workloads ultimately gives us an increased capacity for additional workloads or putting the right amount of horsepower towards the workloads that truly need it.

Turbonomic has helped reduce resource congestion and starvation. It's a powerful orchestration tool and it gives us the platform where, if we did want to innovate in a way that we haven't before, we can leverage the platform to help us toward that. This is something that has happened before and it was able to help us to get there. It's another tool in the belt to help support these initiatives.

The right-sizing feature is the most captivating one for us. It helped in taking the emotions out of what people think they need, basing it off of real data, and providing them what they actually need. It's not really a special feature, but the support that we received from that team really helped us in our success. There were definitely some customizations that needed to take place to make it successful.

This is the most aware of our products, in terms of understanding all of the components from the top down. It is integrated with all of the different modules, all the way down to the core infrastructure. All of it is tied together and there are not many tools that can do that.

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.

Between the different versions and releases, it seems that reporting fell by the wayside. It seems like there was more in the past than there is today, which has made it a little bit more of a challenge for us to capture some historical information.

I have been working with Turbonomic for approximately five years.

This is definitely a stable solution. 

We have had some issues with downtime in the past, realizing it might stop running and we weren't made aware. But the stability's been fairly solid. Working closely with our account team, they understand how we use the product, and more often than not, encourage us not to run the latest version. They want to make sure that we're properly testing before we go to the bleeding edge.

There is value-added from the support team, in them knowing our environment, and what might be impacted by the upcoming upgrades.

This is definitely a scalable solution. We can manage multiple environments using a single pane of glass, which is something that I really like.

The last big update was to create a containerized environment, which laid the foundation for us to continue to grow with this centralized system. From our perspective, it seems scalable and we haven't run into obstacles that I can't overcome.

We have approximately 12 users.

There have been some transitions with the recent acquisitions that have impacted our account team and some of our technical people. However, we are happy with them.

Out of the different products that we oversee, they're one of the best relationships that we've had. They not only help us through problems but help us on an annual basis to reiterate the value that the product can bring to our organization.

I would rate the support an eight out of ten. There is always room for improvement. Nothing will ever score a ten out of ten, even if it is perfect.

The bottom line is that they're superior at the majority of everything they're doing from a support perspective. Some of the biggest hiccups were that a new version would introduce a new problem. For about a year and a half, we'd go to the next version and this very thing would happen. This left us chasing these problems and they kept coming back up. However, it seems that things have stabilized since then, which was a couple of years ago.

We use other tools as part of our operations, including AppDynamics to help with Application Performance Management.

That said, we have not used any other products that have the same capabilities as Turbonomic.

The initial setup was fairly straightforward.

There were some complexities added from our side in trying to make sure that this platform was most successful with the standardizations that we have in our environment. When Turbonomic would perform actions, in most situations, we're actually calling on it to run in-house developed scripts to perform the additional configurations required from that action. Since that has been taken care of, it's been great.

To clarify, the initial setup is simple but we brought some complexity on ourselves. To deploy it to the level that we're using now, it took between six and eight months. This was really taking our time going through non-production environments first, then production, turning on one thing at a time.

There were also scheduling concerns, such as having our maintenance windows every other month. This didn't give us much opportunity throughout the year to deploy, which is why it took several months for us to get fully implemented. Even today, we're still not using it to its fullest potential.

The product was purchased from reseller CDI and I recommend them.

We deployed it ourselves but received assistance directly from Turbonomic.

With respect to product maintenance, it's a fairly hands-off tool. 

We're trying to hand off some of the routine maintenance windows. A lot of the predefined actions are in there but it's a case of setting the window based on our approved maintenance times for reclamation of resources.

If it's a change that involves policy and configuration then the change will be by a senior engineer or someone a little bit higher, because the change can be disruptive if it's not configured correctly. Otherwise, it's fairly hands-off.

The team even considers it an employee at certain times. For storage migrations, as an example, tasks that we had an administrator dedicated to, such as moving workload after workload, have now been assumed by Turbonomic.

We started to realize value from the solution with our first right-sizing, which was probably between three and six months. At this point, we were able to reclaim resources in our environment that were not utilized.

ROI is not something that I am focused on but in general, I think that we see ROI in several areas. I base this on the improvements that I've seen in regard to application performance.

