Turbonomic helped us with cluster projections. We have different-sized hosts in a single cluster. I have two-socket and four-socket hosts sitting in a cluster, so the impacts aren't easy to understand in aggregate. Turbonomic helps to evaluate what will happen in hypothetical configurations. I can forecast the effect of dropping one server and adding another. If I drop a pair of 48 cores and add a single 96 at a different gigahertz, will that be adequate? It can tell you if you need to add more cores to manage your server hardware purchasing. 

It also assists us in evaluating performance risks. The dashboards show what current risks are happening, and we use the planning features to see the what-ifs. We check the heat map daily. If something pops up there, we check it out to prevent issues from happening down the chain. It's mainly on the VMware side with the older VMXs. We haven't found anything on the Nutanix side to be worried about.

Turbonomic has helped us address performance degradation under VMware. It identifies when there's a bottleneck in the storage line, so we can start moving some virtual disks around to different ones. It helps in the older silo structure. The performance degradation is on the VMware or the fiber channel SAN side. Some of the SANs are nine years old. 

It is able to identify points before we even noticed them. We're meeting all our SLAs because it never gets to the point where they catch something. They might say, "Oh, it seems a little slow," and then they'll return from lunch, saying, "Oh, it's okay again." 

We log into it in the morning and let it sit up in the NOC. We take a peek when it shows something. We'll check it out if it's red, but it'll usually clear up if it's yellow. For example, all systems might run at 110% immediately before registration closes while students try to get their last class for their senior year registered before the other students. We'll return to our normal 20-30% usage in about an hour and a half. 

They won't notice a thing because we'll be moving to more of a Kubernetes Docker-style system with Nutanix Carbon. I will probably try to integrate that with Turbonomic. We will probably connect Turbonomic deeper into that stack because that will be able to pull and spin up new Dockers automatically on hardware and not within anything else, giving the server room to spin up another Docker. Theoretically, I've got room for about 600 more containers, and we currently use 15. 

We're centralized IT. I use Turbonomic mainly as a showback because we don't charge our different departments. There technically is no charge in our current Red Hat licenses, and that's picked up. We pick that up and get requests in. There is no self-service here.

The instructor says, "I need 400 cores and two terabytes of RAM to run my analysis." I'm like, "That's how they run it on a supercomputer. We don't have those here. Now, if your research grant wants to buy us one, sure, we'll set it up. Tell us where the half-million dollars is, and we'll set it up for you." There's no self-service here, but we use it for a showback.

We had Turbonomic load-balancing all our clusters, and we did not let VMware load-balance our clusters because of the algorithms. Their marketing and share algorithms were much more precise than VMware's because I had disparate-sized servers. 

VMware liked to put a heavy load on my little boxes and leave my big boxes alone, or it stuffed the big boxes full and left the little boxes alone. Turbonomic keeps everything about even. Their algorithm for load balancing was much cleaner until the ESXi 7 than VMware. That made the hardware more cost-effective because I didn't have little guys sleeping in a corner someplace sucking up hardware, power, and cooling while not doing any work all day.

Resource starvation has never been an issue for use. We run different resource pools, and we've never had any service hit 100%. I have redundancies and reserve capacities needed to weather any storm. We use Turbonomic primarily to monitor and maintain equal resources on all servers. 

We've never had a server hit 100%. I might have one hit 80% periodically before they moved something around. We've been in the VMware game since 2.X back when a monster server had four cores and 32 gigs of RAM. We've been virtualized over 80% for the last 12 years. We've been heavily virtualized for over 80% of the previous decade. We knew virtualization was the way it was going and went for it.

It reduced our operational expenditures because I have reclaimed some of the time typically spent generating reports. It's part of our system, and we just use it. Turbonomic is part of our network operations center. The dashboard is on my screen, so I can see if the indicators turn yellow or red. I can address the issue before it gets to the point where I'm getting calls from the service desk.

We have parts of our payroll engine that run pretty hot, depending on what's happening. Those pieces of the payroll engine and the SQL servers tend to overrun a server pretty quickly, if you're not careful. But Turbonomic always does a great job of making sure that that is not happening.

Our company is growing like a monster. Even during COVID we've been growing, where a lot of companies, unfortunately, are not. Because we've gained a lot of new customers during COVID, because other payroll companies have gone under or because our pricing model is good, the result has been a lot more load on our systems. And even though we've had much more load, Turbonomic has done a great job of keeping everything balanced. We're able to completely utilize our systems before having to introduce more hardware.

Its whole job is to manage our business-critical applications by understanding the underlying supply chain of resources. In my opinion, applications are applications. When your application is running, it's reserving a piece of memory, it's utilizing the CPU, and it's utilizing the network interface. There is a certain limit to the hardware that's available to it. Applications need watching. If we were to use the pieces where it digs down inside the application, it would probably even do better, but we're not using those pieces yet. In the end, no matter what the application is doing, it's using resources, either on a regular basis or on a random basis, and Turbonomic looks for patterns and spikes and how long these patterns last. It looks at the risk of a spike only happening for 30 seconds versus 30 minutes. It makes decisions to move other things off or move off the application in question. It does a great job keeping that balance.

We hardly do any manual execution. Maintenance windows are when it's probably most important to us. For example, when we're upgrading or doing a repair on an ESX host, we're really taxing the other servers because those CPUs and all the I/O capability on that host are lost. That's when it's even more important for Turbononic to keep the rest of the system healthy enough and to keep the system going without showing any degradation. It helps us while we're doing maintenance.

It provides a proactive approach to avoiding performance degradation, absolutely. It always looks at history and looks for patterns. In a lot of cases, it knows that there's a scheduled task or that, on average, a customer is always like hopping on around three o'clock. After a week or two of seeing the exact same things happening—although that timeframe really depends on how big your organization is, the bigger your organization, the longer it takes to understand the full dynamic—it really understood all the patterns and all the schedules. In the past, we'd see systems starting to get a little hotter and then a little hotter still. With Turbonomic, that issue would just go away by shuffling stuff around. After a week or two we wouldn't see that thing getting warm anymore. When that application or server got hot, it never put that host into any kind of jeopardy anymore, not even a little bit where we thought, "Hey, we should look at that."

We have definitely seen a reduction in tickets open for application performance issues. In some cases we get tickets for performance problems because the developer wrote crappy code and wants to blame us in infrastructure. But I can show them, "Look, we're not overloaded." They look at some of the logs we provide them that show that the servers are operating at full capacity and usually they find that there's some kind of weird issue with a database query that they wrote. The solution has definitely reduced tickets for application performance problems a little bit, but it has mostly decreased troubleshooting time.

It's helped us to always meet our SLAs. In previous companies I've worked at, the company was either so cheap, or the boss didn't understand how the infrastructure works, that we got to the point where we were over utilizing our hardware. That's where Turbonomic really makes a difference because without it you can be way over-committing what you have versus what you need. You always have servers that are sitting there idle, so it's best if you can balance the ones that run hot with the ones that run idle and shuffle around use of them based on what you're utilizing. If you don't have Turbonomic, then whatever boxes happen to be on there could be in overdrive to the point where you start ballooning and paging. That can cause a denial of service because you don't have enough resources to handle the workload. It's really great to try to maximize every inch of your infrastructure, to make sure you're utilizing everything to its fullest capacity.

