IBM Turbonomic OverviewUNIXBusinessApplication

IBM Turbonomic is the #1 ranked solution in top Cloud Analytics tools, #1 ranked solution in top Cloud Cost Management tools, #2 ranked solution in top Cloud Migration tools, #2 ranked solution in top Virtualization Management Tools, and #3 ranked solution in top Cloud Management tools. PeerSpot users give IBM Turbonomic an average rating of 8.8 out of 10. IBM Turbonomic is most commonly compared to VMware Aria Operations: IBM Turbonomic vs VMware Aria Operations. IBM Turbonomic is popular among the large enterprise segment, accounting for 67% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a computer software company, accounting for 25% of all views.
IBM Turbonomic Buyer's Guide

Download the IBM Turbonomic Buyer's Guide including reviews and more. Updated: January 2023

What is IBM Turbonomic?

IBM Turbonomic Application Resource Management (ARM) software is used by customers to assure application performance while eliminating inefficiencies by dynamically resourcing applications across hybrid and multicloud environments. Turbonomic customers report an average 33% reduction in cloud and infrastructure waste without impacting application performance, and return-on-investment of 471% over three years.

For further information, please visit www.ibm.com/cloud/turbonomic

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IBM Turbonomic was previously known as Turbonomic, VMTurbo Operations Manager.

IBM Turbonomic Customers

J.B. Hunt, BBC, The Capita Group, SulAmerica, Rabobank, PROS, ThinkON, O.C. Tanner Co.

IBM Turbonomic Video

IBM Turbonomic Pricing Advice

What users are saying about IBM Turbonomic pricing:
  • "In the last year, Turbonomic has reduced our cloud costs by $94,000."
  • "I don't know the current prices, but I like how the licensing is based on the number of instances instead of sockets, clusters, or cores. We have some VMs that are so heavy I can only fit four on one server. It's not cost-effective if we have to pay more for those. When I move around a VM SQL box with 30 cores and a half-terabyte of RAM, I'm not paying for an entire socket and cores where people assume you have at least 10 or 20 VMs on that socket for that pricing."
  • "The pricing is in line with the other solutions that we have. It's not a bargain software, nor is it overly expensive."
  • "The product is fairly priced right now. Given its capabilities, it is excellently priced. We think that the product will become self-funding because we will be able to maximize our resources, which will help us from a capacity perspective. That should save us money in the long run."
  • IBM Turbonomic Reviews

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    Ict Infrastructure Team Cloud Engineer at a mining and metals company with 10,001+ employees
    Real User
    Provides recommendations whether workloads should be scaled up or down
    Pros and Cons
    • "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."
    • "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."

    What is our primary use case?

    We primarily use it as a cost reduction tool regarding our cloud spending 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 takes 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 the 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 on-prem. 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 use it for some of the migration planning and cost planning. However, most of our implementations with this are for optimization and performance in 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 of 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 when you make the change, what that resource utilization consumption will look like from a percentage perspective, if you will be consuming more or fewer 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 is going to look and work for you in the long term.

    How has it helped my organization?

    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.

    What is most valuable?

    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.g., two processors and 24GB of memory. 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.

    What needs improvement?

    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?" because we have a shared appliance. 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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    For how long have I used the solution?

    It has been somewhere between two and a half to three years since we started our relationship with them.

    What do I think about the stability of the solution?

    The stability is very good. We have not had to open up any support tickets for the product to troubleshoot or recover the appliance. It has been running just fine. We haven't had to redeploy or recover anything with it, surprisingly, in the two and a half years that we have had it. The code updates are pretty easy to perform as well. Ongoing maintenance is really simple, and our account team helps us with the code updates. They get a meeting invite together, then it is less than a whole 10 minutes, but they are there every step of the way.

    What do I think about the scalability of the solution?

    It is pretty scalable, in terms of any concerns that we would have. Right now, we are using on-prem appliances. However, if we needed to, they have the ability of pouring into a SaaS-based offering, which would help us adopt it faster, in terms of some of our sister companies, because we are not isolated to network access within this particular data center. We could leverage the same licensing from a SaaS perspective, then they wouldn't have to use a VPN to connect to the appliance to use it. 

    There are situations from a scalability perspective where we have to take into account things like GDPR. For things where GDPR or data sovereignty come into play, the scalability becomes a bit of a concern because you can only keep the appliance within that specific region. You need separate instances of Turbonomic, but the team has the ability to allow us to tackle that from a licensing perspective. This is a pretty minimal concern. We tackle GDPR or data sovereignty from the perspective that we just apply an instance of Turbonomic within that specific country region.

    How are customer service and support?

    If we have any questions or concerns, the account team as well as the product support team are always there and very accommodating to help us. With any problems that we have, even if they are not built into the product, we have worked with them to give them feedback on the product and on how we would like it to work. They have worked with us to help import some of that functionality into the product so it is available, not just for us, but for other customers who use the product as well.

    How would you rate customer service and support?

    Positive

    How was the initial setup?

    The initial setup was relatively straightforward. It was a pretty easy setup. I wouldn't say it was any more difficult than any other tool that we set up or have used in our environment. It is pretty easy to deploy, then probably just as easy to configure once it was deployed.

    What was our ROI?

    It helps us gauge our return on investment for the purchase of Turbonomic, based on the overall actions that we've taken and how much money we have saved by taking those actions over a period of time.

    In the last year, Turbonomic has reduced our cloud costs by $94,000. It has identified a lot more cost saving areas, but we haven't taken advantage of those.

    The amount of tickets that we have had come in for performance issues has surmounted to almost nothing in the calendar year. I don't know what we had before, but now in a calendar year, it is less than 10 to 12 tickets a year for a performance issue.

    It has definitely provided a huge benefit in the area of man-hours saved. Without the tool, we would be flying blind on that and would probably be spending a lot of man-hours trying to formulate in-house strategies on how to reduce costs. Our company is a very lean company, in terms of headcount for IT resources as well as cloud skillset awareness. Having a tool like Turbonomic has allowed us to adopt and implement strategies like this, like cost saving measures with the public cloud, probably making us exponentially faster than we could have been without them.

    When we had hit on how it ingests the workload performance data to help provide performance-driven analysis or recommendations to provide a recommendation for whether a workload should be scaled up or down, one of the things that has been kind of like a side effect to the ingestion of this data and the business decisions coming out of Turbonomic is it has been helping us identify workloads which are really not being used at all. From identifying those workloads that are not being used, we are able to go through our lifecycle management faster and more efficiently than we would have in the past. We have been able to decommission servers, essentially deleting them from our public cloud and completely reducing the operational cost of that workload altogether. So, it is not just ensuring that the VM is right-sized or locking in a commitment, but identifying that the workload is so low to utilize.