We've turned down VMware's vRSOps advanced suite, which is similar in its basic functionality. The problem is that they are behind and just not at the point where we see it being a replacement for what we're using today with Turbonomic. At the same time, vRSOps does have advantages.

The basic pro for VMware is that you have one vendor with one solution, which is a nice simplification. The cons are that the vRSOps group and VMware, in general, don't have support anywhere near the level of Turbonomic, and the functionality isn't necessarily there as an orchestration and workload placement tool.

Where vROps shows its value is from an operational monitoring and troubleshooting perspective. We have seen value in that aspect and in fact, this is why we still have it in our organization.

We are not actively managing workloads in the cloud but it is something that we plan to do in the future. We are using Kubernetes on-premises, although we're trying to get more engagement from that team on the product. Importantly, the right-sizing on-premises is setting up our next steps in moving toward the public cloud, and toward that consumption model to the best that we can.

We may utilize Turbonomic in the cloud. The licensing switch that we went through really opened up not only the ability for us to easily scale to other private cloud environments that we have outside of our main one but much more easily scale to the cloud when we're there. I definitely would consider this tool to be a requirement as we start deploying infrastructure out in the cloud, just to help us understand that we're sizing to the best that we can.

My advice for anybody who is implementing this solution is to utilize it to its fullest potential. This will include aligning your company's culture. The foundation of the product is putting resources where they're needed, and this is done based on actual data. The politics have to be thrown out the window. As long as that can work in your organization, then this is a great tool that can configure your environment to run optimally.

For someone that is interested in Turbonomic, but already has a process in place for monitoring and optimizing their environment, then this is something that should be evaluated. I can't say that it will replace the existing product but there is more at stake. For us, it's the support and the team that come with the product. This is what surprised me the most and something to look out for.

Overall, Turbonomic has had a positive effect on our application performance. It's helped on many different levels, including toward the resolution of problems. It's even helped flat out prevent problems from happening in the first place.

I would rate this solution an eight out of ten.

Turbonomics helps us understand resource usage and enables us to make decisions about how to utilize those resources. For example, let's say you check your monthly water bill and see that it's up 25 percent, but you don't know why. It keeps going like that until you check your toilet and find that the seal is slightly broken. 

Every now and then, a tool will keep running when you're not using it. Turbonomics will identify when the toilet is running and fix it for you, so your bill goes up. It automatically makes the adjustments.  

Our organization uses cloud-based infrastructure, so everything is metered. You're wasting money if you have a system running but you're not using it. Turbonomic can take that system offline or suspend it. It can also adjust resources so that they're optimal for a particular workload. It gives you visibility and also takes action automatically. 

Turbonomic offers a single platform for optimizing complex, mixed environments. With APM integration, it can tell you how each application is performing and rationalize the resources to ensure the optimal configuration for performance, so there's no waste. It will make those adjustments for you based on application trends. It covers the complete stack all the way up from your UI down to your core host machine if you're running on a VM or the physical machine if you're running on a device. It tries to ensure consistency and hasn't caused any additional overhead on my applications. 

The automation features are helpful because engineers no longer need to focus on fixing issues. They can spend their time on innovation and more important things. Right now, a lot of the work is still being done manually. When I get alerts, I send a staff member to make adjustments, but I can't do that in real time. It might take days or weeks to address a ticket. The meter is constantly running while we're waiting to fix that so that money is going down the drain.

It's hard to quantify how much time we save using Turbonomic, but it's around 20 percent. I only do analysis and remediation on maybe Tuesday and Thursday. It's not about the time that I waste; it's about the time and cost we can recover. I no longer need to wait until Tuesday. If something happens on the weekend, the tool can fix it on Sunday. It does save time, but the bigger aspect is cost savings.

The core expense of our setup is cloud costs, so cloud management is a huge piece of our financial operations. We're constantly looking at cloud spending and ways to make that more efficient. 

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. 

We're still evaluating the solution, so I don't know enough about what I don't know. They've done a lot over the years. I used Turbonomics six or seven years ago before IBM bought them. They've matured a lot since then. 

We've been evaluating Turbonomic for the last few months. 

Turbonomic is stable. 

Turbonomic is highly scalable. 

In addition to Turbonomic, we have a tool called Apptio Cloudability that gives you a report on what you spent that month. I have to go back and identify what is going on. Turbonomic identifies the issue, records it, and fixes it with no manual intervention. We also used the native cloud solutions provided by Amazon or Google, but they weren't as effective as Turbonomics. 

