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Turbonomic Primary Use Case

Director of Enterprise Server Technology at a insurance company with 10,001+ employees

Our use case: Planning for sizing servers as we move them to the cloud. We use it as a substitute for VMware DRS. It does a much better job of leveling compute workload across an ESX cluster. We have a lot fewer issues with ready queue, etc. It is just a more sophisticated modeling tool for leveling VMs across an ESX infrastructure.

It is hosted on-prem, but we're looking at their SaaS offering for reporting. We do some reporting with Power BI on-premise, and it's deployed to servers that we have in Azure and on-prem.

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Matthew Koozer - PeerSpot reviewer
Ict Infrastructure Team Cloud Engineer at a mining and metals company with 10,001+ employees

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 don't have any other public cloud offerings, like AWS or GCP. 

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. However,& most of our implementations with this are for optimization and performance into the public cloud.

It provides application metrics and estimates the impact of taking a suggested action from two aspects: 

  1. It shows you what that impact is from the financial aspect in a public cloud offering. So, it will show you if that action will end up costing you more money or saving you money. Then, it also will show you what that action will be like from a performance and resource utilization perspective. It will tell you, "If you make the change, what that resource utilization consumption will look like from a percentage perspective, if you will be consuming more or less resources, and if you're going to have enough resource overhead for performance spikes." 
  2. It will give you the ability to forecast, but the utilization consumption's going to be in the future term. So, you can kind of gauge whether the action that you're taking now, e.g., how it's going to look and work for you in the long-term.
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David Grudek - PeerSpot reviewer
System Engineer at a financial services firm with 201-500 employees

We pretty much use it only for load balancing between hosts.

We're a payroll company and Turbonomic is really important for us from about November until March, each year, because our end-of-year processing increases our load by six to seven times. That's especially true in November and December when companies are running their last payrolls. If we're going to be losing any customers, they definitely have to finalize everything all at one shot. In addition, companies that pay out bonuses at the end of the year also have to be running all these extra payrolls. There are a slew of reasons for extra payrolls at that time of year. They may need to do some cleanup if they messed up something and didn't do so all year long. At that point, they have to do it before December 31st. And after December 31st is the beginning of tax preparation, so our systems are very heavily utilized.

It does a great job year-round, but we're in a situation where we have plenty of resources during most of the year, but at year-end, depending on how busy it gets, it can overwhelm the systems if you're not careful, depending on where a VM sits, on which host.

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Anita H - PeerSpot reviewer
AVP Global Hosting Operations at a insurance company with 10,001+ employees

We wanted the performance assurance because we have seasonal spikes in our volume. One of the use cases was making sure that we could adjust for seasonal spikes in volume. 

Another use case was taking a look at how we increase our density and make a more effective utilization of the assets that we have on the floor. 

The third use case was the planning, being able to adjust for mergers, acquisitions, divestitures, and quickly being able to separate out the infrastructure required to support that workload.

We just upgraded and are using the latest on-prem version. 

We use Turbonomic for our on-prem hosting: servers, storage, and containers. We also use it in Azure. We are trying to use it across multiple hosting environments. The networking team is not really using it. Instead, I am there from a hosting standpoint, where the main focus is on servers and storage, then the linkage to applications with the resources that they are using.

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Sam Beckett - PeerSpot reviewer
Senior Cloud Engineer at O.C. Tanner Co.

We have a hybrid cloud setup that includes some on-prem resources, and then we have AWS as our primary cloud provider. We have one or two resources on the Google Cloud Platform, but we don't target those with Turbonomic. Our company has a couple of different teams using Turbonomic. Our on-premise VMware virtualization and Windows group use Turbonomic to manage our on-prem resources. They use it to make sure that they're the correct size. 

I'm on the cloud engineering team, and I use it in a unique way. We use it for right-sizing VMs in AWS. We're using it to improve performance efficiency in our Kubernetes containers and make sure the requests are in line with what they should be. If an application has way more memory allocated than it needs, Turbonomic helps us decide to scale that back.

We have a platform that we use for our internal deployments. I use our API to get data and transform it for use in our platform. I've developed APIs that go in between our internal platform and Turbonomic. When our developers create and release code, these APIs allow them to take advantage of Turbonomic without using it directly. It's built into our platform so they can benefit from the performance improvements Turbonomic can recommend, but they don't need access to Turbonomic.

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Chris Bannoura - PeerSpot reviewer
Sr System Engineer at Liquidity Services

There have been quite a few use cases, even some that were probably unintended. 

  1. Reduce our footprint and cost. It handled that perfectly. 
  2. Handle our RI purchasing, which is what we are in the process of doing now. 
  3. Automating shutdowns and startups so we can turn machines off when they are not being used. We have several machines in this category. We are going to continue to add more to it, once we go through some finalization. We are using it to delete unattached volumes to manage databases.

The unintended use case was that we started looking at what else could we save. We realized that we had a ton of data in Blob Storage for backups. Turbonomic can't see that, but it brought it to light because we wanted to find a way to look at our overall spending. So, we have saved a bunch of money by reducing that footprint. 

It's on-prem, but we are in the process of moving into the cloud.