    We are able to go back to the business and having a discussion with them based on the utilization of that VM over the course of a period of time for the data that we have, then have the justification and communication with the business to say, "Yeah, it doesn't make sense to have this workload in the environment anymore. Let's delete it." or, "Yeah, it's something that isn't used it all. Let's go ahead and delete it." It is allowing us to identify areas to save cost in those areas, but it's also helping us say, "This workload is costing us this much money. Is it really worth spending this much money every month or so for this solution that is running in the public cloud? Is it generating enough revenue for the business to warrant the run rate? Is the solution providing a service to the business that justifies the operational consumption on a monthly basis?" We are able to have these internal discussions within the business based on the data that Turbonomic is providing. This is a side effect of the product because the product is not providing these decisions and implementing them, but the product is providing us the data to have these discussions and net these decisions as an outcome. Then, this ends up saving money in our public cloud offering.

    Which other solutions did I evaluate?

    We did try some other solutions as PoCs before we worked with Turbonomic. Unfortunately, I am not aware of who those companies were because that was before I came onboard with the team. The big thing that it always came down to was whether we were going to adopt the entire implementation setup and configuration aspect. For example:

    • How much work was it going to take to deploy the appliance? 
    • How many man-hours would it take to configure it? 
    • What the continuous configuration and management was going to be?
    • Was it really saving us time and money in the long run?

    Other solutions always fell flat because of how much involvement it would require from IT to deploy and work it, but also because of the ongoing configuration and maintenance of the appliance.

    What other advice do I have?

    It doesn't pick up the entire supply chain automatically. It requires minimal effort in configuration. We have to show a relationship in a sense that this workload is associated with another workload. However, once that relationship is established, the solution helps us manage our business-critical applications by understanding the underlying supply chain of resources.

    Our capital expenses are relatively flat. We are not purchasing any new equipment. We are actually in a consolidation process. Everything is getting moved to the public cloud. From an operational perspective, with our workloads being in the public cloud, it has provided us:

    1. The ability to identify what we have running in the public cloud and how much it will actually cost us. 
    2. How we can reduce public cloud operational costs, e.g., what actions can we do to help reduce operational expenses in the public cloud? 

    It identifies areas where we can delete storage that is not being used. We can address right-sizing workloads that are overprovisioned in the public cloud as well as logging in long-term commitments with workloads in the public cloud and saving on incidents, on average for us, over 33% or higher for our workloads, as opposed to just paying the pay as you go hourly rate with the provider.

    Try to look at things, not just from a cost savings perspective, but also from performance avoidance. We looked at: How do we quantify our spend in the public cloud and how do we avoid our spend in the public cloud? But we always forgot that there were workloads out there that do have performance impacts. So, we counted this as a cost savings and cost optimization tool, but it became so much more than that. 

    We developed a crawl, walk, run approach. We took some workloads in our public cloud and looked at the business decisions. We took the decisions, then we tested to see what the outcomes were with them. As we went through those actions manually, gained the confidence on how those actions were being made, and what the post impact of that was, that allowed the business to become more confident in the tool. We no longer needed to have meetings to discuss why we were doing what we were doing.

    It then became a point of communication. An action would be taken because Turbonomic said it was the right thing to do. Nowadays, it's not even questioned. When I talked to people about trying out Turbonomic and looking at how to adopt it in their workload, I say to look at areas which are current pain points in your environment and see where Turbonomic would fit into that instead of trying to come up with the workloads or use cases to plug into Turbonomic. Instead of trying to figure out what you have or seeing where you could put Turbonomic in your environment, see where your environment fits into Turbonomic. That was the way that we were able to drive adoption much faster and use it, not just as a reporting tool, but also as an orchestration tool as well.

    They have some room to grow. I wouldn't give them a perfect 10. I would probably give them an eight and a half or nine (as a whole number).

    Which deployment model are you using for this solution?

    On-premises
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    Senior Systems Engineer at a university with 1,001-5,000 employees
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    The solution reduced our operational expenditures and is able to identify points before we even noticed them
    Pros and Cons
    • "I like Turbonomic's built-in reporting. It provides a ton of information out of the box, so I don't have to build panels for the monthly summaries and other reports I need to present to management. We get better performance and bottleneck reporting from this than we do from our older EMC software."
    • "The management interface seems to be designed for high-resolution screens. Somebody with a smaller-resolution screen might not like the web interface. I run a 4K monitor on it, so everything fits on the screen. With a lower resolution like 1080, you need to scroll a lot. Everything is in smaller windows. It doesn't seem to be designed for smaller screens."

    What is our primary use case?

    We use Turbonomic to evaluate all of our virtualized clusters. Initially, we were only using Turbonomic for our long-term VMware stacks. Now we are monitoring VMware ESXi 7 and Nutanix AHV stacks. On the server side, we have 400 VMs. We don't evaluate the VDI side because we have 1,100 seats, so it's too expensive. We made a special contract on ELA for vRealize Ops for VDI on that side. It wasn't horrible. It's just the bare minimum to show us if there's a problem in the stack.

    We mainly use Turbonomic as a heat map, but we aren't drilling down into the performance of individual applications like Kubernetes. That's Docker or Swarm, but we use other tools to monitor the transaction levels, etc., instead of Turbonomic.

    Turbonomic is our overall heat map in our NOC. We fire it up, and when we see a red flag, we dig into it, and off we go, but the basic application components do not have our Dockers linked to them. It's just mainly working on the surface of the virtualization stack itself.

    Our infrastructure is solid enough that I get a VDI call about every three weeks. My server farms are built like tanks, so it takes a lot to take them down. We can sleep well at night. Everything is on-prem. The only cloud solutions we use at the college are SaaS systems. We don't put much in the cloud because cloud environments are too vulnerable to hacks and exploits. 

    We're going from a silo system to HCI — from 450 hard disks to hybrid flash. While we undergo a significant infrastructure change, we're using Turbonomic to watch VMware because it has aged, and our migration isn't happening the way we want. We will probably reevaluate when the next contract is up for Turbonomic instead.

    Once we switch to pure Nutanix, we will reevaluate Turbonomic. I will probably keep it because management is used to Turbonomic's reporting. That saves me much OPEX time building those reports out of Nutanix by hand. I've been here for 16 years, and my CIO has been here for 17 years. They're used to the reports we've been developing over the last decade. We developed them using VMTurbo. We set the standard with that first tool for reporting.

