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Just from a server perspective, we are running about 26, servers right now, where 97 to 98 percent are virtualized. One person can't get a handle on that. Even figuring out what direction to look, you need to have tools to help you. The technical support is good. We actually rarely call them. We have done quite a bit of work with them. Because of the number of purchases, they provided a TAM to work with us.

So, we have kept that TAM around on an ongoing basis. We pretty much just call them, and they handle any support issues. From a support perspective, it has been one of the better experiences.

If it stops doing its thing and moving VMs around, it will be many days before it is going to have any impact on the environment, because everything is configured so well. From that perspective, it is an easier application to score than if you have a VMware host crash and trap a bunch of VMs on it. We knew we were having some performance issues and ready queue problems that we felt could be improved. We worked with VMware for a while to tweak settings without a lot of success.

So, we saw what Turbonomic said that they could do. We tried it, and it could do those things, so we bought it. From a compute standpoint, Turbonomic provides us with a single platform that manages the full application stack. When we originally started, we were primarily looking for something that would make better use of our existing infrastructure.

Because it does a much better job of putting VMs together on hosts, we were able to save money immediately just by implementing it. At the time, we were non-cloud. There was a period of time where we just couldn't put anything into the cloud for security reasons. We have moved past that now and are moving to the cloud.

This solution has a lot more use cases for that, e. It's incredibly easy to set up. It took a couple of days. You spend more time building servers and getting ready for it. It gathers its own data from vCenter. It doesn't touch the actual servers at all. Same thing with the different cloud vendors. It looks at your account information. It doesn't actually have to touch the servers themselves.

As far as the product goes, it's not an agent based. It can gather information, and start making recommendations within two or three days, then better recommendations within a week.

After that, you're good. It doesn't get much easier. My group built a couple of the VMs that we needed and installed it. As far as gathering information, you don't have to put agents on any servers or anything like that. You give a user an ID for vCenter, and we have multiple vCenters.

The open enrollment applications are all mission-critical apps. If they go down, then the clock starts ticking on its way to seven-digit sales losses. It helps us avert situations like this multiple times a week.

We are constantly using it to watch and notify application owners. If we don't use Turbonomic for this, then what would typically happen is the node recommendations that they would get from Dynatrace would start showing them that there is latency in their app. If they started digging into Dynatrace, then it would come up, going, "I'm running at 90 percent CPU all the time.

I better get some more CPU. There are a lot of other tools in play that are monitoring what is happening. For our managers, Turbonomic helps us figure out what is going to happen. We use Turbonomic to help optimize cloud operations, and that has reduced our cloud costs. We have a lot of applications that we run which are very cyclical. Fourth quarter of the year, they get the crap beat out of them. The other three quarters of the year, they are not used a whole lot.

Without Turbonomic, would it be appropriate for the application to get resized nine months out of the year. Probably not. The tool itself is not free, but it's easily a positive ROI. It's hard to measure the benefit of just doing the DRS and optimizing our virtual infrastructure. I just can't stress enough how much it does such a better job of stacking VMs onto a set of ESX infrastructure.

If you're using Turbonomic and looking at a cluster, you will see pretty much even utilization across a set of hosts. If you let VMware manage it, you will see one host at 95 percent, then another at five percent. Everything is running fine, and that's all they care about.

However, if something starts going wrong on the host that is running at 95 percent, then you may see some degradation, just like rats leave the sinking ship trying to get out through that 5 percent host. Because it does a better job of balancing things, it utilizes infrastructure better, so you have fewer servers to host the same amount of VMs.

We have probably reduced our server purchase by a million dollars, just having Turbonomic manage the VDI infrastructure. Before they were static, so they just put an X number of VMs on each host, e. If we saw hotspots, then we would manually try and move a VM or two around. We are using Turbonomic now to manage that and the supercluster feature that lets us migrate across clusters, which is really key for the VDIs, because we had infrastructure that wasn't well utilized 24 hours a day.

So, we were buying lots of extras. The reason for that was we have developers in India, tons of people offshore, and people in the Philippines.

As those people come and go, the utilization of different clusters shifts radically. So, if you're trying to have enough infrastructure to manage each cluster individually, then it takes a lot more than if you're managing it as a whole.