Whoever is on call loves Turbonomic because if we didn't have it we'd be getting alerted much more often. That's especially true at three o'clock in the morning when some backup or something that's not even important is running and the pager will go off because it hits some threshold for too long. Turbonomic sees, "Okay, this server does this at this time and it's going to use a lot more resources than anybody else," and it just shuffles everything away.

It helped reshape the organization. We used to have around 46 admins who could create virtual machines in Azure, and it was very difficult to manage them. It became exceedingly expensive, getting to a point where it received attention from the president of the company. Installing Turbonomic gave us sort of a governor over our cloud environment, where people started to really understand that everything you do has a cost. Now, we have like four or five admins. If someone wants a VM, we run a plan based off: available RIs, cheapest costs, and can it go into shut down mode at night? This has helped us create a standard of implementation going forward to prevent us from spending the money in the first place. While I'm sure Turbonomic would say that's their overall goal, we just never really saw it that way. 

I didn't know it was going to change how we submit tickets and work orders for adding service to the environment. That has all changed for the better.

I know when we are moving workloads from on-prem to the cloud, we have not been utilizing the planning in Turbonomic as much as we should. I think that is changing. People who have access to Turbonomic are now realizing, "Here are the specs of my machine. Turbonomic will put it in the cheapest compute resource template that it can find." 

This is starting to change how we even consider building something. We don't ask the end user, "What do you need?" Instead, we say, "What do you want to host?" Then, we look at other virtual machines out there. If we want to host a website, then it will be X number of users per day, month, or year. We look at some of our other marketplaces, then we make a plan to see what Turbonomic recommends, as it takes into account the disk, IOPS, RI, CPU, RAM, etc. This helps us prevent the spend in the first place. The idea where we build then save on the backend, that is what's changing. We are no longer just building blindly, then going to Turbonomic, and saying, "Okay, fix what we built." We are saying, "Turbonomic, tell us what we should build." I would rather do it when we build a machine than have to take a website down and schedule maintenance at two in the morning on Saturday when I am at the bar.

It gives people like me, who are engineers, the ability to launch environments without having to create a bunch of changes down the road. I think that's a wake-up call for a lot of the people at the company. Because we would just build our build, where we were spending $5,000 more than we should, so then we have to put in change tickets and scale all that back. I don't have to do that anymore.

If we see a system or service increasing usage, we can then anticipate building it out bigger to manage traffic and workflow. With version 8, it will almost be like having a tool to manage our machines actively versus just actions.

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. 

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.

It integrates into our other tools that we have been able to stitch together. When I take a look at an infrastructure cluster, I can see what applications are running on it. I can see down to the transaction level who is actually causing a performance constraint. We can then go back to our application teams to get that issue resolved.

When I start to take a look at a cluster level, I can look to see which application is running in that cluster. Then, we can get down into specific transactions. We can then watch to see how workload is trending and identify where we may need to add more hosts into the environment. With our transactions, we use Turbonomic linked into AppDynamics. When it links in and pulls the application data, it also helps us dig down. So, if I see my utilization trending up, then is it something on the infrastructure side or the application side? Is it something the application team needs to address? Or, is it something my infrastructure team can address? This allows us to make fact-based decisions.

In our organization, optimizing application performance is a continuous process that is beyond human scale. We would not be able to do the number of actions that Turbonomic takes on a daily, weekly, and monthly basis. It is humanly impossible with the little micro adjustments that it can make. That is a huge differentiator. If you just figure each action could take anywhere very conservatively from five to 10 minutes to act upon, then you multiply that out by thousands of actions every month, it is easily something where you could say, "I am saving a couple of FTEs."

On Windows 2008, whenever we did a large scale OS upgrade, it was kind of taking a look at what resources were allocated to each of the applications and server instances. Then, you basically would replicate that. Being able to use Turbonomic, we have been quickly able to go through and take a look, and say, "Okay, wow. This may have been what was previously allocated to you. We now realize that your utilization doesn't require that level." We are able to actually downsize as we go through and rebuild. This part, the planning aspect, is really good.

One of the things that we completed this year was starting to tag applications so we can pull up more critical applications and take a look at their resources needs. We can have a specific dashboard per critical application.

Turbonomic provides recommendations about ideal resource levels. It helps us identify where we lack capacity and require more resources. These forecasts save time because we can avoid a capacity crisis. It tells us where to place the machines, so resources are automatically balanced. Those recommendations are there from the tool. That has helped.

It is a standard tool that helps to analyze capacity metrics. Without Turbonomic, we would struggle to manage capacity planning. It is essential to have a tool like Turbonomic because we rely on it for VMware capacity planning.

Turbonomic helped to reduce performance degradation by forecasting utilization and notifying us when we need to increase hardware resources before it reaches a critical threshold. Our SLAs require us to maintain 24/7 availability. 

In our organization, optimizing application performance is a continuous process that is beyond human scale. We see tremendous value in Turbonomic to help us close that gap as much as possible within our organization. Essentially, Turbonomic will provide us with a recommendation on how to address a workload in real time based on its actual utilization. Then, we have pre-defined time slots where those actions can be implemented with minimal impact on the business because some of the changes may require the rebooting of the server. So, we don't want to reboot the server at 2:00 in the afternoon when everyone is using it, but we might have a dedicated time slot that says, "After 5:00 today or 2:00 in the morning when no one is using it, this server can be rebooted."

We have leveraged Turbonomic to not only ingest the data from the utilization of workloads to come up with performance-based driven decisions. We also have used Turbonomic to help orchestrate and initiate those actions automatically for a very large portion of our organization without us having to even be involved at all. For some more sensitive workloads, we look at them and coordinate with the business whether we will take action at another date and time.

We primarily use it in the public cloud for servers. We also monitor storage and databases within Azure. This is another added benefit that we like about Turbonomic. When we look at a decision, we are looking at how that decision is being driven based from a storage perspective, the IOPS being driven to a specific storage solution within our public cloud offering, its decisions based on specific DTU utilization from a database perspective, or if it is even a percentage of memory or CPU consumption. It takes into account all those various aspects and never puts us in a position where we take a decision or action without accommodating these other pieces and having them negatively impact us.

That level of monitoring is what has given us the confidence to allow Turbonomic to implement actions automatically without having IT oversight micromanage decisions, because it provides that holistic view, takes into account all those aspects, and ensures that a decision that is implemented never puts you into a point of contention or concern. We have the confidence to allow the appliance of the software solution to take actions without little to no IT oversight.

Turbonomic has identified areas within our public cloud where we had storage that was not being used at all. So, it provided us with insight into what that unused storage was so we could delete the unused storage and save on the recurring consumption cost. That was very helpful.

We have identified numerous workloads which have been overprovisioned by an administrator. We were able to essentially right-size workloads to use less resources, which cost us less money in our public cloud offering, e.g., a configuration with less memory or less CPU than what it was originally configured for. That helps us reduce our cloud consumption significantly.

In addition to ensuring that workloads are right-sized correctly, we have been able to save even more with our public cloud consumption by identifying workloads where we could purchase reserved instances, essentially long-term contracts for specific workload sizes. This allows us, on average, to save an additional 33% or more on our server run rates.