    We use Nutanix Prism Central to manage everything on the Nutanix side, but Turbonomic provides ancillary information that gives me a holistic view of reporting and more features that Prism Central doesn't cover. Turbonomic provides linkages, visual aids, graphs, charts, etc. 

    I'm the one who uses it. It's up on my NOC screen. We log and monitor it pretty much every day. Then, once a month, it generates reports on its own. In that sense, it's used daily or monitored daily. We watch what it's reporting every day on the heat map. Regarding issues and such, maybe every couple of weeks we have something pop up that we look at. 

    How has it helped my organization?

    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.

    What is most valuable?

    I like Turbonomic's built-in reporting. It provides a ton of information out of the box, so I don't have to build panels for the monthly summaries and other reports I need to present to management. We get better performance and bottleneck reporting from this than we do from our older EMC software.

    We look at the resizing recommendations in the reports, but we don't follow all of them because we know the ebb and flow of our systems. It shows us the storage array evaluations for our storage devices. We have some older primary channel VNX systems. 

    What needs improvement?

    The management interface seems to be designed for high-resolution screens. Somebody with a smaller-resolution screen might not like the web interface. I run a 4K monitor on it, so everything fits on the screen. With a lower resolution like 1080, you need to scroll a lot. Everything is in smaller windows. It doesn't seem to be designed for smaller screens.

    When I change the resolution to 1080, I only see half of what I would on my big 4K monitor. It would be annoying to have to scroll to see the flow chart. They have a flow chart that goes top to bottom like a tree. On a lower resolution, it might be nice if that scrolls horizontally because it's long, narrow, and tall. It's only three icons wide, but it's 15 icons tall. I think it would be helpful to have the ability to change that for a smaller screen and customize the widget.

    For how long have I used the solution?

    We've been on Turbonomic since version 2. 

    What do I think about the stability of the solution?

    I haven't had it fail, especially with the 8.X line. Other users report bugs, but we've never encountered any of those issues in our own implementation. Once, I didn't patch it for a year, and it kept running. No Windows system can be up for 365 days and not need a reboot. This solution is rock solid.

    What do I think about the scalability of the solution?

    We scaled Turbonomic up but not out. We didn't try to add more nodes of Turbonomic, but we increased the size of the current VM.

    How are customer service and support?

    I rate IBM support a nine out of ten. I haven't talked to the head engineer for Turbonomic in nine years because he moved up, and they got a real support tier going. I contact their support probably once or twice a year. They typically solve the issue within an hour.

    Nobody is ever perfect. Perfect is when they call me to let me know there is a problem before I realize it. That's my old life at Hewlett-Packard, but I don't want to talk about what that support contract costs.

    How would you rate customer service and support?

    Positive

    How was the initial setup?

    Setting up Turbonomic is pretty straightforward if you take it slowly. If you assume you know the answer and click "next" automatically, you will run into an issue here or there. You must properly set up your permissions in the vCenter and Nutanix before you install. I always make a Turbonomic-specific local ID so it can't be used anywhere else.

    It's a nice security practice using a local account for Nutanix and one for vCenter to connect proper permissions. After the prerequisites are in place, it is relatively straightforward. It used to be pretty cumbersome for the licensing. I haven't done a fresh installation since 8.1. It wasn't as simple before 8.1, and it seems like they've streamlined it even more in 8.5. I don't think you'll face any challenges if you follow the instructions and set up the accounts it needs to connect to from the appliance ahead of time.

    It took about 15 minutes to configure Turbonomic for Nutanix because I connected through Prism Central. That includes verification and making sure the data is coming in. For VMware, it took no more than 10 minutes per vCenter that I added. I spent probably half an hour reading instructions to ensure everything was right before I started.

    What about the implementation team?

    I've been doing this for so long. We've been doing VMware since 2.X. It was all done on-premise. We had support back in the day if there was an implementation problem. We had support on the phone with us until it was resolved. We had more problems back when it was still called VMTurbo. When I called support, I would get a senior engineer who actually wrote code for VMTurbo instead of a support desk. 

    What was our ROI?

    The ROI for us is a reduction in operating expenditures. We fix problems before they become issues that our clients see. I don't need to spend an hour a month putting together reports for upper management. We've identified the canned reports they'd like to see and Turbonomic builds them in PDF files. I'm still working 50-60 hours a week, but that's not 51 and 62.

    What's my experience with pricing, setup cost, and licensing?

    I don't know the current prices, but I like how the licensing is based on the number of instances instead of sockets, clusters, or cores. We have some VMs that are so heavy I can only fit four on one server. It's not cost-effective if we have to pay more for those. When I move around a VM SQL box with 30 cores and a half-terabyte of RAM, I'm not paying for an entire socket and cores where people assume I have at least 10 or 20 VMs on that socket for that pricing.

    We're not in the cloud, so we pay per VM. I have the license set at $500. We have around 400 VMs. I don't have to go over the price break at $500 that we got. We're a public institution, so I can't talk about the exact cost, but I can talk about strategy. We discovered that the one VM at $500 was better than getting four plus a couple of 10 packs. It was better for us to go ahead and call 500 in and use that as our leverage to bring the cost down.

    Which other solutions did I evaluate?

    We evaluated VMware, vRealize, and Gotti. At the time, Turbonomic was called VMTurbo. We chose VMTurbo because it was the best fit. Gotti didn't do enough, and vRealize was way out of our price range. They later changed their price structure, but we stayed with Turbonomic.

    What other advice do I have?

    I rate IBM Turbonomic a nine out of ten. Before implementing Turbonomic, you should do your research. Check the documentation to see if Turbonomic's processes make sense for what you're doing and if your current setup will handle all the different aspects of Turbonomic. If your current solution does 85% of what you need, and Turbonomic does 87%, I don't think that's enough to switch products. If your solution meets 80% of your need, and Turbonomic does 98%, why wouldn't you change?

    What do you need to do? I can flip a quarter or half-dollars instead of quarters. If all you're doing is flipping dimes, do you need something that flips half-dollars? I'm frugal. I worked for a 501(c)3 nonprofit most of my life before I came to this college.

    I look for bang for my buck and stability. I used to describe to other system admins that I may not have the flashiest new Volvo turbo diesel truck that goes up the hills. My Peterbilt with a CAT diesel may smoke and have a little rust on it, but in the middle of a subzero blizzard, it's making that hill while yours is gelled up at the bottom.

    Take a long, hard look at the pre-generated reports and how it holistically checks your system from top to bottom through the tree to see if that's a good fit for you. You can't change that tree. If the homepage tree doesn't work for you, then Turbonomic won't work.