That is one of the things that we use it for. When we have expanded our licensing, it has always been easy to make an ROI-based decision. So, it's reasonably priced. We would like to have it cheaper, but we get more benefit from it than we pay for it.

At the end of the day, that's all you can hope for. We paid for our TAM, but I'm sure it's embedded in the cost. However, that's optional. Obviously, you can do it all yourself: Open all your own support tickets and just send in an email to your TAM. Our TAM has access to log in, because she's set up as a contractor for us.

So, she can actually get in and work with us. There weren't a lot of other options available at the time, but we did look at three others. I know there are other companies on the market. I don't remember which ones were competing with it at the time. There was only really one other in that space at the time, and there's a bunch now. Then, VMware was there competing as well, saying, "You just don't have it configured right. We can do better," but they really couldn't.

The model behind the scene that Turbonomic uses to make decisions just has a better way of balancing resources. It considers a lot more factors. We use other tools to provide application-driven prioritization, to show us how top business applications and transactions are performing. Unfortunately, a lot of our infrastructure in the cloud is still legacy. So, we can't make full use of it to go out and resize a server, because it will bring the application down.

However, what we are doing is setting up integration servers now. This puts a change control out to make the recommended change and the owner of the server can approve that change, then it will take place within a maintenance window. We don't manage resources in real-time.

Most of our applications just don't support that. We don't have enough changes required that it would be mutually beneficial to us, so we aren't doing that yet, but we're headed in that direction. It would be a big stretch for us to actually use Turbonomic to take resources away from servers.

Our company has a philosophy, which was decided four or five years ago that the most important thing for us is for our applications to be up. So, if we waste a little money on the infrastructure to bolster applications when there is a problem, that is okay. We even have our own acronym, it's called margin of error MOE.

Typically, we are looking to have at least 30 percent free capacity on any server or cluster at any given time, which is certainly not running in the most efficient way possible, but we're okay with that. While we may spend three million dollars more a year on infrastructure, an hour long outage might cost us a million dollars. So, if there is a major problem with it with big performance degradation, then we want to have the capacity to step up and keep that application afloat while they figure out the issue.

It projects the outcome of if you are going to move from one set of infrastructure to another, then it will make a recommendation. For example, if I'm moving from one type of server to another type of server where there are different core counts, faster cores, and faster memory, then it will tell me in advance, "You need fewer resources to make that happen because you are moving to better equipment.

Biggest lesson learnt: What you should do is the obvious, it is just difficult to get people to do it. You need to have servers grouped and reported up to an executive level that can show the waste. Otherwise, you are working with server owners who have multiple priorities.

They have a release that's due in two weeks which will impact their bonus at the end of the year, etc. If you hit them up, and go, "Hey, you're wasting about a thousand dollars a week on this server, and more on the others, so we need to resize them.

On an individual application or server basis, it's not a big deal. That is the biggest challenge: competing priorities. You have one group trying to manage infrastructure for the least possible amount while getting the best performance, and you have other people who have to deliver functionality to a business unit. If they don't, the business unit will lose a million dollars a day until they get it.

Those are tough priorities to compete with. Build that reporting infrastructure right from the beginning. Make sure you have your applications divided up by business unit, so you can take that overall feedback and write it up when you are showing it to a senior executive, "Hey look, you are paying for infrastructure.

You are spending a million dollars more a month than you should be. I would rate this solution as an eight out of It is a great app. The only reason I wouldn't give them a higher rating is from a reporting standpoint. That's just not their focus, but better reporting would help. We use an app called Cloud Temple with them, who is actually a partner of theirs. Turbonomic will tell you reporting is not what they see as their core competency, and they are going to take actions to optimize your environment.

However, at the same time, they have done these partnerships with another company who does better reporting. We primarily use it as a cost reduction tool regarding our cloud spend in Azure , as far as performance optimization or awareness.

We use Turbonomic to identify opportunities where we can optimize our environments from a cost perspective, leveraging the utilization metrics to validate resources are right-sized correctly to avoid overprovisioning of public cloud workloads. We also use Turbonomic to identify workloads that require additional resources to avoid performance constraints.