Turbonomic provides a proactive approach to avoiding performance degradation. It has allowed us to detect issues before they have actually become issues. Traditionally, in IT, we would not be aware of an issue until someone from the business came to us with an issue, then we would investigate the issue. In some cases, we would spend a couple hours trying to figure out what the issue was, then determine if something needed more resources, like more memory. Since Turbonomic, we have been able to almost immediately identify that our system needs more resources and take the action right then and there. Or, Turbonomic has identified there is an issue and we take an action, then notify the business that an action was taken in order to preemptively avoid a business impact.

Previously, a business impact use case would potentially take us hours. With Turbonomic, whenever we run into a business impact use case now, before we even log into a system to initially troubleshoot it, the first thing we do is go to Turbonomic and see, "What is Turbonomic telling us? What is the workload like now? What has it looked like in the last 24 hours or week? Do we see any trends to help guide us towards identifying where we should go from a troubleshooting perspective?" From that aspect, Turbonomic has definitely helped guide our path to resolution.

Rightsizing and right categorization are part of optimization exercises. Turbonomic provides a single platform to help optimize costs and resource efficiency.

It provides good visibility of performance at the resource level. This visibility and analytics have helped bridge the data gap between disparate IT teams such as Applications and Infrastructure.

The visibility and analytics from Turbonomic have not helped reduce our mean time to resolution. We only used it for cost savings and not optimization.

Turbonomic has not impacted our application performance. You can do it if you integrate it with a tool like Dynatrace but not in itself.

Turbonomic can optimize the monitoring of public cloud, private cloud, hybrid cloud, and/or Kubernetes. That is where it specializes. With respect to the cloud, their algorithm is pretty good, and their recommendations are relatively trustworthy as compared to other tools. For cloud optimization, it is pretty good. It is also pretty good for balancing on-prem resources.

On the on-prem side, we had some automation or scheduling in place. On the cloud side, we did not do any scheduling. On the on-prem side, it would automatically go and make the changes needed, but on the cloud side, we took the recommendations, and we made the changes ourselves. We did not schedule them in the cloud. It is hard to quantify the time saved, but the analysis part is pretty good. We must have saved time and money.

Turbonomic helped to optimize costs and automate the changes on-prem. There were savings, but I do not have an exact number because we did it in phases. The first time, there would be more savings, and from the second round, they would slow down because you already reaped the benefit from the first-time recommendations. We did not do all the changes at once, so I do not have the numbers, but typically, any organization would have 20% savings in VMs and disks. Turbonomic does a good job. It depends on how big an organization is, but on average, the tool can cut down the VM cost by 20%.

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.

The proactive monitoring of all our open enrollment applications has improved our organization. We have used it to size applications that we are moving to the cloud. Therefore, when we move them out there, we have them appropriately sized. We use it for reporting to current application owners, showing them where they are wasting money. There are easy things to find for an application, e.g., they decommissioned the server, but they never took care of the storage. Without a tool like this, that storage would just sit there forever, with us getting billed for it.

The solution handles applications, virtualization, cloud, on-prem compute, storage, and network in our environment, everything except containers because they are in an initial experimentation phase for us. The only production apps we have which use containers are a couple of vendor apps. Nothing we have developed, that's in use, is containerized yet. We are headed in that direction. We are just a little behind the curve.

Turbonomic understands the resource relationships at each of these layers (applications, virtualization, cloud, on-prem compute, storage, and network in our environment) and the risks to performance for each. It gives you a picture across the board of how those resources interact with each other and which ones are important. It's not looking at one aspect of performance, instead it is looking at 20 to 30 different things to give recommendations.

It provides a proactive approach to avoiding performance degradation. It's looking at the trends and when is the server going to run out of capacity. Our monitoring tools tell us when CPU or memory has been at 90 percent for 10 minutes. However, at that point, depending on the situation, we may be out of time. This points out, "Hey, in three weeks, you're not going to be looking good here. You need to add this stuff in advance."

We are notifying people in advance that they will have a problem as opposed to them opening tickets for a problem.

We have response-time SLAs for our applications. They are all different. It just depends on the application. Turbonomic has affected our ability to meet those SLAs in the ability to catch any performance problems before they start to occur. We are getting proactive notifications. If we have a sizing problem and there's growth happening over a trended period of time that shows that we're going to run out of capacity, rather than let the application team open a ticket, we're saying, "Hey, we're seeing latency in the application. Let's get 30 people on a bridge to research the latency." Well, the bridge never happens and the 30 people never get on it, this is because we proactively added capacity before it ever got to that point.

Turbonomic has saved human resource time and cost involved in monitoring and optimizing our estate. For our bridges, when we have a problem, we are willing to pay a little bit extra for infrastructure. We're willing to pull a lot more people than we're probably going to need onto our bridge to research the problem, rather than maybe getting the obvious team on, then having them call two more, and then the problem gets stretched out. We tend to ring the dinner bell and everybody comes running, then people go away as they prove that it's not their issue. So, you could easily end up with 30 to 40 people on every bridge for a brief period of time. Those man-hours rack up fast. Anything we can do to avoid that type of troubleshooting saves us a lot of money. Even more importantly, it keeps us productive on other projects we're working on, rather than at the end of the month going, "We're behind on these three projects. How could that have happened?" Well, "Remember there was that major problem with application ABC, and 50 people sat on a bridge for three days for 20 hours a day trying to resolve it."

In some cases you completely avoid the situation. A lot of our apps are really complex. A simple resource add in advance to a server might save us from having a ripple effect later. If we have a major application, as an example, and to get data for that application, it calls an API in another application, then pulls data from it. Well, the data it asks for: 80 percent of it's in that app, but 20 percent of it's in the next app. There is another API from that call to get that data to add it to the data from application B to send it back to application A. If you have sometimes a minor performance problem in application C that causes an outage in application A, which can be a nightmare to try and diagnose those types of problems, especially if those relationships aren't documented well. It is very difficult to quantify the savings, but If we can avoid problems like that, then the savings are big.

We are using monitoring and thresholds to assure application performance. It is great, but at the point where our monitoring tools are alerting, then we already have a problem in a lot of cases, though not always. The way we have things set up, we get warnings when resource utilization reaches 80 percent, because we try to keep it at 70 percent. We get alerts, which is kind of like, "Oh no," but we can do something about it when the applications are at 90 percent. The problem is there are so many alerts and it's such a huge environment. Because there is too much work going on, they get ignored. So, they can work into the 90s, and you end up a lot more often in a critical state. That's why the proactive monitoring of all our open enrollment stuff is really beneficial to us.

Cost savings is a significant benefit, especially with our AWS computing. It cuts down on human error. For example, sometimes someone will spin up some resources in AWS and then forget about it. We can go into Turbonomic's reporting and see that a virtual machine is idle, so you might want to scale it down. If it's not being used, you should delete it. Then you can save X amount of money. Turbonomic will automatically apply those things for you and tell you how much you're going to save. It's integrated with your AWS billing report and everything; it can give you real data. You click a button, and it'll apply all the functions for you, so you save a bunch of money. I would say that that's a huge part of it for us.