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Todd Winkler - PeerSpot reviewer
Principal Engineer at a insurance company with 10,001+ employees

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

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

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

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Alex Darby - PeerSpot reviewer
Director, Infrastructure, Wintel Engineering at a tech services company with 201-500 employees

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

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

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Keldric Emery - PeerSpot reviewer
Advisory System Engineer at a insurance company with 1,001-5,000 employees

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

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

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

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Infrastructure Manager at a insurance company with 501-1,000 employees

We use the Reserved Instances and the recommendations of sizing of our family types in Azure. We use it for cost optimization for our workloads there.

We started with the on-prem solution, but then we went with the SaaS model. Now, Turbonomic handles the installation and the support of the appliances.

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Server Administrator at a logistics company with 1,001-5,000 employees

The primary reason we initially got it was to help us to right-size all of our VMs, to make sure that they were the appropriate size for the amount that they were being used. That was the biggest push to get this, and we implemented it. 

We have also discovered that Turbonomic can automatically suspend virtual machines that were on a schedule. For example, in the afternoons and the evenings when a VM wasn't going to be used, it could just be shut down, so that we wouldn't be charged eight to 10 hours of compute time, per machine, that wasn't going to be used at all during that time. That's been pretty useful. 

We're also using it to help us determine the reserved instances that we need. We haven't purchased the reserved instances yet but we're using Turbonomic's suggested reserved instance purchasing algorithms to assist us in finding the right balance for the number of RIs that we want to purchase.

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Chief Information Officer at a government with 501-1,000 employees

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

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

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Ervis Charles - PeerSpot reviewer
Principal Engineer at a computer software company with 1,001-5,000 employees

It has a feature called "right-sizing". This makes sure that our virtual machines are sized properly so we don't have a lot of wasted resources, either too large or too small. This way, our machines function much better than they should.

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Advisory System Engineer at a insurance company with 1,001-5,000 employees

We're using it for placement automation. Turbonomic will look at the virtual machines that are on different hosts and it will say, "Hey, three are too many machines on this host. And this host doesn't have a lot of machines on it." It will place the virtual machines in a balanced way on different hosts and try to balance the hosts out as best it can.

We're also using it for CPU and RAM addition and automation: Do we need to add more memory or take away memory in the environment or look at a machine to see if it is being used to the best capacity?

We also use Turbonomic for planning. It takes a look at our environment and we can make plans, like if we want to put some of our environment into a cloud-based system, like Azure, it will tell us our costing.

We use it for about 4,000 machines.

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Linley Ali - PeerSpot reviewer
Head of Enterprise Wide Technical Architecture / Enterprise Technology Specialist at a healthcare company with 5,001-10,000 employees

The primary use case is to optimize our environment. We will take our OpenShift environment and use Turbonomic to monitor the size of the pods, then determine where to place the pods as well. We will make recommendations from that perspective. Turbonomic is an excellent product as far as we are concerned for managing the pod sizes and determining the best sizing for those pods. Right now, our development staff prefer to maximize the size of their pods and requests in terms of memory and CPU, and that causes us to potentially run out of resources.

We are managing the pods, their performance, and the utilization. It is more of a pod deployment model. Right now, we are monitoring the whole application as well as its allocation of resources, CPU, memory, etc. So, the application will be optimized and Turbonomic will help us optimize that sizing, because that is a problem right now.

We will be deploying this solution across all our OpenShift platforms to manage our existing environment.

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Ryan Mahon - PeerSpot reviewer
Team Lead, Systems Engineering at a healthcare company with 5,001-10,000 employees

We do vMotion through VMware. We let Turbonomic control our vMotion. We do server rightsizing and capacity management with it.

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Operations Engineer at a government with 5,001-10,000 employees

I'm using this solution to get performance stats outside of my vCenter environment.

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Richard-Romeo - PeerSpot reviewer
Sr. Cloud Architect at a computer software company with 10,001+ employees

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

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

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reviewer1550322 - PeerSpot reviewer
User at a computer software company with 201-500 employees

We looked to this product to help us to right-size our virtual machines and containers. Most people who request virtual machines tend to request more resources than they need, and most of the time it's hard to prove that they don't.

Our environment is entirely on-premises. We have virtual machines and Kubernetes running on some of those VMs. We also have plans to go to the cloud with some workloads in the future, so it's good to have this tool to help get the sizing just right when the time comes to pull the plug.

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Tjeerd Saijoen - PeerSpot reviewer
CEO at Rufusforyou

We implemented this solution in our company and we also implement it for our clients. We use it because it connects to monitoring tools over APIs and if you have a monitoring solution, it removes data intelligently. Our aim is to optimize our customers' systems. The solution also offers insight into the financial impact of an event. We are partners with IBM which purchased Turbonomic earlier this year, and we are resellers of Turbonomic. I'm the company CEO/CIO. 

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Chris Childerhose - PeerSpot reviewer
Lead Infrastructure Architect at ThinkON

Turbonomic keeps our cluster balanced and VMs running optimally. It shows us where in our environment that resources can be recovered as well as when extra is needed.

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Buyer's Guide
June 2022
Learn what your peers think about Turbonomic. Get advice and tips from experienced pros sharing their opinions. Updated: June 2022.
610,190 professionals have used our research since 2012.