    There's not much I know you can do to change that. If that tree makes sense to you, then look at the reporting. Look at how it evaluates load balancing based on shares instead of just the overall weight that VMware does. Turbonomic uses market shares.

    They turn it into a cost market share to help adjust. It will tell you if a CPU load is heavy. It will give you recommendations to adjust the size. We're not going to move it right away because what is mission-critical is over here, and we don't want to impact that. VMware looks at how heavily the CPU is being utilized in the VM and says, "Well, I'm going to slap that over here," arbitrarily.

    Turbonomic has a share you set up. Think of it like stock market shares. That share went up, but it's not a blue-chip stock. We try to move it over to where the blue chip stocks would take a hit. We move it someplace that's a lesser value, so to speak, once machines are of lesser value.

    Which deployment model are you using for this solution?

    On-premises
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    Buyer's Guide
    IBM Turbonomic
    January 2023
    Learn what your peers think about IBM Turbonomic. Get advice and tips from experienced pros sharing their opinions. Updated: January 2023.
    670,523 professionals have used our research since 2012.
    Senior Cloud Engineer at O.C. Tanner Co.
    Real User
    Top 20Leaderboard
    The cost savings is significant, especially with our AWS computing
    Pros and Cons
    • "Turbonomic can show us if we're not using some of our storage volumes efficiently in AWS. For example, if we've over-provisioned one of our virtual machines to have dedicated IOPs that it doesn't need, Turbonomic will detect that and tell us."
    • "The deployment process is a little tricky. It wasn't hard for me because I have pretty in-depth knowledge of Kubernetes, and their software runs on Kubernetes. To deploy it or upgrade it, you have to be able to follow steps and use the Kubernetes command line, or you'll need someone to come in and do it for you."

    What is our primary use case?

    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.

    How has it helped my organization?

    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.

    What is most valuable?

    Turbonomic can show us if we're not using some of our storage volumes efficiently in AWS. For example, if we've over-provisioned one of our virtual machines to have dedicated IOPs that it doesn't need, Turbonomic will detect that and tell us. You can save like a thousand bucks a month by switching the storage class. With a click of a button, it automatically makes the changes for you, and you can go in and save a ton of money on AWS with it. That's one of the primary ways I've used it. 

    Kubernetes integration is excellent. Turbonomic helps us right-size deployments and replica sets. They've come a long way since I started here. I've been working with the team that uses Kubernetes or develops the Kubernetes integration, and it's been fantastic. Turbonomic helps prevent resource starvation too. Inside the console, there's a little graph that tells you what your application has been doing over the last week. You know that you need to take action right now before you run out of CPU or memory and your application starts to suffer. 

    With Turbonomic, you have everything in one place. There aren't a bunch of different things to worry about or manage. It helps you manage full-stack applications as well. It's a challenge for many of our developers to understand what resources their application needs. We can automate that. Turbonomic processes all of the data, makes intelligent decisions, and automatically applies changes to the application. These are problems that are difficult for humans to solve because of the complexity of taking into account all these variables and determining how much memory to give an application. If you don't make the right decision, Turbonomic can discover that for you and fix it.

    You can automate all of these functions. It tracks your application performance, and you can automate everything or have it wait for your input. It'll do it in real-time asynchronously in the background. Turbonomic can predict the impact of any given action, and that's one of the things I like about it. There's a little graph that pops up when you're about to do something. It shows you the history and predicts the future impact of what will happen when you click the button. For example, it can tell you that your utilization of the resource allocation will drop by this much, and you're going to be at about X percent utilization.

    It's reasonably accurate. I haven't had a situation where it told me that everything would be okay, but it didn't work when I applied the change. So far, everything has been smooth sailing. Turbonomic can tell you how everything is currently performing, but we use other tools for that kind of monitoring. It can show you how your system is currently acting. If some things don't need action at the moment, it will tell you why. For example, it'll say you have this much memory allocated, and you're right on target, so you don't need to do anything. 

    It's harder to use a monitoring tool to understand how your application performs over time. It depends on the monitoring tool, but often you have to set it up to ingest all this data and pick the right things to look at. Turbonomic does all that for you in the background. You can look at a suggestion, for example, if you need to up your memory allocation by a certain amount — and see all the data Turbonomic has gathered to make that decision. With a standard monitoring tool, you have to make that decision yourself. You're the one ingesting all the data. 

    A monitoring tool is probably better if I want to see what my application is doing right this instant. As far as thresholds go, I think that's something I would probably use monitoring tools for. I would set it up to alert me when my resource allocation or memory usage exceeds 80 percent. I haven't used Turbonomic to do things like that. It's more forward-looking. When something is happening, like my application is running low on startup resources, I'll hop on a Turbonomic to see if there's a solution that I should apply. 

    What needs improvement?

    It's tough to say how they could improve. They've done a lot better with their Kubernetes integration. If you'd asked me a year and a half ago, I would say that I think their Kubernetes integration needs work. They started with more of a focus on on-prem VMware virtual machines. I think it was called VMTurbo at one point. Their main goal was to help you with these virtual machines. 

    Now they've pivoted to also supporting containers, cloud-native tools, and cloud resources. At first, it was a little hard because they had this terminology that didn't translate to cloud-native applications for the way that Kubernetes deploy things versus a virtual machine. 

    I was left wondering if this was a Kubernetes resource but now, it's come a long way. I think they've improved our UX as far as Kubernetes goes. I'm interested in seeing what they do in the future and how they progress with future Kubernetes integration. I would say that's something they've improved on a lot. 

    For how long have I used the solution?

    I've been at my current company for a little over three years, and I believe we started looking into Turbonomic around that time. I would say I've been using it for two to three years.

    What do I think about the stability of the solution?

    I have never had Turbonomic go down or had a problem with it not being available when I need it, so I would say stability is great.

    What do I think about the scalability of the solution?

    I've never had an issue where I would need to scale Turbonomic to handle more resources. Knowing what I know about how the solution is deployed, I would say it's scalable since it's built on Kubernetes. You can install the Kubernetes cluster and scale up instantly. Turbonomic has a micro-service architecture, so it appears to be scalable on the backend. I would say it's very scalable, but I haven't had any direct experience with scaling it myself. 

    We're using it fairly extensively, but we don't have a ton of people working with it right now. Every relevant team uses it, including my team, cloud engineering, storage, and networking groups. In total, that's around 10 or 15 people using it. We are planning to increase usage. We're working on some new applications for Turbonomic, like integrating some of the data from Turbonomic into our platform as a service. 