We have a couple of different use cases, and it was essential for us to meet all of them without the need to go to several different vendors. Turbonomic can manage on-premises and cloud-native resources all in the same place, providing direct cost benefits through our cloud providers and our on-prem hardware storage.

Turbonomic has also helped us improve our efficiency as an organization. We can better understand the actual cost of our applications and how to optimize, so we've become more efficient and cut down some of the extra expenses. It's also useful for capacity planning. We can understand how much resources we're using right now and how much we'll need when we bring on new clients for our software solution.

Turbonomic has helped us manage multiple facets of our business-critical functions. Our company provides a software platform for our clients. They log into a portal that's hosted either in the cloud or on-premises. Turbonomic can monitor those applications as well as the underlying storage and computing resources. It's monitoring the applications themselves, the production environments, development, and QA for future changes. We can understand how changes are going to impact our production.

It depends on the system that we're looking at. We have a change-management process for our business-critical things and our production resources. With that, we either schedule a change or manually execute the change during a planned maintenance window. Our change management board approved other functions, like development and QA-type resources that aren't in production that we're developing. We can automate those kinds of things all the time. I know that our storage team automates a ton of tasks, but I'm not exactly sure. I assume they wouldn't be automating production resources either.

We follow some pretty strict change management policies. Applying some of these resources will require restarting your process. We would do it either in a change management window that we schedule through Turbonomic or manually apply it. 

Turbonomic's application-driven prioritization helps us identify where risks are coming from while proactively preventing performance degradation. It's nice to be able to avoid problems before they happen. I don't have to wake up in the middle of the night and respond to some alert because one of our applications ran out of memory, and people couldn't use our product. It's helped me get some sleep. Our storage teams are super stoked about that, too, because they had all sorts of alarms going off all the time, and they set up a ton of automation with Turbonomic to handle that all for them. We've seen a significant reduction in open tickets for application issues.

We had a lack of knowledge about things at our product level, and Turbonomic helped us resolve that. From an integration perspective, it also helped us find connectivity between our gateway tool products.

When it comes to optimizing costs and resource efficiency, before Turbonomic, we would add big, expensive storage and scale up across the tenant. Now, we are able to allocate the resources we need. We can also justify to the business, based on usage, why we are going with those resources. We have all kinds of proof to explain to the business how we are scaling down.

The visibility and analytics into our environment’s performance, from the APM down to the infrastructure, help us illustrate and clarify for the business the types of infrastructure changes we are suggesting. And they give us approval. Although we can collect the same information from Azure, Turbonomic is very user-friendly, and we can also automate notifications.

Regarding policy implementation, that can be implemented by a skilled engineer in five to 10 minutes. But if that same task is assigned to a new engineer who is not familiar with Turbonic, he would have to reference the previous document and the previous policy. Implementing the same thing would take that new engineer 15 to 20 minutes.

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.

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 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.

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.

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.

Turbonomic has shed light on processes, on how applications actually function for people. The folks in the IT organization still tend to build large, to oversize things, to make sure that their applications perform properly. Turbonomic sheds light on what could be a more efficient application and deployment.

We use it in a multi-cloud environment.

With Turbonomic, we were able to reduce our ESX cluster size and save money on our maintenance and license renewals. It saved us around $75,000 per year but it's a one-time reduction in VMware licensing. We don't renew the support. The ongoing savings is probably $50,000 to $75,000 a year, but there was a one-time of $200,000 plus.

It also saved human resource time and the cost involved in monitoring and optimizing our state by 25%.

It has provided us with a pretty good deal of savings on the front-end, helping us to correctly size VMs that were over-provisioned. We were paying a lot for VMs that really didn't need to be as big as they were. There has been a pretty drastic decrease in compute and cloud spends, due to either making the changes suggested by Turbonomic, or letting Turbonomic make the changes. That, coupled with using the suspend functionality to suspend machines that are not being used, pulled down our cloud spend a good bit.

The solution also provides a proactive approach to avoiding performance degradation. When you check in daily, it does evaluations on where your VMs and your infrastructure stand on that day. As a VM starts becoming more utilized, it will let you know to start planning on upgrading the machine because it's starting to show some extra usage that may grow beyond its capacity.

It offers visibility and analytics for monitoring performance across our environment, starting from the application layer and extending down the stack to the underlying infrastructure resources. Specifically, it concentrates on optimizing memory and CPU resources as part of our focus on hardware and environment optimization, without delving into additional aspects.

There was a single project where it helped us reduce the size of hundreds of VMs. This represents the only example with which I am familiar.

It's important to note that optimizing the monitoring of our private cloud is not the primary function of this tool. It is specifically utilized for optimization purposes. We employ it for tasks such as trending predictions and VM utilization performance. However, for monitoring, we rely on a completely different tool.

It has resulted in cost savings, specifically at the infrastructure layer.

The volumes feature lets us know which volumes or disks are not attached or that are not being used anymore and that we can go ahead and delete them. It tells us how much money we'll be saving if we delete them. It's the same thing with Reserved Instances. It has that ability, that visibility, with those recommendations. 

There is also the family type that tells you which family the VM is going to and how much you're going to be saving. Disk tiering is one of the latest features. If you go from premium to standard, it shows you just how much you're going to be saving. It makes those decisions based on metrics.

When it comes to cloud costs, to VMs, the solution is saving us about $30,000 a month. It has also definitely reduced our IT-related expenditures by about $40,000 per month. And when it comes to the human resource time involved in monitoring and optimizing our estate, it saves us about 20 hours a week.

With the reporting I am able to 'right size' my environment from the amount of cores and memory a VM actually needs to how many hosts I need to run that environment in. With automation, my machines are moved to the most efficient host based on the data that VMTurbo gathers, this is more efficient than DRS and WAY more efficient than doing this manually.

Turbonomic provides visibility and analytics into an environment’s performance. The visibility and analytics help bridge the data gap between disparate IT teams, such as Applications and Infrastructure. Having this visibility, specifically for cloud optimization, is extremely important

This has helped reduce our mean time to resolution (MTTR). On average there is about a 10% to 20% reduction, but it can be up to 60%.

Turbonomic has shortened application response time. It has made them more agile.

It's very good for optimizing the monitoring of the public cloud, private cloud, hybrid cloud, and/or Kubernetes. There are some health tools. It is extremely good for that. It is good for our clients to have visibility. It helps to have a complete view of what is going on.

Their automation has helped engineers focus on innovation and ongoing modernization projects. It has saved us about 30% of our work time. Having visibility for particular solutions helped resolve issues, troubleshoot the management of clusters, and so on. It helped to reallocate resources to other parts of the business.

Our clients have seen about 10%-20% of savings from utilizing Turbonomic. 

At the resource level, Turbonomic has enabled us to right-size our converged infrastructure to a more appropriate level. Instead of using 12, we can use 10. It has been really good in helping us size the environment for our compute.

Another benefit is that it has helped reduce performance degradation. That happens at the application layer sometimes, and then a reset happens and everything is fine again. I would estimate it reduces performance degradation by 10 percent.

It has helped us streamline a lot of those applications. We're leveraging faster configurations on our VMs. Those systems that are being virtualized are operating with better peak performance whenever it's required, and that's what Turbonomic really does. It gives us insight into those peaks and valleys that we tend to go through.

