Turbonomics helps us understand resource usage and enables us to make decisions about how to utilize those resources. For example, let's say you check your monthly water bill and see that it's up 25 percent, but you don't know why. It keeps going like that until you check your toilet and find that the seal is slightly broken. 

Every now and then, a tool will keep running when you're not using it. Turbonomics will identify when the toilet is running and fix it for you, so your bill goes up. It automatically makes the adjustments.  

Our organization uses cloud-based infrastructure, so everything is metered. You're wasting money if you have a system running but you're not using it. Turbonomic can take that system offline or suspend it. It can also adjust resources so that they're optimal for a particular workload. It gives you visibility and also takes action automatically. 

Turbonomic offers a single platform for optimizing complex, mixed environments. With APM integration, it can tell you how each application is performing and rationalize the resources to ensure the optimal configuration for performance, so there's no waste. It will make those adjustments for you based on application trends. It covers the complete stack all the way up from your UI down to your core host machine if you're running on a VM or the physical machine if you're running on a device. It tries to ensure consistency and hasn't caused any additional overhead on my applications. 

The automation features are helpful because engineers no longer need to focus on fixing issues. They can spend their time on innovation and more important things. Right now, a lot of the work is still being done manually. When I get alerts, I send a staff member to make adjustments, but I can't do that in real time. It might take days or weeks to address a ticket. The meter is constantly running while we're waiting to fix that so that money is going down the drain.

It's hard to quantify how much time we save using Turbonomic, but it's around 20 percent. I only do analysis and remediation on maybe Tuesday and Thursday. It's not about the time that I waste; it's about the time and cost we can recover. I no longer need to wait until Tuesday. If something happens on the weekend, the tool can fix it on Sunday. It does save time, but the bigger aspect is cost savings.

The core expense of our setup is cloud costs, so cloud management is a huge piece of our financial operations. We're constantly looking at cloud spending and ways to make that more efficient. 

I like Turbonomic's automation and AI machine learning features. It shows you what it can do, but it can also act on recommendations automatically. Integration with an APM system makes the AI/ML features truly effective. Understanding what the application is doing and the trends of application behavior can help you make real-world decisions and act on that information. 

We're still evaluating the solution, so I don't know enough about what I don't know. They've done a lot over the years. I used Turbonomics six or seven years ago before IBM bought them. They've matured a lot since then. 

We've been evaluating Turbonomic for the last few months. 

Turbonomic is stable. 

Turbonomic is highly scalable. 

In addition to Turbonomic, we have a tool called Apptio Cloudability that gives you a report on what you spent that month. I have to go back and identify what is going on. Turbonomic identifies the issue, records it, and fixes it with no manual intervention. We also used the native cloud solutions provided by Amazon or Google, but they weren't as effective as Turbonomics. 

Turbonomic is fairly easy to deploy. The product is highly intuitive from a deployment standpoint. We worked with a consultant from the vendor. The deployment team consisted of five or six people.

We evaluated and purchased Apptio Cloudability. Turbonomics offered an opportunity to reduce the costs of our physical environment, but it's also part of our cloud journey. The cloud capabilities were a significant factor for us. 

I rate Turbonomic nine out of 10. It goes into a lot of detail about what you know and your opportunities, but there's always room to improve. 

Initially, our use case was to reduce cloud spend. But Turbonomic is much more than just a reduction-in-cloud-spend tool. As we went on, it became more about optimizing applications and making sure that they function as expected, while reducing the cost of cloud resources. It became a question of how we make applications function properly, at speed, with the best cost possible, and without creating any risk for the application itself.

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

We use it in a multi-cloud environment.

My favorite part of the solution is the automation scheduling. Being able to choose when actions happen, and how they happen, whether that be through an approval process during the workflow, or whether it be someone executing it on a weekend because they're working in their own environment.

We don't use Turbonomic for FinOps and part of the reason is its cost reporting. The reporting could be much more robust and, if that were the case, I could pitch it for FinOps. You might say that's a weakness, but it's not what it's supposed to do.

If it had the reporting, it would be a 10 out of 10.

I've been using IBM Turbonomic for four years.

Since we moved to the SaaS deployment, I haven't noticed any issues. About five years ago when I started evaluating it, there were some on-prem issues, but not with the SaaS solution.

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.

Their tech support is very responsive. They are part of IBM and not just Turbonomic anymore, so they've grown exponentially over time. But I found, in working with their engineers on the tickets we submitted, that they were very responsive, getting back to us as quickly as they could on the challenges we were having. They have been helpful.

Positive

We would go quarter-to-quarter and say, "Okay, go optimize our application environments." We could use Azure Monitor or a couple of other tools that aren't nearly as robust, and without knowing the impact, other than what Azure Monitor gives you. But Azure Monitor, which doesn't do memory metrics, would tell you, "You can reduce size by doing this," but maybe memory was the problem. Turbonomic is much more robust. Before using it, we were doing things in a very manual way. 

The way I got Turbonomic through the door was by saying, "You want to have your entire staff clean up the cloud every quarter?"

The initial deployment is very straightforward. The Kubernetes stuff was a little beyond me because I'm not a Kubernetes person. But once we got somebody who knew Kubernetes involved, it was pretty straightforward. It takes less than a few hours and that's for an enterprise. It can be done very quickly.