    I've also worked with some of their engineers on this. It's not necessarily things that I wouldn't figure out on my own, but they've helped to smooth the process along. Every once in a while, one of my contacts at Turbonomic lets us know a new feature is coming and ask us if we want to beta test it. We install it, update to the beta version, then go through and take a look. Some of those things would be cool, like a scaling solution with Istio, a Kubernetes load balancer service mesh tool.

    I want to delve into scaling applications horizontally with Turbonomic based on response times and things like that. It would be nice to be able to automate more actions. Right now, I've integrated this into our platform, but in the future, we want to automate some of this more, especially for non-production resources. For example, if a developer decides to spin up a development application using way too many resources, we can automatically scale that down. That's the problem Turbonomic is trying to solve. It's tough to know how much you need. 

    How are customer service and support?

    I rate Turbonomic support eight out of 10. Their support team has been good. We haven't had many problems, but when we do, they respond quickly. Whenever I've had to reach out for anything, they've been super-responsive, and they'll hop on Zoom call if we need them to troubleshoot something. 

    How would you rate customer service and support?

    Positive

    How was the initial setup?

    The deployment process is a little tricky. It wasn't hard for me because I have pretty in-depth knowledge of Kubernetes, and their software runs on Kubernetes. To deploy it or upgrade it, you have to be able to follow steps and use the Kubernetes command line, or you'll need someone to come in and do it for you. We're deploying it to use with our OVA in our VMware environment on-premise, which is a little rough. It's not terrible, and I've had way worse software vendors, but I would say there's probably a little bit of room for improvement as far as upgrades go. We have to schedule a window and then make sure everything's working. With other on-prem services, you just run one command, and everything updates for you. Turbonomic upgrades are a little more involved.

    When the guy on our side was going through the install process and setting all of this up, he had to get into the virtual machine environment and do a bunch of stuff, download some things, and then start running scripts. On top of that, he was trying to run these Kubernetes controls, and this other guy was helping install them. So it felt a little more clunky. I don't know how you would improve that unless it was a complete software solution service or a simple installer that you download and run.

    The total deployment time depends on some different factors. We've deployed Turbonomic a couple of times. When they come out with a new version, we have to do a complete redeployment. I wasn't involved in the initial setup, so it's hard for me to say. But it took a couple of days to deploy the new version, plus a couple of hour-long sessions. It was around 15 hours total. I remember we tried to download a file, and it took two hours. I think that was because of the internet connection on our side. It's hard for me to quantify it. 

    What was our ROI?

    We've seen a great return on investment. Then again, I'm not sure how much we initially paid for it anyway, but we went through renegotiation. I don't have the numbers, but we bought some additional licenses, so we just expanded our use a little bit two or three weeks ago. I'd say that we got a good return on our investment, and we're excited about expanding our use in the future too. 

    It has reduced our capital and operational expenditures. It's hard to estimate it, but the cloud savings have been significant. I can't give a percentage. However, there have been multiple times when I've applied something, and it has cut a considerable portion of our monthly spending on AWS — over 5 percent. Sometimes it's just a little, but all of those actions add up over time. If I apply a bunch of changes at once, it can add up. I can say we reduced 5 percent of our monthly spending just once, and that was pretty huge for us because we spent a ton on AWS resources. That was one time I can remember, but I'm sure it's been more than that, especially our other teams using it. We've also seen some savings in human resources costs, especially on the other team. They're not dealing with alarms going off all day anymore.

    What other advice do I have?

    I rate Turbonomic 10 out of 10. For anyone thinking about implementing Turbonomic, I would suggest having someone familiar with Kubernetes — the more familiar, the better. You need someone who knows how to run a Kubernetes command to see what's happening with the state of the Turbonomic deployment if necessary. If you've got someone who knows how to use Kubernetes, include them in the deployment process.

    Which deployment model are you using for this solution?

    On-premises
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    PeerSpot user
    Alex Darby - PeerSpot reviewer
    Director, Infrastructure, Wintel Engineering at a insurance company with 5,001-10,000 employees
    Real User
    Top 20Leaderboard
    Saves time during workload migration, facilitates sizing of virtual servers, and the support team is helpful
    Pros and Cons
    • "We can manage multiple environments using a single pane of glass, which is something that I really like."
    • "The reporting needs to be improved. It's important for us to know and be able to look back on what happened and why certain decisions were made, and we want to use a custom report for this."

    What is our primary use case?

    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.

    How has it helped my organization?

    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.

    What is most valuable?

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

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

    What needs improvement?

    The reporting needs to be improved. It's important for us to know and be able to look back on what happened and why certain decisions were made, and we want to use a custom report for this.

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

    For how long have I used the solution?

    I have been working with Turbonomic for approximately five years.

    What do I think about the stability of the solution?

    This is definitely a stable solution. 

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

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

    What do I think about the scalability of the solution?

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

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

    We have approximately 12 users.

    How are customer service and support?

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

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

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

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

    Which solution did I use previously and why did I switch?

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

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

    How was the initial setup?

    The initial setup was fairly straightforward.

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

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

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

    What about the implementation team?

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

    We deployed it ourselves but received assistance directly from Turbonomic.

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

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

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

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

    What was our ROI?

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

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

    Which other solutions did I evaluate?

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

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

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

    What other advice do I have?

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

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

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

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

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

    I would rate this solution an eight out of ten.

    Which deployment model are you using for this solution?

    On-premises
    Disclosure: PeerSpot contacted the reviewer to collect the review and to validate authenticity. The reviewer was referred by the vendor, but the review is not subject to editing or approval by the vendor.
    PeerSpot user
    Keldric Emery - PeerSpot reviewer
    Advisory System Engineer at a insurance company with 1,001-5,000 employees
    Video Review
    Real User
    Top 20Leaderboard
    Saves time and costs while reducing performance degradation
    Pros and Cons
    • "We've saved hundreds of hours. Most of the time those hours would have to be after hours as well, which are more valuable to me as that's my personal time."
    • "The way it handles updates needs to be improved."

    What is our primary use case?

    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. 

    How has it helped my organization?

    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.

    What is most valuable?

    It's been a very good solution. The reporting has been very, very valuable as, with a very large environment, it's very hard to get your hands on the environment. Turbonomic does that work for you and really shows you where some of the cost savings can be done. It also helps you with the reporting side. Me being able to see that this machine hasn't been used for a very long time, or seeing that a machine is overused and that it might need more RAM or CPU, et cetera, helps me understand my infrastructure. The cost savings are drastic in the cloud feature in Azure and in AWS. In some of those other areas, I'm able to see what we're using, what we're not using, and how we can change to better fit what we have.

