Turbonomic Glossary

Turbonomic Global Glossary

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Data Cloud

Turbonomic Data Cloud is a data service that integrates directly with Turbonomic to pull data about your Applications, Container Orchestration, Hypervisors, Storage, and Cloud Service Providers and give you the means to show and share how Turbonomic is currently assuring application performance.

For more information, see the Data Cloud documentation at 

Data Exporter

The Data Exporter is a reporting capability that customers can use to feed reporting data to an external system. By using Data Exporter, valuable Turbonomic insights can be visualized with reporting solutions that customers already have in their environments.

The Data Exporter is a component that extracts reporting data from the core Turbonomic platform, transforms the data into JSON, and regularly publishes that data to a Kafka topic.

Data Transfer Object (DTO)

A Data Transfer Object (DTO) is an object that is used to encapsulate data and send it from one subsystem of Turbonomic to another. The API uses DTOs to send and receive REST payloads. For example, a DTO can represent the list of actions for a given entity. Turbonomic uses Kafka software to communicate DTOs between its platform components.


The memory in use by the database, as a percentage of the allocated capacity. Database configuration determines the capacity for this resource. Note that for databases, Turbonomic uses this resource to drive actions, instead of the VMem on the hosting VM. This means that actions are driven by the actual memory consumption on the database.

Desired State

The Desired State is the state of your environment that assures application performance while achieving efficient use of resources and complying with business rules and constraints.

Instead of responding after a threshold is crossed, Turbonomic analyzes operating conditions and constantly recommends actions to keep the entire environment within the desired state.

You can measure performance as a function of delay, in which zero delay gives the ideal Quality of Service (QoS) for a given service. You can measure efficiency as a function where 100% utilization of a resource is the ideal. You can plot the relationship between delay and utilization as a curve. Up to a point, as you increase utilization, the increase in delay is slight. There comes a point on the curve where a slight increase in utilization results in an unacceptable increase in delay. On the other hand, there is a point in the curve where a reduction in utilization doesn’t yield a meaningful increase in QoS. The desired state lies within these points on the curve. 

DRS (Distributed Resource Scheduler)

DRS is the VMware vSphere utility that “provides resource management capabilities like load balancing and virtual machine (VM) placement” on a cluster of ESXI hosts. (Understanding vSphere DRS Performance, p.4).

Turbonomic discovers DRS rules in your environment and generates Placement Policies that respect the given constraints.


Dynatrace is a platform that uses artificial intelligence to deliver application performance monitoring (APM), artificial intelligence for operations (AIOps), IT infrastructure monitoring, digital experience management (DEM), and digital business analytics capabilities.

Turbonomic supports discovery of applications that are managed by the Dynatrace platform, and can make recommendations and take actions to both assure performance and drive efficiency with the full knowledge of the demands of each individual application experience.