Turbonomic is fairly easy to deploy. The product is highly intuitive from a deployment standpoint. We worked with a consultant from the vendor. The deployment team consisted of five or six people.

We evaluated and purchased Apptio Cloudability. Turbonomics offered an opportunity to reduce the costs of our physical environment, but it's also part of our cloud journey. The cloud capabilities were a significant factor for us. 

I rate Turbonomic nine out of 10. It goes into a lot of detail about what you know and your opportunities, but there's always room to improve. 

My main purpose is to provide an assessment for clients, agencies, or the government to help them understand their workloads and what it would take for us to do a migration of their workloads, before we do it. I generate a report based on the client's existing on-prem workloads, and see how Turbonomic optimizes everything and how things would look once they are migrated to either Azure or AWS. I review that report and all the possible savings if they move their workloads to the cloud.

It's deployed on-premises, but we have been using it for public and private cloud.

It provides visibility and analytics at the underlying infrastructure stack level, in the way I use it. That is key. That's what differentiates between an agency saying, "Go ahead and move our workload because we see the value," or "Just decommission everything and we'll find an alternative to keep our workloads going." Most of my discussions are around trying to get things from on-prem to the cloud, and Turbonomic has been very helpful with that.

The visibility and analytics help bridge the data gap between disparate IT teams. They give us a central point around which we can sit down and discuss the savings and how we would actually move the workloads, based on how workloads are truly running today on-prem. That is very important because we want to show the client savings and help them to optimize their workloads, whether a system is on-prem or in the cloud.

In addition, the visibility and analytics have helped reduce our mean to resolution when it comes to identifying places where we can optimize things and getting that to the customer as soon as possible. Instead of having to search and discover all the infrastructure and calculate things based on usage, I have a single pane of glass with Turbonomic. I can look at the graphs because the data is already there.

The solution gives us a single source of truth for application performance management. That is vital because when we migrate workloads for any client. I've been doing migrations for almost eight years now, moving people from data center to data center, and workloads from data center to data center or to the cloud. One of the key factors in doing that is a single point of truth. If you don't have that, you repeat work. You don't know what's truly correct and the migration could fail.

Turbonomic also gives us the ability to review reports with our clients on a monthly basis. It makes us look good. It shows that we're being proactive and that we're looking ahead to ways we can help our clients optimize and save money. And if we're saving them money, they're happy.

From a performance standpoint, we know before we move workloads that we have optimized the performance for that workload. That means that when we migrate it, it shouldn't be a problem. In all the migrations we've done, performance hasn't been a problem, based on the performance readings we got from the Turbonomic reports.

In addition, it helps us meet our SLAs. When many workloads were running on-prem, we could not track our SLAs as well as we can now, thanks to tracking things with Turbonomic in the cloud.

Overall, from our organization's standpoint, the solution has helped to build our entire migration effort. Our migration team can follow a single path and understand how to present the data to our clients and help them in moving from one point to another. It helps the engineers to focus on issues and it really helps them do their migration prep. The smoother the migration prep, the smoother the actual migration will be.

The feature for optimizing VMs is the most valuable because a number of the agencies have workloads or VMs that are not really being used. Turbonomic enables us to say, "If you combine these, or if you decide to go with a reserve instance, you will save this much." That feature gives you an estimate using, for example, a Microsoft cost model, to show clients how much can be saved.

Another key aspect that I really like about Turbonomic is the user interface. It gives you a visual representation of where there might be issues. That stands out. When I'm looking at resources for migrating different workloads, if something is shown in red, that identifies a risk. If it's a risk where it's currently running, it's definitely going to be worthwhile to migrate it. It helps us to mitigate that risk before we do the actual migration.

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.

I've been using Turbonomic for a little over two years.

The customer support is definitely a 10 out of 10, and the training gets a 10-plus.

Positive

We leverage IBM Turbonomic to manage our 28 on-premises data centers, effectively optimizing resources and ensuring their operational efficiency. It helps us automate workload scaling to guarantee consistent application performance. Additionally, while we primarily use Turbonomic for on-premises management, we also utilize it within our AWS environment for cost optimization purposes. This allows us to identify and implement cost-saving measures within the cloud.