    It gives us the ability for applications and teams to see the hardware and how it's being used versus how they've been told it's being used. The reporting really helps with that. It shows which application is really using how many resources or the least amount of resources. Some of the gaps between an infrastructure person like myself and an application are filled. It allows us to come to terms by seeing the raw data.

    This aspect is very important. In the past, it was me saying "I don't think that this application is using that many resources" or "I think this needs more resources." I now have concrete evidence as well as reporting and some different analytics that I can show. It gives me the evidence that I would need to show my application owners proof of what I'm talking about.

    In terms of the downtime, meantime, and resolution that Turbonomic has been able to show in reports, it has given me an idea of things before things happen. That is important as I would really like to see a machine that needs resources, and get resources to it before we have a problem where we have contention and aspects of that nature. It's been helpful in that regard.

    Turbonomic has helped us understand where performance risks exist. Turbonomic looks at my environment and at the servers and even at the different hosts and how they're handling traffic and the number of machines that are on them. I can analyze it and it can show me which server or which host needs resources, CPU, or RAM. Even in Azure, in the cloud, I'm able to see which resources are not being used to full capacity and understand where I could scale down some in order to save cost. 

    It is very, very helpful in assessing performance risk by navigating underlying causes and actions. The reason why it's helpful is because if there's a machine that's overrunning the CPU, I can run reports every week to get an idea of machines that would need CPU, RAM, or additional resources. Those resources could be added by Turbonomic - not so much by me - on a scheduled basis. I personally don't have to do it. It actually gives me a little bit of my life back. It helps me to get resources added without me physically having to touch each and every resource myself.

    Turbonomic has helped to reduce performance degradation in the same way as it's able to see the resources and see what it needs and add them before a problem occurs. It follows the trends. It sees the trends of what's happening and it's able to add or take away those resources.

    For example, we discuss when we need to do certain disaster recovery tests. Over the years, Turbo will be able to see, for example, around this time of year that certain people ramp up certain resources in an environment, and then it will add the resources as required. Another time of year, it will realize these resources are not being used as much, and it takes those resources away. In this way, it saves money and time while letting us know where we are.

    We've saved a great deal of time using this product when I consider how I'd have to multiply myself and people like me who would have to add resources to devices or take resources away. We've saved hundreds of hours. Most of the time those hours would have to be after hours as well, which are more valuable to me as that's my personal time.

    Those saved hours are across months, not years. I would consider the number of resources that Turbonomic is adding and taking away and the placement (if I had to do it all myself) would end up being hundreds of hours monthly that would be added without the help of Turbonomic. 

    It helps us to meet SLAs mainly due to the fact that we're able to keep the servers going and to keep the servers in an environment, to keep them to where (if we need to add resources) we can add them at any given time. It will keep our SLAs where they need to be. If we were to have downtime due to the fact that we had to add resources or take resources away and it was an emergency, then that would prevent us from meeting our SLAs.

    We also use it to monitor Azure and to monitor our machines in terms of the resources that are out there and the cost involved. In a lot of cases, it does a better job of giving us cost information than Azure itself does. We're able to see the cost per machine. We're able to see the unattached volume and storage that we are paying for. It gives us a great level of insight. 

    Turbonomic gives us the time to be able to focus on innovation and ongoing modernization. Some of the tasks that it does are tasks that I would not necessarily have to do. It's very helpful in that I know that the resources are there where they need to be and it gives me an idea of what changes need to be made or what suggestions it's making. Even if I don't take them, I'm able to get a good idea of some best practices through Turbonomic.

    One of the ways that Turbonomic does to help bring new resources to market is that we are now able to see the resources (or at least monitor the resources) before they get out to the general public within our environment. 

    We saw immediate value from the product in the test environment. We set it up in a small test environment and we started with just placement and we could tell that the placement was being handled more efficiently than what VMware was doing. There was value for us in placement alone. Then, after we left the placement, we began to look at the resources and there were resources. We immediately began to see a change in the environment.

    It has made the application and performance better, mainly due to the fact that we are able to give resources and take resources away based on what the need is.

    Our expenses, definitely, have been in a better place based on the savings that we've been able to make in the cloud and on-prem. Turbonomic has been very helpful in that regard. We've been able to see the savings easily based on the reports in Turbonomic. That, and just seeing the machines that are not being used to capacity allows us to set everything up so it runs a bit more efficiently.

    What needs improvement?

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

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

    For how long have I used the solution?

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

    What do I think about the stability of the solution?

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

    What do I think about the scalability of the solution?

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

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

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

    How are customer service and support?

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

    How would you rate customer service and support?

    Positive

    Which solution did I use previously and why did I switch?

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

    How was the initial setup?

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

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

    What's my experience with pricing, setup cost, and licensing?

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

    Which other solutions did I evaluate?

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

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

    What other advice do I have?

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

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

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

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

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

    Which deployment model are you using for this solution?

    On-premises
    Disclosure: PeerSpot contacted the reviewer to collect the review and to validate authenticity. The reviewer was referred by the vendor, but the review is not subject to editing or approval by the vendor.
    PeerSpot user
    Infrastructure Manager at a insurance company with 501-1,000 employees
    Real User
    Recommendations regarding volumes and family types tell us how much we will be saving by implementing them
    Pros and Cons
    • "The recommendation of the family types is a huge help because it has saved us a lot of money. We use it primarily for that. Another thing that Turbonomic provides us with is a single platform that manages the full application stack and that's something I really like."
    • "In Azure, it's not what you're using. You purchase the whole 8 TB disk and you pay for it. It doesn't matter how much you're using. So something that I've asked for from Turbonomic is recommendations based on disk utilization. In the example of the 8 TB disk where only 200 GBs are being used, based on the history, there should be a recommendation like, "You can safely use a 500 GB disk." That would create a lot of savings."

    What is our primary use case?

    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.

    How has it helped my organization?

    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.

    What is most valuable?

    The recommendation of the family types is a huge help because it has saved us a lot of money. We use it primarily for that. Another thing that Turbonomic provides us with is a single platform that manages the full application stack and that's something I really like. 

    One other useful feature in Turbonomic is the support for Kubernetes. That's one of the things that I have worked on with Kevin, our account rep, from Turbonomic. We're going to work on setting that up because our developers are pushing hard for Kubernetes for containers this year. Knowing that it's supporting that is awesome.

    Something that Turbonomic started doing, just a couple of months ago with one of their latest releases, is the potential savings when it comes to disks. It is very promising. They make recommendations based on the type of disks. For example, if you're using a premium SSD, it makes recommendations, based on I/O metrics, to go to a standard SSD. Those types of recommendations are very valuable and that's another area where we see cost savings, which is awesome.

