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.

At the first shop I worked at where we got Turbonomic, we had over 60 hosts and it did a magnificent job. In my current company we're only monitoring 15 or 20. I can't see it having a problem. The more servers you have, the more return you get on it.

In terms of increasing our usage, we're always pushing the developers to do stuff with it. The problem for us is that we're owned by a parent company and IT infrastructure works for and reports to the parent company. But the IT development software group reports to the actual company. They're under a totally different chain of command, so we can't really dictate anything that they do. All we can do is make recommendations, but their director has his own plans. We try to show them the benefits, but it's a lot of work to sit down and configure it, which is not worth it if they're not going to use it. And we have enough other projects that we have to work on, so we have to pick our battles.

Everything is manual. We don't automate anything, only because our environment isn't that big. If we were to set up all the groups as manual, it would actually take more time than just to go in and click go on each of the items after I have submitted a change request. We have about 180 VMs in Azure, not quite big enough to automate.

Turbonomic is highly scalable. 

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

The scalability is great. There is no problem with scaling.

There are about a dozen people from engineering, operations, and capacity who login and use the data to make decisions. It is a hands-off type of product. You only need a couple of key people from the different use case areas to use it.

Turbonomic is scalable. 

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.

It was good. I did not see any big issues, but we did not scale it a lot. We added a couple of accounts later, and it was okay.

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

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

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

The scalability is good. I don't see any issues at all.

We were initially on the high-end of their customers. We ran two instances of it for a while, just because there was a limit of like 10,000 devices per system, and we were significantly past that.

Just from a server perspective, we are running about 26,000 servers right now, where 97 to 98 percent are virtualized. One person can't get a handle on that. Even figuring out what direction to look, you need to have tools to help you.

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. 

It's scalable because we are hosted in the cloud. We can expand it vertically.

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.

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

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

IBM Turbonomic is highly scalable.

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.

Scalability is not a problem. If you need more, just buy more licenses and it expands. They monitor that and expand your instances. It's not something you need to worry about.

We've been able to add resources or things for it to look at without any issues so far. So there haven't been any scalability issues.

We are monitoring 3,000 workloads with Turbonomic.

There are two systems engineers who use it. In terms of maintenance, it only requires software updates. 

We may do some more integration with other applications like AppDynamics, but the platform itself, we've integrated it completely.

I think it would scale very well. Our size is in the medium range, but based on the way I see it working, I don't think it matters what size your cloud infrastructure would be. I think it would handle it very well.

In our company, Turbonomic is monitoring pretty much all of our machines in the Azure cloud. If they're in AWS, those are not managed. That's a separate side of the house and they don't want to have their stuff managed by Turbonomic. But we use it to manage everything from size to suspending, for all of our Azure-based machines.

As we move forward, we'll be using it more. We're going to look into using the suspension feature to suspend more VM. As we start getting comfortable with reserved instances, we'll probably use it to help us gauge how many reserved instances we need to buy.

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.

I have not tried to scale yet.

The scalability is okay. It sometimes has problems with the hybrid nature of things, but it is fairly scalable.

Not yet.

None.

No problems with scalability.

None.

Nothing so far.

Our environment is smaller, and we don't add many resources to what we have. However, it seems to scale pretty well based on what I know about the product.

No scalability issues,so far and we have 20 hosts.

Not yet.

Turbonomic seems scalable to me.

There have been no issues with scalability. Currently, it is used to monitor several hypervisor environments including XenServer, VMware, VXRail, etc.

No.

No, we have not. Initially we used it for our Production Cluster but have recently expanded it to our SQL Cluster without issue.

None.

Scalability is fine. We're using the product extensively with deployment of almost 54,000 systems. We receive a lot of alerts from those systems and do a lot of monitoring, so it's used constantly. 

It seems scalable, although I haven't scaled it up or taken anything away yet. We plan to use more storage. We're not using as much storage as we would like.

We have been able to scale and use the product without any interruptions.

I'm monitoring 6 UCS Domains, 5 vCenter servers, 23 ESXi clusters spanning 115 hosts, and over 900 VMs in six countries. This little appliance has no issues.

None.

It scales well. If you need to scale up, you just purchase more licenses.

We have 6,500 endpoints, which are 95 percent virtual and five percent cloud.

We have our operations team who use it sometimes. Operations gets the first call about performance improvements. If someone calls or opens a ticket with them, and says, "Oh, I need more resources," then they will log onto Turbonomic and see if a machine is underperforming for whatever reason. 

My team is managing the resources for right-sizing and forecasting,

It probably does have a lot of scalability. I'm a pretty small shop compared to some of the users who use this product, but I'm sure it scales out. From what I can tell, no matter how much I grew, it would still scale to my environment. Now, I can't speak about somebody who has 10,000 virtual machines out on the cloud and things of that nature, but it does allow me to facilitate cloud virtual machines outside of my environment if I had any.