The solution has also reduced resource congestion and starvation. For us, it's always a matter of refreshes. I like the forecasting tool that Turbonomic has where you punch in what you have today and it assesses the history of that setup. Then you can say, "I want to replace it with a snazzy, new compute/storage component," and it will provide a recommendation. That is a very good forecasting tool.

The tool allows us to reduce the operational time spent managing our vSphere estate and more time developing new systems for the business.

We are able to maintain a much higher level of performance and efficiency in our virtual environment with the same or reduced levels of staffing.

We used Turbonomic to plan our hardware refresh, and it was right on the money. Now, we are using it to plan VM moves to the cloud.

We automate our vMotions, so it has helped us keep congestion on our hosts way down, and has been more effective than DRS. We also have used wasted storage report to reclaim over 2TB of storage from orphaned files that would have had to have been manually located before. Turbonomic has also helped with workload and capacity planning, allowing us to be more accurate with requesting expansion during budgeting.

Turbonomic helps us right-size virtual machines to utilize the available infrastructure components available and suggest where resources should exist. We also use the predictive tool to forecast what will happen when we add additional compute-demanding virtual machines or something to the environment. It shows us how that would impact existing resources. All of that frees up time that would otherwise be spent on manual calculation.

The solution's analytics are less important today because of changes in our environment. When we started using it, it was essential because we had more performance issues with the technology we had at the time. Turbonomic helps us interpret data alerts and speed sheets, which also isn't as important as it used to be. The solution helped to reduce performance degradation in the past, but it's less of an issue these days because we have optimized our environmental design.

Turbonomic reduced our mean time-to-resolution by about 50-60 percent when I used it for that. I can't say that it has improved our information sharing because our IT team is super small. We've got three people that are on the infrastructure. However, I have some experience with much larger environments, and the information that's in Turbonomic is easier to consume for some IT teams that maybe aren't as familiar with the virtualization environment.

It improved our application response time when we used it a lot more for performance analytics. We could see what consumed more IOPS and put it on the appropriate lens, where memory was not assigned properly. We could increase memory utilization or CPU. 

We can identify what is over-provisioned or if there are too many IOPS going through a particular data endpoint. CPU processor utilization, memory ballooning, etc., impact performance. 

Turbonomic provides many recommendations for right-sizing VMs for the tasks they're doing. That saves us significant time because we don't need to look at all that information and use calculators to figure it out. Turbonomic can tell you. Turbonomic reduced the time spent managing the performance of existing assets, freeing up time to do extra development work. 

I saw improvements in application response times when I used it regularly to look at performance gains. We achieved an improvement of around 20 percent in heavy application performance by right-sizing VMs and ensuring resources were appropriately assigned. 

We have a relatively small team for these tasks. We want to ensure that we have automation to provide our clients with the best experience, as well as reducing our overall labor. These factors are critical to our success.

Keeps clusters aligned, compute wise. We also use the planning and forecasting tools to determine needs.

It allows us to plan accordingly for any future growth.

Turbonomic has been helping us use our resources more efficiently, the challenge we currently face internally is getting people to allow the servers to be turned off to make the changes recommended.

I also like the planning tool, which is helpful to make sure we have enough capacity for failing over one datacenter to the other in case of disaster, while still maximizing what we already have and helping to keep us from making host purchases we don't need yet. It's nice not having to make all those calculations on my own.

Due to the loss of our primary VMware administrator, my colleagues had to take over managing the virtual environment. There were settings for various reservations set at one of our locations. Although memory/CPU may have been increased at some point on these systems, it was not until Turbonomic recommended increasing the reservations that we realized these settings were in place.

More recently, we have used it in planning data center upgrades. It allowed us to determine how many additional blades we may need due to upcoming projects. We built a template on the new model of blades we were considering, and of the new SAP HANA VM's we were going to be needing. It provided a plan of how many blades we would need to add to the environment to accommodate this expansion, which allowed for more accurate budget planning. 

Assure Service Performance: This feature is useful, because it gives us insightful information (similar to ESXTOP, but minus all the analysis) about a virtual machine (VM), whether it is over-provisioned or under-provisioned. The recommendations help us maintain a well-balanced virtual environment.

Policy/Automation: We set up a policy of automatically adding more vCPUs to the VMs based on Turbonomic's recommendation and continuous monitoring. This feature serves a dual-purpose for us: alleviate administrative tasks for our sysadmins and help maintain the highest performance in our VMs.

Plan: It is a great tool for capacity planning. It helps to eliminate all the guesses and gives us a good idea of the hardware specs we will need for future expansion.

Application/Network Module: Another great features that we use in our environment to help autoscale our application servers, so they are performing smoothly and fluidly with minimal intervention.

The reporting has allowed us to quickly evaluate our VM infrastructure and where we stand on a day to day basis. The planning/forcasting feature has allowed us to plan for additional hardware. At times, it has saved us lots of money when we did not need to purchase additional hardware even though we thought we would.

From a engineer perspective the ability to automate and show what is being used and what is really needed has helped us gain traction with virtualization. Also allowing application teams to login to Turbonomic and scope them to their servers has been a very valuable tool for us.

The help desk analyzes metrics events and Turbonomic tells you exactly what is wrong and how to resolve it. The solution improves the function of the help desk and saves time by making repairs quickly.

Performance is something that should constantly be monitored and constantly be worked on. Turbonomic is doing that in the background, without me having to manually do it. It's a great help. It's monitoring something that I just physically couldn't do all by myself because the environment is too large. It's looking at the resources in any environment and taking snapshots of where things are. At the right time, it's adding or taking away resources, and that's helping make the environment more efficient.

Planning is another way it really helps because it gives us an idea of the cost to move. We wanted to move everything to the cloud. It helps us to figure out what it would look like and how Turbonomic could even help, if we want to do that. But more importantly, it gives us an idea of how much it would cost. We get a round figure of the cost involved.

It handles virtualization, cloud, on-premise, and storage for us. We're moving towards it handling applications. The solution understands the resource relationships at each of these layers and the risks to performance for each. It understands them and makes adjustments based on what's needed. It also lets us know, if we need to make some adjustments, where they are. It definitely does a good job with that. It's not only knowing where to put things, but it's doing it for us.

We use it for implementing scheduling of actions for change windows. We do that based on our service-level agreements. We have to have a certain level of uptime. We do things because of our change process and the way that we have systems going. It's best for us to do it at a scheduled time, when everybody knows that the system will be going through some type of change.

It helps us meet SLAs by making sure that the machine has the resources it needs to function properly. Also, when it does make changes, it does it during the SLA windows.

We also use Turbonomic to show application metrics and estimate the impact of taking a suggested action. We have it doing that based on things in clusters. We'll set something up in the cluster and then have it see if that cluster is being utilized to its fullest or if it's being over-utilized. It gives us visibility.

In addition, it helps optimize cloud operations and reduce our cloud costs. We're putting things on a certain type of storage and moving things to best fit our environment and give us the best cost for our environment. It will also give us an idea, before we put it there, of what the cost will be before we move it to Azure.

It saves me a lot of time because I don't have to do things to monitor the environment to see what machines need RAM or memory or need CPU taken away or added. It can do that for me. I would estimate it saves me 20 hours per month.