    What needs improvement?

    One ask that I'm waiting for, now that they have the ability to make recommendations for disks, for volumes, and disk tiering, is all about consumption. For example, we have a lot of VMs now, and these VMs use a lot of disks. Some of these servers have 8 TB disks, but they're only being used for 200 GBs. That's a lot of money that we're wasting. In Azure, it's not what you're using. You purchase the whole 8 TB disk and you pay for it. It doesn't matter how much you're using. So something that I've asked for from Turbonomic is recommendations based on disk utilization. In the example of the 8 TB disk where only 200 GBs are being used, based on the history, there should be a recommendation like, "You can safely use a 500 GB disk." That would create a lot of savings. And we would have more of a success rate than with the disk tiering, at least in our case.

    Also, unfortunately, there is no support for cost optimization for networking.

    For how long have I used the solution?

    I've been using Turbonomic for about three years.

    What do I think about the stability of the solution?

    It was definitely more stable on-prem. The reason I say that is because we've had several times where we have run into licensing issues. I don't know why that has been the case, although they have been few and far between. 

    But when it has no issues, it runs just as if it were on-prem. The performance and the stability are not a problem.

    What do I think about the scalability of the solution?

    It's a mature product. It very quickly detects when new VMs, new workloads, are added. You don't have to wait long. The tool picks things up very quickly in our environment.

    How are customer service and technical support?

    Their technical support is excellent. I would rate them a nine out of 10. Whenever I send an email, they respond back. The only reason I don't give them a 10 is that I have been waiting for some time now on the Reserve Instances to work again. That's the only thing that has been a downer because we rely on them heavily. We are now having to use the Azure tool for that, and before the issue with Reserve Instances, we didn't have to. There's a lot of overlap between Azure on Turbonomic, but Turbonomic works better for us.

    An aspect of the Turbonomic team that I have found, working with them over the years, is that whenever we've had an issue, they have always been willing to listen and to address it and to add the features we need. For example, when we started, Reserved Instances was really not up to par. But they listened to their customers and they started making changes. As time has gone on, the product has matured. They've incorporated a lot of the features that we've asked for into their appliance.

    How was the initial setup?

    We tried it first on-prem, years ago. We used to host it. I installed it and updated it, working with the Turbonomic team. When it was hosted in our environment, I was responsible for everything.

    The initial setup was straightforward. Because it was an appliance, the deployment took about an hour to stand it up. We use VMware on-prem so it was done with an OVA file, and it was pretty much a "next-next" process because the OVA is already packaged with how the tool should be deployed. There are certain custom inputs needed, like the name of the appliance, and how much storage. But everything else was already pre-packaged. The configuration definitely took a little bit longer.

    The only downside was that Turbonomic came out with many releases. The latest releases had the latest features, but it required continuous upgrades. If we wanted to take advantage of one feature we continued to have to upgrade the appliance on-prem. That is why, when we found out that they do have a SaaS model, we went with that instead. We wanted Turbonomic to worry about things like the licensing, the updates, et cetera. We don't have to worry about that at all now, and that has been a huge relief. That has saved us a lot of time, for sure.

    We didn't have to do any type of migration to their SaaS offering. They took care of everything in the back end.

    We have five engineers who use the product, including a networking engineer, a storage engineer, and our DevOps team.

    Which other solutions did I evaluate?

    There are competitors out there. Since we're in Azure, which is the only cloud vendor that we use today, it has something called cost Azure Advisor, to help you with costs. I've tried it because it comes with it and we're paying for it, but Turbonomic is a better tool for us. We always seem to gravitate more toward it because everything is right there in that single pane of glass. It gives you recommendations based on Reserve Instances, even though right now, unfortunately, that's not working 100 percent. It does a lot of things, like the family types and the deleted volumes, and that type of automation for us, which is awesome. Azure Advisor does give you that as well, but it doesn't have everything. We have to drill down in it and it's not easy to navigate.

    What other advice do I have?

    At one point the most valuable feature for us was Reserved Instances. The only problem with that today is that last year we changed from the EA licensing model to an MCA. At this moment, unfortunately, the Reserved Instances is not working. They're still working on it. It's in the roadmap, but that definitely was a big selling point for us. It worked well for us because we purchase a lot of Reserved Instances for our VMs.

    Turbonomic makes a lot of recommendations to help prevent resource starvation. We can't implement all of them because it depends on our workloads. Not all the recommendations work for us because workloads on some of our VMs are very seasonal. There may be three times throughout the year, for about two weeks, where those VMs' usage is very high. They have to work at a high level. The solution can only go back a maximum of three months, and it won't work for us in some of those workloads because it doesn't have full visibility into the past year. But for some of our other workloads, those recommendations work.

    Optimization of application performance is an ongoing process for us, especially as we move VMs from on-prem to Azure, or even build new VMs in Azure. More apps are being created and more services are being created, and we're taking advantage of that within Azure. However, we don't use Turbonomic's automation mode to continuously assure application performance by having the software manage resources in real-time. Our DevOps team is using Azure to control that automation.

    For us, Turbonomic is an infrastructure service, VMs. As for applications, not yet, because now that we're introducing Kubernetes into our Azure environment, while it does have support for that, I don't know what it looks like yet. I have a meeting scheduled with them in order to configure that. It doesn't create it for you automatically in the back end. But it's more for our IaaS, infrastructure as a service. For storage, the closest thing now is the disk tiering with recommendations for going from and to different types of standard and premium SSD and HDD disks. Before, there wasn't that level of support. It was just VMs and family types, in our case.

    We use manual execution for implementing the solution’s actions. We use manual because it depends on the business. We run a 24/7 shop. That's how it has always been on-prem, and that's how it is now in Azure, for our production VMs. We need to schedule maintenance windows because some of the recommendations from Turbonomic require a reboot. We need to schedule downtime with the application owners within the business.

    Disclosure: PeerSpot contacted the reviewer to collect the review and to validate authenticity. The reviewer was referred by the vendor, but the review is not subject to editing or approval by the vendor.
    PeerSpot user
    Chief Information Officer at a government with 501-1,000 employees
    Real User
    Easy to manage using a single pane of glass, informative cost estimation features, responsive support
    Pros and Cons
    • "Using this product helps us to reduce performance risk because it shows us where resources are needed but not yet allocated."
    • "Recovering resources when they're not needed is not as optimized as it could be."

    What is our primary use case?

    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.

    How has it helped my organization?

    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.

    What is most valuable?

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

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

    What needs improvement?

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

    For how long have I used the solution?

    I have been working with Turbonomic for approximately four years.