We started with the solution on-prem, but I quickly moved it to the SaaS model because with on-prem there's a lot to manage. It's a Kubernetes cluster and you need a Kubernetes administrator. You have to have rights to it. There are a lot of other moving parts when you manage it yourself. Once you move to a SaaS-based solution, the burden of keeping the product upgraded and up to date is on Turbonomic. I don't want to manage updates and patches.

With the SaaS solution, there is no maintenance on our side.

Our internal resources worked with the Turbonomic team. After that, I turned over the application to the team that is going to be supporting the applications, because I have no insight into applications. That's not my role. Turbonomic is meant to be in their hands, not mine.

There were three to four people involved initially. Once you get it installed, you start bringing in your DevOps engineers to have them understand it, and they'll work with the application support people. 

The team grows as large as it has to, depending on how many application teams and DevOps engineers you have. People can manage their applications or they can manage multiple applications. You can divide it up, so the teams vary in size. But it's always going to land as close to the application as it can, to get the right people to make the right decisions. If you're a very large organization, you don't centralize the product. It doesn't work well that way.

Everybody tells me the pricing is high. But the ROIs are great. Like any software, if it sits on a shelf and no one uses it, it's a waste of money. If you implement it and do the right things before you start using it, the ROI is very fast. And then you can justify the cost, because the ROI is very quick.

We had a couple of hiccups, but we planned for about a nine-month ROI, in the course of a three-year plan. If you put the resources into it and you dedicate the time to it, then ROI is very attainable. If you just let the product churn and tell you what's going on, and don't do anything, then you don't get ROI and don't actually reduce your cloud spend.

I looked at CloudHealth, Cloudability, and one other. We went with Turbonomic because of the intelligence engine. It uses AI to make determinations on data that's coming in at a faster pace than humans can comprehend. People can't monitor a thousand VMs and keep track of them on a daily, hourly, or minute-by-minute basis. With Cloudability, it's not done as efficiently and it's not done with AI. It has cloud-native optimization tools, and they're not as accurate. Turbonomic provides you with accurate, almost up-to-the-minute, information about your application performance, VMs, databases, and storage performance at a much faster pace than humans could ever do. That's why I liked it so much.

Turbonomic does give you visibility into your environment’s performance as well as analytics, from the application layer all the way down the stack. But it does not give you as much as others do. More specialized applications, like New Relic, go much deeper, but with those products, those features are an additional cost. How much is enough is what it really comes down to. How much monitoring and in-depth analytics do you need? Some applications need much more and some don't. If a website is running fine, don't worry about it. In that case, you just need to know the up/down status and that's it. If you're running database queries and things are running slow, you might need deeper analytics. Turbonomic doesn't do that.

Whenever we have a specific application that we need to go into deeper, we will use New Relic or SolarWinds or the like; a dedicated application performance monitoring tool. Turbonomic does have the ability to target apps, but we're not quite there yet.

Educate yourself on the product, as well as on the process. The process is even more important than the product because people need to understand that you're going to be making some changes to the environment. If they're resistant to that, then you're going to have challenges getting Turbonomic to be useful.

You not only need executive buy-in and senior leadership buy-in, you also need your engineers' buy-in. If your executives don't buy into it, your engineers certainly aren't going to. And even if your executives have bought into it, you still have to get the engineers on board because there are all kinds of ways not to do work.

And you have to understand your own company's processes around how to make changes to an environment. What is your change control process? Can you make changes in dev, test, and QA without a change ticket? How do you do production? Do you, in fact, do production?

I would recommend doing something like a workshop where you look at all the applications you're going to point Turbonomic at. Get each team together and explain to them how it's going to work and how it benefits them, as opposed to: "We bought a new product. You're going to use it. Deal with it." People like to know how it impacts their lives and why they're potentially doing more work. In the long run, it actually becomes less work. It's just hard to get past that point. In the movie "Cast Away" it was really hard for Tom Hanks to get past those waves. But once he got past them, he was fine. It's something like that, but not as dramatic; it's not that you're trying to save your life. But you have to explain to people why there's going to be some upfront work: to save them a lot of work on the back end.

In terms of the solution's visibility and analytics helping to bridge the data gap between disparate IT teams, we're working on that. Implementing Turbonomic is a journey. It's not "install it, and then it does what it does." You have to learn it and integrate it into your environment and your workflows. It does shed light on infrastructure and application teams having to work together, and that's a good thing. Application teams generally don't like infrastructure teams because they don't give them enough infrastructure. Infrastructure teams think the application teams complain too much. Turbonomic says, "Here is what you guys are doing. And here is how to get it done right. Work together," and everybody will be happy. That's more of a "people challenge" and less of a technology challenge.

But the visibility and analytics have not yet reduced our mean time to resolution. The solution hasn't had any impact on our application response time and it's not supposed to. Turbonics is supposed to change your resources based on your schedule, and you shouldn't notice it doing anything, except for the downtime that an application sometimes requires. It should be seamless.

Similarly, when it comes to helping our engineers focus on innovation and modernization, it's a work in progress. That's hard to quantify. It's our role, as architects, to help people do their jobs better and have more time to do innovation versus fixing. We are definitely spending less time worrying about application performance, because Turbonomic takes care of that. But in terms of innovation, I have no way to quantify that. We have people learning it and using it, but are we innovating better? I hope so.

We did some digging into Kubernetes and the solution does show you some good insights there, and it may have come a little farther in that regard since the last time I was hands-on with it. It gave us good insight into what our Kubernetes clusters were doing. Since then, we have moved on to doing more IaaS-based stuff.

Overall, it's the best product for APM that I've seen.