IBM Turbonomic 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.

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.

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.

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

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.

Before implementing Turbonomic, we had difficulty reaching a consensus about VM placement and sizing. Everybody's opinion was wrong, including mine. The application developers, implementers, and infrastructure team could never decide the appropriate size of a virtual machine. I always made the machines small, and they always made them too big. We were both probably wrong.

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.

Using this product helps us to reduce performance risk because it shows us where resources are needed but not yet allocated.

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.

With Turbonomic, we were able to reduce our ESX cluster size and save money on our maintenance and license renewals. It saved us around $75,000 per year but it's a one-time reduction in VMware licensing. We don't renew the support. The ongoing savings is probably $50,000 to $75,000 a year, but there was a one-time of $200,000 plus.

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.

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.

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.

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.

The way it handles updates needs to be improved.

Turbonomic doesn't do storage placement how I would prefer. We use multiple shared storage volumes on VMware, so I don't have one big disk. I have lots of disks that I can place VMs on, and that consumes IOPS from the disk subsystem. We were getting recommendations to provision a new volume.

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.

Recovering resources when they're not needed is not as optimized as it could be.

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.

The GUI and policy creation have room for improvement. There should be a better view of some of the numbers that are provided and easier to access. And policy creation should have it easier to identify groups.