As we project growth and expansion, we have to consider high availability and redundancy. We also have to consider business continuity and keeping track of current and future assets. Those items are really key to this program.

Turbonomic's largest impact is that I no longer have to manually monitor VM/host performance across vCenter's and clusters. This has been replaced with a single dashboard, which highlights recommended actions and reasons.

We have been able to get the most out of our hardware investment as its being used more efficiently. Virtual machine resource over and under commitment quickly filters to the top and can be addressed. We are also using the storage integration module which allows us to track storage performance from virtual machine to storage controller.

It has essentially replaced the need for 2-3 operations personnel managing requests for RAM/CPU resizing for VDIs. 

We have a system where our developers automate machine builds, and that is constantly running out of resources. Turbonomic helps us with that, so I don't have to keep buying hardware. The developers always say, "They don't have enough. They don't have enough. They don't have enough," when they just configured it improperly. Therefore, Turbonomic helps us identify configuration issues on their side so it doesn't cost me money on the other end to buy resources that I don't really need.

The solution handles some of our applications and cloud as well as giving us some insight into the storage aspect. While we have other tools, Turbonomic does give me insight onto my storage utilization as well. That part helps us with the virtualization stack. Turbonomic understands the resource relationships at each of these layers and the risks to performance for each of them, which helps us be a little more at the front of the game, giving us a little more insights to be more ahead of what we need to do.

To an extent, the solution helps manage our business-critical applications by understanding the underlying supply chain of resources. Some of our business-critical apps are our large virtualization stacks, and that is what our developers develop on. These keep our development environment running optimally so they can continue to develop without having to wait for resources.

It does suggest actions. It let us know ahead of time: 

• If we need to increase hardware.
• If we're okay.
• If we need to decrease hardware.
• What to expect during peak season.

We now have a more robust capacity request process within the department, and over the past 18 months, we have put on hold a scale out of physical hosts at both our primary datacenter and DR. This has saved the trust 1000s in new hosts and more than paid for the solution many times over.

The big benefits for me is a lot of time savings. I don't have to care and feed for each individual VM, and make sure that the environment's balanced just the right way. Also, I'm able to see which of my applications are taking more cycles, more compute cycles and RAM usage. I really can understand my environment a little bit better.

Our clusters are more balanced now than relying on DRS to manage workloads. Also, with the plan data, we are able to have actual data behind what our clusters look like now, how to best optimize them, and if we can afford to remove hosts. This will help us run an efficient, high performing environment while also limiting out licensing costs.

In the past, used multiple products to monitor CPU, memory utilization, or find virtual machine using large snapshots on datastores. We can look in one place throughout the day or get daily reports alerting us at the start of the day.

We use it to keep our virtual landscape balanced and bottleneck free. When we enabled automatic guest balancing within Turbonomic, our complaints about slow VM's dropped over 90%.

It keeps resources loads balanced with in my ESX clusters. Also the information about scaling up or scaling down machines is very useful as I am able to properly increase or decrease resources for virtual machines. We are more efficient and once again the reporting allows us to get pertinent data quickly.

We now have intelligently controlled VMs with consistent performance, it has helped us avoid purchase of additional hardware and software through increased utilisation in excess of 90%. It also eliminated configuration and capacity planning guesswork and has even identified where people have over-provisioned VMs so we can take back those resources and use them for other VMs.

There are a couple improvements: The sizing functions and the reporting are instrumental for the 600 engineers that login and use the product. They take the reports in both a troubleshooting capacity but also in a business review capacity, where they are able to share the trends with the client. Since our organization provides managed services to our clients, it is important our engineers are able to retrieve not only real-time data but the recommendations and rightsizing information instantly. VMTurbo’s automation component continuously helps us get the most out of our cloud infrastructure.

We have been able to recover significant headroom by utilizing Turbonomic's measurements. Moreover, there is no need for any in-house reporting to check capacity.

Server staff gained 4 hours a week in time they did not have to devote to items other than watching a hyper-v cluster utilization.

It has helped us to show real resource usage in order to justify or deny application owner requests for additional resources, and has helped us to rightsize our VMs to reclaim wasted CPU, memory, and disk space so we can avoid additional hardware procurement.

We have been able to use the planning feature to consolidate VMs on few hosts and have been able to show savings of several hundred thousands.

We have been experiencing VM guest performance issues for months. We tried many things including adding more hardware to no avail. Within a week of running Turbonomic we were able to see clearly which guest systems needed to be resized and, especially, moved to other nodes within our clusters to obtain the optimal performance.

Performance issues have decreased since there's no longer bottlenecks on certain ESXi hosts.

We first pursued the product some years back for it's capacity planning tools but we find the continuous analysis the most useful. We can spin up new servers without a full understanding of workload values and then keep tabs on it and make adjustments as needed.

On a daily basis we analyse the recommendations that VMTurbo provides and decide on whether these need to be followed. This ensures that our environment is running at optimal performance, providing the necessary resources that our customers need.

It has allowed our IT organization to keep investments in hardware flat for a projected three year period. In addition, we have seen a 30% performance improvement overall.

We utilized the Plan View to understand our hardware requirements. When we replaced our old hardware with the new hardware in our datacenters, we were able to more accurately predict our needs, then with the old rule of thumb method.

It has reduced our hardware costs by allowing us to purchase only the necessary resources instead of over purchasing out of caution.

While none of our VMs are highly transactional, good performance 24/7 is needed in the healthcare realm. Turbonomic gives us insight and assurance that we are meeting operational targets.

Planning infrastructure needs for our virtual environment was previously a tedious task that included a lot of guesswork. With Turbonomic we can now precisely model future workload and infrastructure supply to plan for growth.

We've been able to balance our environment with much more automated ease than was previously possible.

We no longer have to worry about our hosts being over/under provisioned. Turbonomic just evaluates the VMs and moves them for us. It's one less thing that we have to worry about.

It forced us to organize and standardize our storage environment - making smaller, generic datastores that had an unintended benefit of making the backups faster.

Prior to using Operations Manager I spent a considerable amount of time evaluating VM placement. I found myself shuffling VMs between hosts on a regular basis. The automation feature of Operations Manager monitors performance and migrates VMs between hosts as needed. It has been saved me a considerable amount of time.

Planning for capacity is much easier now. With this setup we were able to get specific reporting and it allows us to acquire the necessary hardware in time to meet the demand.

It allows our small team manage a larger infrastructure because we can focus our efforts in other areas.

Tuning VM's to the correct resource consumption, memory or CPU, has provided a true snapshot of the environments "foot print". This has aided in the correct sizing of physical machines needed to support the environment.

It helps us stay on top of the health of our virtual infrastructure, make near-real-time decisions on how to fine-tune and adjust our infrastructure, and lets us be proactive in our approach.

Auto load balance recommendations, always keeps our VMware cluster optimized.

Turbonomic provides weekly and monthly reporting functions to our operations. This gave insight to management on how our virtual environment is doing in terms of efficiency and capacity.

It has increased the utilization of our hosts without sacrificing performance. We can run more VMs over a longer period of time without needing to purchase additional hardware. The Plan tool is great as you can create a plan and save it for the future. It allows you to configure the plan however you need it to determine what is needed. For example, I use the Plan tool for capacity planning throughout the year, where it used to be a manual process. I now have plans that I can run and within minutes; the report will let me know what we need and where.