One of our key challenges was finding a tool that could provide a holistic view of our entire environment and report back key data points, such as CPU and memory usage. This would allow us to identify potential areas for cost savings. We were frequently receiving requests to increase resources like memory and CPU, so we needed a tool that not only gave us historical data but also empowered us to take action, whether that meant automating changes or manually making the changes and IBM Turbonomic does that.

We use IBM Turbonomic in a hybrid cloud environment. Although it supports multi-cloud capabilities, we currently operate in a single-cloud setting.

Turbonomic offers visibility into our environment's performance, spanning across applications, underlying infrastructure, and protection resources. 

The visibility and analytics help to bridge the data gap between disparate IT teams such as applications and infrastructure. This is important for awareness collaboration, cost saving, and helping to design and improve our application.

Enhanced visibility and data analytics have contributed to a significant reduction in our mean time to resolve. Tools like Turbonomic provide crucial visualization and insights, empowering us to make data-driven decisions instead of relying on assumptions as we did before. This newfound transparency translates to a massive improvement, going from complete darkness to having a clear 100 percent view of the situation.

Although our applications are not optimized for the cloud we have seen some improvement in response time.

IBM Turbonomic empowers us to achieve more with fewer people thanks to automation. Previously, customers frequently contacted us requesting resource increases to resolve issues. Now, we have a tool that allows us to objectively assess their needs, leading to a deeper understanding of our applications. This solution also generates significant cost savings in the cloud and optimizes hardware utilization within our data centers. Its AI algorithm intelligently allocates servers on hosts, maximizing efficiency without compromising performance. By fine-tuning resource allocation without causing performance bottlenecks, Turbonomic extends the lifespan of existing hardware, postponing the need for new purchases. This effectively stretches our capital expenditure budget. We started to see the benefits of IBM Turbonomic within the first 60 days.

IBM is a fantastic partner. Their tech support has been outstanding, and the product itself is excellent - a very solid offering.

By automating resource management with Turbonomic, our engineers are freed up to focus on more strategic initiatives like innovation and ongoing organizational projects. Previously, manually adding resources was a time-consuming process that interrupted workflows. Now, automation handles scaling efficiently, saving us thousands of man-hours and significant costs.

It has illuminated the need for SetOps. It has highlighted areas of overspending, and the actions we've taken have demonstrated significant cost savings.

IBM Turbonomic has positively impacted our overall application performance.

IBM Turbonomic has helped reduce both CAPEX and OPEX. It has also significantly reduced cloud build times.

On-premises, one advantage I find particularly appealing is the ability to create policies for automatic CPU and memory scaling based on demand. This improves elasticity and responsiveness to application needs. Additionally, IBM Turbonomic helps us track and quantify cloud cost savings, facilitating informed decision-making.

We're also implementing FinOps principles. By collaborating with other departments, we can demonstrate the cost implications of various resource allocations. For example, specifying a minimum processor requirement might incur higher cloud costs. This increased awareness through IBM Turbonomic allows us to predict impact and make cost-effective decisions.

Turbonomic can modernize the look and feel, making it more user-friendly to access and obtain information.

I have been using IBM Turbonomic for over two years.

IBM Turbonomic is one of the most stable solutions that I have worked with in the last 26 years.

IBM Turbonomic is highly scalable.

The technical support team is both responsive and knowledgeable. They quickly escalate complex issues to someone who can resolve them efficiently.

Positive

The initial deployment proved complex due to our extensive environment, encompassing over 23,000 VMs. This necessitated a year-long rollout, overseen by a dedicated team comprising a salesperson and a senior technical expert.

IBM Turbonomic helped us with the implementation. They were a great partner.

We have seen a return on investment with IBM Turbonomic.

IBM Turbonomic is an investment that we believe will deliver positive returns. We justified the purchase based on its potential to significantly reduce costs, which will allow us to recoup the investment and generate additional benefits. This ultimately makes refinancing a worthwhile option.

I would rate IBM Turbonomic ten out of ten.

We need to perform regular maintenance due to the frequent release of updates.

I recommend that users review their internal processes and partner with other departments to facilitate company-wide implementation. Collaboration will be crucial, so ensure they have a FinOps practice in place, or establish one if necessary.