    What do I think about the stability of the solution?

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

    What do I think about the scalability of the solution?

    Turbonomic is a scalable product.

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

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

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

    How are customer service and support?

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

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

    How would you rate customer service and support?

    Positive

    Which solution did I use previously and why did I switch?

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

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

    How was the initial setup?

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

    What about the implementation team?

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

    What was our ROI?

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

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

    What's my experience with pricing, setup cost, and licensing?

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

    Which other solutions did I evaluate?

    I do not recall evaluating other solutions.

    What other advice do I have?

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

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

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

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

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

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

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

    I would rate this solution a nine out of ten.

    Which deployment model are you using for this solution?

    On-premises
    Disclosure: PeerSpot contacted the reviewer to collect the review and to validate authenticity. The reviewer was referred by the vendor, but the review is not subject to editing or approval by the vendor.
    PeerSpot user
    Head of Enterprise Wide Technical Architecture / Enterprise Technology Specialist at a healthcare company with 5,001-10,000 employees
    Real User
    Top 20Leaderboard
    Provides us a map of resource utilization as part of its recommendation
    Pros and Cons
    • "We like that Turbonomic shows application metrics and estimates the impact of taking a suggested action. It provides us a map of resource utilization as part of its recommendation. We evaluate and compare that to what we think would be appropriate from a human perspective to that what Turbonomic is doing, then take the best action going forward."
    • "After running this solution in production for a year, we may want a more granular approach to how we utilize the product because we are planning to use some of its metrics to feed into our financial system."

    What is our primary use case?

    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.

    What is most valuable?

    The most valuable features have been the resizing, then the allocation of resources and where to run the pods. Those have been a huge success for us. It is a self-funding initiative in that regard.

    Turbonomic provides specific actions that prevent resource starvation. Potentially running out of resources is a possibility. Now, we have an overallocation of resources. However, each time we use the resources, we incur additional costs from a licensing perspective. Turbonomic allows us to maximize our resources before we have to utilize additional resources. 

    We like that Turbonomic shows application metrics and estimates the impact of taking a suggested action. It provides us a map of resource utilization as part of its recommendation. We evaluate and compare that to what we think would be appropriate from a human perspective to what Turbonomic is doing, then take the best action going forward. So far, we like exactly what we see from the product. It is very powerful.

    What needs improvement?

    After running this solution in production for a year, we may want a more granular approach to how we utilize the product because we are planning to use some of its metrics to feed into our financial system.

    For how long have I used the solution?

    We have been currently using the product in our OpenShift environment for about six months. We did a PoC starting last Fall. We are now in the process of implementing it in production.

    What do I think about the stability of the solution?

    So far, the stability has been good. There is always room for improvement, but so far we have had no complaints from our team in regards to the product and how it operates in the OpenShift environment.

    How are customer service and technical support?

    The technical support is outstanding. We have had a great relationship with the Turbonomic folks from the beginning. They have given us some excellent resources. Their support is five-stars.

    Which solution did I use previously and why did I switch?

    We did not use another product. We are not replacing anything. We were familiar with the Turbonomic product in the context of our VMware environment. We thought it was the ideal product. Because of the way it calculates things, we also thought it was the right approach going forward. So, we went directly to choosing Turbonomic.

    How was the initial setup?

    Our admins who deployed the technology said it was fairly straightforward. Because Turbonomic in OpenShift runs as a pod, it is fairly straightforward from a deployment model.

    It is a relatively easy product to implement. If you're familiar with OpenShift, my OpenShift admins had no problems deploying it and working with the Turbonomic team. Their support has been great.

    Phase one in deployment is to understand what actions would be from Turbonomic regarding resizing, then take actions based on those recommendations. After we are satisfied with what Turbonomic is doing, we will let Turbonomic take automated actions, which is phase two. We will be building a better trust relationship between our app and operations teams, when we allow Turbonomic to automatically deploy and take actions.

    We like that Turbonomic provides a proactive approach to avoiding performance degradation. In phase one, we will do a manual evaluation of the recommendations. Then, in phase two, we plan to have Turbo fully automated and take actions based on what it thinks the best resource allocation model is.

    We have two separate OpenShift clusters. We will be deploying one environment with more than 100 nodes and the other one with more than 50 nodes.

    What about the implementation team?

    Working with Turbonomic consultants, the deployment was probably a couple of days. That was more to familiarize ourselves with the environment, what the commands were, etc. It was not a function of the complexity of the tool.

    We don't have many people working on the product. We have about three people going through the testing and PoC environment right now and setting it up for deployment in our dev stage, and then finally in our production environment. There are about three individuals working on that. 

    Because the product is self-managing in many ways and runs the way that it does, i.e., it runs as an application inside of OpenShift, I would probably dedicate half a resource from the OpenShift side to managing Turbonomic over the long-term.

    What was our ROI?

    While we are in the process of deploying now, we did a calculation and think that we definitely will be showing value and savings. Our expected ROI is 2:1. 

    What's my experience with pricing, setup cost, and licensing?

    The product is fairly priced right now. Given its capabilities, it is excellently priced. We think that the product will become self-funding because we will be able to maximize our resources, which will help us from a capacity perspective. That should save us money in the long run.

    Which other solutions did I evaluate?

    I did some research on other products out there, but nothing met what I required from. Some of the products were cloud-only solutions, and that wasn't going to work for us because we are an all on-prem environment. However, we still think that the model that Turbonomic uses to make us determinations (its secret sauce) is actually the best thing out there.

    What other advice do I have?

    You need to know OpenShift well to utilize the product. That is probably my biggest piece of advice. The more you know OpenShift, the better off you are when it comes to the product. The product can be self-driving in many ways.

    We came in with a very specific set of goals, and Turbonomic has been able to meet those goals. We have had no real roadblocks so far

    Our only context for productionizing is Turbonomic for containerized environments in OpenShift. We have taken a look at using Turbonomic for VM management, but that is not part of our initial work.

    We are not running any cloud activities right now.

    I would rate them as a nine out of 10. There is always room for improvement. For example, if they lower the cost, I could get a 3:1 ROI.

    Which deployment model are you using for this solution?

    On-premises
    Disclosure: PeerSpot contacted the reviewer to collect the review and to validate authenticity. The reviewer was referred by the vendor, but the review is not subject to editing or approval by the vendor.
    PeerSpot user
    Buyer's Guide
    Download our free IBM Turbonomic Report and get advice and tips from experienced pros sharing their opinions.
    Updated: January 2023
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    Download our free IBM Turbonomic Report and get advice and tips from experienced pros sharing their opinions.