No issues.

We started out with VMTurbo in our development and test data center managing over 400 virtual machines. The same instance now manages our entire production data center with our SaaS platform that all of our customers connect to. I didn't have to change anything. The virtual appliance handled it without breaking a sweat.

No.

Ran into a snafu with a database during an upgrade, support was knowledgeable and on top of the issue quickly and resolved it as quickly.

We've had a few issues upgrading and getting things working the way would we like, but Turbonomic has been very supportive to allocate knowledgeable resources to address them quickly.

Not scaling out at this point.

No

Definitely scalable. Our licensing scheme allows us to go into and discover some of the acquisition environments that we've done and see what virtual environments these acquisitions have fairly quickly.

We have multiple vCenters so we did have to break out our initial Turbonomic implementation into multiple Turbonomic instances.

We have not reached the limit scaling yet.

We've actually reduced our host footprint by using Turbonomic to rightsize things as we modernize and migrate.

The appliance has been able to handle our environment with speedy interface response.

None.

I haven't had a need to increase or decrease the amount of hosts i'm monitoring. From the GUI i'm able to find the top 10 worst offending VMs for resource utilization or what have you fairly easily. I'm monitoring 15 or so ESXi hosts with nearly 1000 VMs, I haven't had any issues with the product not able to handle my scale.

Not applicable.

No issues have been encountered with scalability.

The only issue we have had with scalability is that the sites are not integrated into the aggregator. We need to update each site individually and cannot export or import the changes, and need to do double duty to maintain a level playing field in multiple environments.

No.

No.

No.

None.

Turbonomic is fantastic at scalability! It has great built in tools to plan scaling.

We have not had any issues with scalability.

No.

None.

None.

No issues.

Nope.

None.

No.

There were no issues with scalability.

None so far. My environment doesn't task the scalability meter though.

No.

Again, we have not come across any issues here.

No.

It easily handles the environment.

One Turbonomic instance supports up to 10,000 VMs, so no, scalability was not an issue.

No.

No, albeit I haven't scaled out much, there hasn't been any issues with adding some nodes here and there.

No.

There were no scal issues.

No.

None.

None.

No.

None.

We've continued to expand our VMware environment and the application has scaled with it.

None.

None.

No.

None.

No.

No. Have yet to have a need to change the number of hosts in our environment. We have had to replace some older hosts per Turbonomic's suggestion.

No.

None.

We've had no issues with scalability yet.

No. We use if for seven hosts at two sites.

None.

None. We deployed the appliance two years ago and since then have added four more vCenters (200+ VMs) for it to manage and we have not had to change any settings to do this.

No.

None

No

No issues with scalability as the VM when deployed is provisioned well for your environment.

No scalability issues encountered.

No.

No, but our environment has been pretty stable for the past 18 months.

Nothing as of now.

No.

None.

None.

No

There were no issues with scalability.

None.

Not thus far.

No issues.

No issues with scalability.

With any application like this, the more information it holds, the slower it could take. We have roughly 80 hosts and about 3500 VMs in it and it might take some time to complete a full discovery, but it is negligible considering the importance of the data.

No.

No.

Due to the ability to link multiple instance to each other, it can easily be scaled and segmented.

None.

None.

None

None.

No.

There were no issues with scalability.

No, we have a steady growing Global environment and we didn't have issues so far.

No.

No

No, we scaled our ESXi hosts and VMTurbo scaled accordingly.

No.

We have added additional hosts quite easily.

Additional licensing purchases were the only issues for scalability.

None.

I have not encountered any scalability issues.

No issues with scalability.

No issues.

We have not added any additional hosts.

Scalability has not been an issue. In fact, we included some additional socket licenses in our initial acquisition as we anticipated adding additional physical hosts to our environment.

No

It's best used in a clustered environment, and a bit cumbersome to maneuver around in when installed in a single host environment.

Nope.

Nope.

None at all.

None.

None.

We have 4000+ VMs in our environment and 120+ Hosts. No issues so far with the scalability.

None.

No issues with scalability.

None.

No.

Only because of licensing, since the model we have is per Core.

No issues.

No, we have one Turbo instance controlling multiple datacenters.

None at all, we have a lot of hosts and VMs and the OVA file we deployed scaled perfectly.

No.

None. The software was been able to keep pace with our environment as it has grown and the licensing model allows us to true up yearly.

No.

We never experienced any scalability issues.

No issues scaling we add a new host every 1-2 years.

No issues have been encountered with scalability

No.

No

No.

No

No.

None.

No issues with scalability.

No.

We did not encounter any issues with scalability.

No.