We have four hosts and 250 VMs, so we automated Turbonomics to load balance across multiple hosts and achieve the most efficient usage of resources. The objective is to make the machines run as well as they can. The second use case is sizing recommendations, which we treat as gospel. The third use case is to help us replicate our VMs into Azure using a tool called Zerto. Turbonomic ensures we size the Azure instance correctly because we need to choose from a list of 10,000 sizes. We'll pay too much if we get the sizing wrong. 

Before implementing Turbonomic, we had difficulty reaching a consensus about VM placement and sizing. Everybody's opinion was wrong, including mine. The application developers, implementers, and infrastructure team could never decide the appropriate size of a virtual machine. I always made the machines small, and they always made them too big. We were both probably wrong. 

Turbonomic can determine the correct size of the box. The appropriate placement and sizing change every minute, so you'd only be correct for a minute if you ever got it right. Everyone is making incorrect assumptions about virtual machines based on physical workloads. They want to add more CPUs or 600 gigs of RAM. You're not going to get that in a virtualized or cloud environment. If you don't size it correctly, it will cause a performance issue or cost too much in the cloud. Turbonomic helps us avoid these mistakes. 

It helps us do everything we can to make a VM run optimally in an automated fashion. I have to understand why the VMs need to be redistributed. It just does it. If we have a problem after that, I know that placement and sizing aren't the problems. If I still have a problem, I need to use other tools to figure that out.

The solution helps us avoid performance degradation by placing the VM correctly and telling us if we're sized incorrectly. If someone complains about a performance issue and asks for more resources, I will consult Turbonomic about whether they need more CPU or RAM. If Turbonomic tells me that they do, I will give it to them. 

However, in the case of SQL Server, Turbonomic can't tell me if I have an index that's out of balance, so it doesn't fix the underlying problem. It just says that we need more resources to do this. When a situation like this happens, we go to the database admin and tell them we're using too much RAM, disk, or CPU. He will identify the problem and notify the other employees to stop doing whatever is causing it. 

We don't have applications that external users can access for a fee. Users in our company consume our applications to help them get business done. We don't have constant performance issues. By transitioning to virtualization, we got the benefits of fault tolerance and high availability because we used clustering. Now, instead of having available or unavailable applications, we have applications that perform better or worse. Turbonomic helped us avoid having applications that slow down because we virtualized. It's all shared resources, and we don't get trouble tickets about slowness unless there's an application problem.

Turbonomic provides some visibility into the application layer and underlying infrastructure. We also use ControlUp to drill down into the services running on each VM and what's hogging resources. Turbonomic manages Kubernetes and will size the Kubernetes container, but we don't use it to identify processes that consume the most resources.

Turbonomic handles workload placement and sizing exceptionally well. Granted, we don't make VMs with three CPUs and weird numbers of RAM. We try to come up with sizing that makes sense, but it tends to be close to what Turbonomic recommends. It does something that no other solution does. Microsoft and VMware will not suggest the correct size of a VM. 

It's essential to have an automated solution for handling placement and sizing. Things are changing so fast that a decision about the correct balance of your VMs across your cluster is incorrect by the time you make it. Turbonomics is constantly evaluating placement. 

Changes in the loads happen at various times of day, and some loads are unknown to us in different periods of the year, so we automate the decisions. It has a feature that enables you to start your VMs small and let them grow. Then, you can turn them off every month and try again. 

Turbonomic not only calculates the availability of resources for the task at hand but also forecasts what will happen to the system if I perform my recommendation. The problem with performance tools is that they sometimes provide recommendations that cause a problem, and they need to correct the problem they just fixed. Turbonomic avoids that by measuring what will happen if they do what they want. That's awesome.

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. 

We use NetApp storage on the backend for the big one. I didn't want to re-provision a new volume. I wanted a placement. If it can place my workload in CPU and memory, why can't it tell me the placement of my disk volumes to spread my IOPS instead of telling me to make another volume? 

We have used Turbonomic for three or four years. I've gone through several upgrades.

Turbonomic is highly stable. We've never had issues. 

Turbonomic can handle any workload we throw at it, whether in the cloud or on-prem. I think that's why they went to Kubernetes. If your workload increases after your deployment, it will make recommendations on its own Kubernetes cluster that you need to size up or down. It doesn't automatically scale, but it understands that there are challenges to scale over time. In our case, we've scaled it down. It didn't need as many resources as it had.

