Item: IBM Turbonomic
Rating: 9
Author: Verified User

Overall Satisfaction with Turbonomic, an IBM Company

Use Cases and Deployment Scope

We use Turbonomic on the Openshift Platform primarily, but testing it in our HCI context as well. We use Turbonomic to address 2 key problems; (1) to right-size containers which developers typically ask for XL and (2) capacity plan for the size of the Openshift cluster itself - here we are calculating resource consumption and growth.

Pros and Cons

Pros

Right-size container.
Capacity planning through proper resource utilization.
Feed resource consumption to finance system.

Cons

Better usage of consumption stats to find a consistent costing model - containers can be quite dynamic.
Better understanding of CPU throttling impact on the whole application stack.

Return on Investment

Positive ROI for resource usage.
Cost of product was not onerous.

Alternatives Considered

Instana

We liked Turbonomic as it could work in the container space and the VM space. Other products were too one-dimensional. Additionally, the algorithm in Turbonomic is not typical. Turbonomic does not take the standard data elements and map them to consumption. Their use of a "financial" model seems to provide more accurate and meaningful decisions.

Other Software Used

DX Application Performance Management (formerly CA APM), Dynatrace, Splunk Enterprise

Likelihood to Recommend

We use Turbonomic to optimize our Openshift environment. We are seeing that the data captured could also be used for better predictions of how to manage the ecosystem. One of the key reasons to use containers is to pack the hardware as much as possible. Turbonomic helps us do that. We have seen the same use case apply in the VM context.

Comments

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Great tool for modeling resource consumption

Software Version