I no longer need to keep a watchful eye on the environment. Turbonomic provides assured performance. Anything that we don't yet have automated, it will make a recommendation to improve the performance of that particular server.

We have used the planning feature to retire ESXi hosts and move hosts from one datacenter to another. The planning feature told us how many ESXi hosts we needed to move based on the needed VM resources. We have also used the rightsizing recommendations on some VMs and plan on using it more extensively.

The number one improvement is that Turbonomic gives me more free time in my day to address other concerns. I no longer have to worry about host and guest resource utilization, because it is all handled for me behind the scenes.

I no longer have to worry about workload management, and when it comes time to plan for expansion it is no longer a hardware guessing game. Turbonomic can tell you exactly what hardware you will need based on the proposed workload. You can even input your own desired hardware configs to get more precise details on the report.

In the first month, we ran this as a POC. It saved us over 5k a month in costs by implementing its recommendations. The product continues to save us money but constantly updating its pricing files from Azure with current promotions and regional costs.

This product has allowed us to see how dense we can make our ESXi clusters.

With over two and a half years of Turbonomic in operation, we are now using the planner functionality for an ongoing datacenter consolidation project. The accuracy of our initial planner results again have been impressive, and this will allow us to project investment costs in detail and with confidence.

Helps us get the most out of the hardware we have in place.

Performance of all hosts have improved.

We use Turbonomic to fully optimize the use of our infrastructure. We also use it for health checks and assessments we perform for our customers.

Showed us how to merge clusters to increase density.

Being able to easily drill-down to find root issues.

The reporting features easily allows me to determine where we are having deficiencies in our virtual environment.

Right-sizing and right-balancing VMs and hosts used to be an ongoing, tedious, and time consuming effort. With Turbonomic, it does that work for me so I can focus my attention on other priorities.

Due to the VMs being correctly sized, we had an instant increase in the resources and saw an immediate CapEx saving, as we were in the process of purchasing new equipment.

Turbonomics is DRS on steroids. Our clusters have been perfectly balanced.

It continually gives me a solid look at my virtualization environment. It gives me a second set of eyes on our VMs.

It allows us to rightsize VMs. While scaling down is critical, it is also important to scale up when needed. Turnbonomic monitors your environment and reacts automatically. If a VM needs more vCPU or memory, it gets it automatically. No need for manual intervention. When Turbonomic observes a downward trend and it appears that your VM no longer needs those resources, they can be taken away automatically.

This toolkit has some hooks that allows us to upsize VMs on the fly based on the user's current utilization.

I like the reporting system along with the ability to export reports to PDF format.

We allow it to do all our VMotion migrations, ensuring our systems are running at their peak performance.

Previously we had no automated VM moves, which meant some of our VM hosts would be overloaded and others would be under utilized.

It has freed up space on our VMware hosts to allow optimized utilization of our resources.

Helped us right size a number of VMs and helped reduce CPU ready time.

This keeps our hosts optimized at all times and helps us in predicting when a new host will be needed soon.

I'm able to work in a more proactive manner and now have less issues to deal with. I'm able to avoid major problems.

This product has extended the life of our HW and allowed us to get more utilization out of the existing HW before needing to add hosts to the cluster.

The direct impact is that we decided to expand our platform and I needed specific numbers to see how a specific node would impact our environment, we were able to get specific reporting. That’s direct ROI. The feature that allows you to optimize and distribute your loads according to the balance of your “sweet point,” balancing your load against your compute is very valuable for decision making.

It has balanced the load on the hosts during the day to eliminate bottlenecks.

Ongoing process. Overview, scaleability and resource usage.

Having Turbonomic as a resource is like having a few extra engineers dedicated to performance monitoring, getting that time back from diagnosing resource issues is a huge plus.

Basically if there were issues with our VMs, which account for 95% of our environment, we had to wait until one of the techs would look and react to the issue. We can set up triggers to automatically handle these issues before they get any worse.

Everyone's sizing guess is wrong.

Turbonomics resolves the issue with continuous workload placement and sizing recommendations/actions.

The optimization has allowed us to focus our efforts on other areas of our virtual environment.

Better than DRS to load balance VMs across hosts, allowing us to release 30% more computing resources.

Getting the numerous VMs properly sized has saved a fair bit in hardware and licensing costs.

It has allowed me to manage over 19 sites with one person after losing two supporting staff members without a negative impact on operations.

We are able to maintain a higher level of performance & efficiency in our virtual environment.

Monthly reporting is more detailed now and we can see where improvements can be made within the environment.

We are able to optimize our resources in the infrastructure while gatekeeping the oversized resource requests.

With Turbonomic we are using our hardware resources more efficiently.

The VM rightsizing tools and the intelligent placing of workloads have helped us to not only streamline what we have but, in conjunction with the sizing tools, has allowed us to look at future scenarios and potentially reduce our spend on physical kit in the DC.

On a quarterly basis we take the VM right-sizing report and, based on the Turbonomic recommendation, we make the changes to resources. So far, no issues reported and it allows us to right-size our VM and use the resources properly. Along with that, the Projected Cluster report enables us to share the monthly report for capacity planning.

As a small organization I am solely responsible for the server/storage environment. With running as lean as we do, this product has simplified the decision making process for maintaining and managing the environment.  Decisions can be made much faster as data is in front of us that is up to date and on demand.

Our VMWare servers run a lot smoother with this product as it continues to look at resources and ensures our servers are on the best host at that point in time.

We are over 75% virtual, so the importance of our virtual environment stability and performance are vital. Turbonomic has been excellent in keeping us running smoothly.

We have used Turbonomic to help correct performance issues with applications in our business.

Capacity planning.

This has saved us a great deal of expenses by better balancing workloads across ESXi hosts. This allowed for higher VM densities.

We no longer have to continuously monitor our virtual environment through multiple interfaces (WhatsUp Gold, Veeam ONE, vSphere, etc.) to discover issues impairing performance. We now receive three separate reports every morning, one showing any actions that Turbonomic attempted to make which failed that lets us know what we need to look at; one showing recommended actions which we have designated within Turbonomic to be manually performed; and one showing all datastore utilization over 85%. All from a single product and all visible from a single pane of glass. With the capacity planning feature, it allows us to accurately determine the proper sizing for our replacement hosts while projecting for a rate of growth specified by us.

We no longer have to constantly manually manage host utilization to keep some hosts from running much 'hotter' than others.

Automation, policies, and reports have made a lot of previously manual work now either more efficient or completely automated.

There are fewer tickets about VM performance problems.

It gives us a quick look into what the environment is doing, down to the individual application, on the fly. We can find misbehaving VMs very quickly and to see what is related to it, be it storage or network.

We are able to focus in on the actual problem faster.

We use the tool to properly size the virtual servers and get a lot of resources back, while reducing the Ready time, so that was like winning twice.

We have been able to reduce manual labor in keeping our environment healthy performance wise.

Turbonomic has made more time available for me to pursue other projects.

As a one man IT department, keeping track of resource use across multiple sites has been complicated at best. With Operations Manager, I can see my entire infrastructure in one view, in real time.