I rate IBM support a ten out of ten. I've never had a problem. We can always reach support, and they know their product well. They can typically answer most questions or get back to me with a solution in a reasonable time. For example, when I asked them about the storage placement issue, they said, "We don't do things exactly the way you want. We understand it and will add that to our list of feature requests." If enough customers ask for it, they'll do it with the storage placement based on IOPS.

Positive

We use Turbonomic for infrastructure awareness, but we have other tools for application awareness like ControlUp. VMware has distributed resource scheduling, but we believe that Turbonomic is far superior to that.

Turbonomic has gone through several versions, and the latest is the most complicated because the first wasn't Kubernetes. It's a deployed OVF, so it's not that hard to do. Understanding the UI and configuration options isn't easy, but I'm an old guy who has been around since '87. I think all the new interfaces are unbelievably complicated and incomprehensible. It's like any product. Turbonomic is easy once you understand it. 

I didn't find the deployment to be complex or challenging. After you've deployed it, you need to configure it, do some placement, and tweak its recommendations. For example, I would never implement an odd number of CPUs, so I will specify that it only makes recommendations in units of two.

The deployment process is relatively lengthy because they've done all this Kubernetes stuff. You deploy it, and it spawns all these Kubernetes things. You need to wait until it finishes. It isn't instantaneous. 

Turbonomic requires no more maintenance than the average application. We keep it updated but don't immediately upgrade to the latest version. We stay one version behind. That's the sweet spot because we don't want to deal with problems in a brand-new release. We also review it annually. I can think of at least two occasions where they scheduled a technician to help us get it to the spot we agreed was the best. 

I haven't calculated the ROI. We do our internal ROI that looks at what it would cost not to implement Turbonomic. The cost would be poor performance based on infrastructure constraints. We believe it's worth what we pay for it. 

It has some features that help us control costs on the cloud. If we perform the recommendations on sizing, it shows you the difference in cost versus inaction. Turbonomic helps us size machines in the cloud and Kubernetes containers. We can run sizing reports that forecast whether a workload will be cost-effective if we move it to the cloud. 

When we create on-premise machines, the capital expenditure for on-prem equipment is fixed. It doesn't cost us more to be inefficient because we've already bought the hardware. It doesn't matter if I use it 70 percent or 90 percent. If you have an inefficient workload on the cloud, it may cost you a lot more than running it on-premises. You need to fix the application to avoid something stupid like storing data forever. Turbonomic will help us identify an inefficient application so we don't move it to the cloud and find out it costs a trillion dollars to run it.

When we first bought Turbonomic, we paid by ESXi host or something like that. We have several hosts with small workloads and a few with high workloads. We negotiated with Turbonomic, but the licensing model prevented us from covering a significant portion of our workload. Later, we got everything covered because they changed their pricing to a per VM model. 

I believe they modified it when IBM acquired Turbonomic or maybe right before. We could cover all the VMs that weren't included when it was charged by the number of hosts. We use virtualization for fault tolerance and high availability, but we might only have a handful of VMs. 

The licensing is now straightforward. You have a fee for a certain number of VMs plus maintenance. Everybody's switching to a subscription model these days. I'm an engineer, so I don't care how much anything costs. I only care that it works and doesn't keep me up at night. I'm not involved in purchasing. I don't think there are better, cheaper alternatives, but we review that annually.

I rate Turbonomic a ten out of ten. I always tell people about Turbonomic when talking to other infrastructure nerds. When we talk about infrastructure, the crucial part is not the implementation but measuring performance over time to see if your top is spinning out of control or falling over. 

We can typically get it right up front. The big question is: Does it continue to run, or is it slowly running out of steam? Turbonomic recommends, "Hey, if you're going to continue to build like this, you need to start provisioning the host." We don't use it for that, but if I get those recommendations, I need to check on the garbage collection, i.e., deleting unused resources that someone built and forgot about.

My biggest advice about Turbonomic is to use it to its fullest potential. To get the best benefit, you need to use it and measure the results. And if you don't use it, they're going to come up and go, "Well, what are you using this for?" "Oh, I don't know," and they won't renew it.

If you already have distributed resource scheduling or similar tools, Turbonomic does a better job and can do other functions that DRS can't. VMware won't recommend ways to size a VM in Azure so you can move it. Why would they want to do that? Turbonomic is middleware, so it doesn't have skin in the game regarding placement. It's making impartial recommendations irrespective of whose storage, hypervisor, or cloud platform you're using.