We use the tools to assist in the orchestration of Turbonomic generated decisions so we can incorporate those decisions through automation policies, which allow us to alleviate long man-hours of having someone be available after hours or on a weekend to actually perform an action.

The decisions from those actions are scheduled in the majority of cases at a specific date and time. They are executed without having anyone standing by to click a button. Some of those automated orchestrations are performed automatically without us having to even review the decision, based on some constraints that we have configured. So, the tool identifies the resource that has a decision identified to either address a performance issue or take a cost saving optimization, then it will automatically implement that decision at the specific times that we may have defined within the business to minimize impact as much as possible.

There are some cases where we might have to take a quick look at them manually and see if it makes sense to implement that action at a specific date and time. We then place the recommendation into a schedule that orchestrates the automation so we are not tying up essential IT people to take those actions. We take these actions for our public cloud offering within Azure.

We don't use it so much for on-prem workloads. We do have it monitor our on-prem workloads, but we do not really have much of an interest in the on-prem because we're in the process of a lift and shift migration for removing all workloads in the cloud. So, we are not really doing too much with the on-prem stuff. We do use it for some migration planning and cost optimization to see what the workload would look like once we migrated into the cloud.

From our on-prem perspective, we do use it for some of the migration planning and cost planning. It provides application metrics and estimates the impact of taking a suggested action from two aspects:. 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 to the business because some of the changes may require rebooting the server. So, we don't want to reboot the server at in the afternoon when everyone is using it, but we might have a dedicated time slot that says, "After today or in the morning when no one is using it, this server can be rebooted to take the action.

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. 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.

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?

The ability to look at a workload from an actual consumption perspective for the resources that it's consuming internally is particularly valuable. For instance, when we have a server in the public cloud, we might provision a certain amount of memory resources to it and CPU, e. The tool provides the ability to look at the consumption utilization over a period of time and determine if we need to change that resource allocation based on the actual workload consumption, as opposed to how IT has configured it.

Therefore, we have come to realize that a lot of our workloads are overprovisioned, and we are spending more money in the public cloud than we need to.

This solution allows us to have the data to make business decisions without having a concern on whether we are going to be impacting the business negatively by taking the wrong action.

We actually have the analytical data to back decisions. This helps us have discussions with the business on if it's the right decision to make or not. Turbonomic has the ability to manage the full application stack. We have not plugged in all aspects of our application stacks, but it does provide that. That's one of the things that we love from Turbonomic is that we're not only ingesting the data into Turbonomic and reviewing the decisions that Turbonomic is providing, but Turbonomic is also essentially providing us a single pane of glass to implement those actions.

So, if there is an action that we would like to take, whether it is someone manually clicking a button and taking the action or the action being initiated automatically by Turbonomic, that is all taken from within the appliance. We don't have to go and log in somewhere else or log into our public cloud offering and take that action. It can all be done from a single management pane. We can look at our supply chain for a specific application or workload and see if one specific part of the solution is causing a problem, as opposed to having a bunch of people on the phone with a bridge call and having people looking at different aspects of the solution that they are more intimate with.

Turbonomic shows us the ability from a service chain perspective, how things pitch together, and helps us identify that single point or bottleneck causing the impact. We have used it from that perspective. It provides the ability for us to create customized dashboards and custom reports to help showcase info to key stakeholders.

We have leveraged the custom reporting for things, like SAP, that we have running in the public cloud to show how SAP is running, both from a performance aspect as well as from a cost perspective. There is an opportunity for improvement with some of Turbonomic's permissions internally for role-based access control. We would like the ability to come up with some customized permissions or scope permissions a bit differently than the product provides.

We are trying to get broader use of the product within our teams globally. The only thing that is kind of making it hard for a mass global adoption, "How do we provide access to Turbonomic and give people the ability to do what they need to do without impacting others that might be using Turbonomic? I also feel that that scenario that I'm describing is, in a way, somewhat unique to our organization.

It might be something that some others may run into. But, predominantly, most organizations that use or adopt Turbonomic probably don't run into the concerns or scenarios that we're trying to overcome in terms of delegating permission access to multiple teams in Turbonomic.

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