It has saved us a lot of time in keeping our vSphere clusters running smoothly.

We no longer have to worry about cluster management, even in an environment with multiple hypervisor vendors.

We have saved money by not having to purchase Enterprise (including DRS) and no longer having to manually balance VMs in a cluster.

In the past, we would try to manually capture resource utilization, and then use raw math to extrapolate growth requirements. With Turbonomic, we can scale a production (or proposed) use case based on normalized real data, and know exactly the horsepower it will need.

We spend much less time trying to figure out how best to distribute VMs, and how much horsepower to give each one.

We can use the planner to support a business case. Improvements for performance or growth can be executed without human interference. You only have to think about it once then its fire and forget.

It is like we hired a junior system admin that works 24 hours a day to keep our environment in top form.

There are no more arguments between departments anymore. We add and remove resources based off our optimization report. And we no longer have to allocate absurd amounts of resources to cover for crappy code.

We had CPU issues with one of our SQL servers.  The software was able to provide us with recommendations on correctly sizing the platform eliminating many of the performance problems.

Allowed us to concentrate less on the day to day optimization and more on the big picture of utilization.

Turbonomic has allowed us to hold off on turning up additional hypervisors by allowing us to better use existing hardware.

Overall, Turbonomic has helped us be more efficient with the equipment we have.

We are a very small staff, and this gives us a peace of mind that our servers will run optimally.

Based off it's metrics, we were not only able to expand our storage environment but fine tune our environment further in order to achieve maximum performance.

Trending on capacity and overall workload for multiple clusters and hypervisors.

The balancing features on Turbonomic help keep our environment running fast and more efficiently over even DRS and sDRS.  In fact one the best performance features is the rightsizing tool, to either increase or decrease sizes of specific VM's.  Again this can save money, but also allows our clusters to perform much more reliably with little to no CPU Ready.

Automating move and resize tasks have allowed our team to spend less time micro-managing VMs and more time completing projects.

Helped to “right size” productions server environment. We now can do more with less.

we only do investments in new hardwarie when the life cycle is ending or when Turbonomic have been a right sizing.

The biggest improvement for us has been we have been more proactive when dealing with issues. We can even head things off before they cause any outages.

The automation of VMotion allows us to avoid over utilized memory and CPU on our Hosts.  Turbonomic also addresses the issue of I/O on our network something that has been a concern at times in the past.

Not having to regularly monitor our VM environments' resources has been a definite improvement over our previous time-intensive and often reactive processes.

Used it during a ESX host refresh project to calculate how many hosts we would need to accommodate our growing production environment over the next 2 years. We reduced from 20 ESX hosts to 8 large hosts saving on VMware licensing costs as well as server hardware maintenance

With VMware's DRS aggressiveness turned down and allowing Turbo to manage the load, we now have a perfectly balanced load across our clustered hosts. These could otherwise easily be off by as much as 30-40%, even on the very aggressive settings in VMware before Turbo.

Helps us rightsize workloads, highlight bottlenecks and effectively plan for capacity.

We are able to balance loads across clusters automatically, versus the very manual calculation and migration process without VMTurbo.

Turbonomic, per its design, finds bottlenecks and, depending on how it is configured, recommends actions and takes action to resolve the bottlenecks. Bottlenecks could be related to RAM, CPU, disk IO, etc.

Instead of buying more RAM for ESX hosts, Turbonomic managed the VMs in a more efficient way than DRS. The software makes recommendations of increasing the number of ESX hosts.

After our ESX lease was up and we purchased new hardware with more RAM, we continue to use Turbonomic in our development and UAT lane. I expect to use this product when using the cloud as the cost of CPU and RAM in the cloud will be prohibitive.

When spinning up new servers we use vendor best practices and hardware sizing documents.  Turbonomic lets us see real usage and resource requirements.

Our CPU ready used to be off the charts, after just a day or two, Turbonomic had it all fixed and users were very happy.

VMTurbo Operations Manager has given myself and my staff more time to focus on other projects and tasks as well as improved overall performance of the virtual environment.

Automatic migration of VMs keeps our workloads balanced at an efficient level.

It allows for automation thus freeing my time to do other projects.

Due to automation of workload placements Infra Management has been more efficient and smooth. Performance check and appropriate action taken to eliminate the same. Proactive suggestions based on underlying issues have helped us a lot. Due to that, we have reduced number of Incidents and effort being spent to manage our environment.

Turbonomic has, to an extent, helped us grow our VM environment without us having to buy new hardware. We are also using the performance statistics gathered by Turbonomic in our operations dashboards to give us control over the environment.

Turbonomic has helped mitigating the risks of LUNs filling up and resource congestion on individual hosts.

VMTurbo helps us manage our virtual infrastructure with a more automated and hands off approach thanks to the way it proactively looks at issues. Automated v-motioning, for example, has been a great and reliable feature.

Getting a better understanding on host utilization, providing better planning on infrastructure upgrades.

Limits the amount of time I have to spend staring at a screen to find bottlenecks and slowdowns in my virtual environment. The ability at one glance to see what machines are over provisioned or under provisioned and the ability to adjust that with just a click.

This product allows me to do other things while it takes care of all the "grunt" work. It also allows me to pull up reports in PDF format as needed, with ease.

Simple vCenter performance charts will show you only latency on datastores and will not drill down to show VMs causing the trouble.  Turbonomics will show the IOPS and which VM is causing it easy. 

Without having to worry about a host becoming over-utilized, we have been able to work on more important projects. We are able to be more efficient with our host resources, saving the business money.

I no longer have to keep my vSphere Client open to monitor constantly. I let the product move machines to new hosts and change datastores as needed for best overall performance. And all of this is based on best practice from Turbonomic and a few tweaks on our end.

We see increased speed in our environment as VM's are moved based on needs and requirements.

Planning for capacity is much easier now. It is relatively simple to model growth based upon expected company growth for a given cycle, allowing us to acquire the necessary hardware in time to meet the demand.

It allowed us to plan and scale our capacity based on our sales pipeline.

We have the best practices recommendations to optimize our virtual machine (VM) environment.

Use it over the built-in VMware tools for distributing VMs to hosts.

I no longer have to pour over the VM's and hosts statistics to figure out if my environment is running at it best.

I never have to worry about the ESX host CPU and memory utilization anymore and allow VMTurbo to do its job.

Have the best practices recommendations to optimize our VM environment.

Our servers are now correctly utilized, and I am now able to test a complete disaster recovery procedure, or plan a new VM or host implementation.

Response times have been improved on many of our servers.

Allowing Turbonomic to take over for vCenter DRS has shown a marked decrease in vMotion of virtual machines to keep our cluster resources balanced.

Turbonomic has kept my applications healthy and shown different ways to move my environment to a healthy state.

The TVs in our offices display custom dashboards that display the health of clusters and the actions taken by Turbonomic. It has helped us justify hardware and software purchases by easily showing our budget-makers where improvements can be felt.

Assurance spread of resources over our cluster and to right size VMs.

VMTurbo helps us manage our virtual infrastructure with a more automated and hands-off approach, thanks to the way it proactively looks at issues.

Automation of keeping resources balanced among the cluster.

Provides a level of automation beyond VMware provided DRS.

Gives me more time to spend on real issues.