Cost & Carbon Optimization concepts

• Latest Dynatrace
• Explanation
• Published Jun 29, 2026

Cost & Carbon Optimization uses industry-standard guidelines to estimate electricity consumption, carbon emissions, and cloud costs for Dynatrace-monitored hosts and Kubernetes infrastructure.

Methodology to estimate electricity consumption

Electricity consumption and carbon dioxide emission are calculated based on guidelines from the Sustainable Digital Infrastructure Alliance (SDIA) with some contributions from the Cloud Carbon Footprint project and internal research from Dynatrace. All of the methodology is aligned with the GHG Protocol.

Energy is estimated based on the utilization metrics captured by Dynatrace OneAgent (in all modes for hosts) for CPU, memory, storage IO, and network. This estimation is performed every hour for each instrumented host through an automation.

The formula to estimate energy draw includes several parameters from external data sources and some assumptions.

External data sources

Assumptions for electricity consumption

Power Usage Effectiveness (PUE)

The final result of the formula includes the energy consumed by hardware and cooling. Cooling is included in a standard metric, Power Usage Effectiveness (PUE—not displayed directly in Cost & Carbon Optimization but available in the raw data generated). This metric, used to measure the energy efficiency of a data center, is a ratio between the total power consumption of a data center—including cooling, lighting, and support equipment energy use—and the power consumed by the IT infrastructure. It describes how much energy IT equipment uses compared to other electrical devices.

The Power Usage Effectiveness varies depending on a data center, but its predefined values for the main cloud providers are publicly available. The ones used in the calculation are:

Wasted energy calculation

Wasted Energy calculation is based on the assumption that every CPU cycle that is not utilized wastes about 1/3*TDP (Thermal Design Power). The proportion of unutilized CPU cycles is roughly 100% - CPU usage %. With those assumptions, the Wasted Energy (WE) is calculated as WE = Wp * 1/3 * TDP, where Wp is 0 for 100% CPU utilization and 1 when the CPU utilization is equal to the idle threshold.

Carbon emissions calculation

Carbon emissions are estimated in CO2 equivalent grams. The calculation is multiplying carbon intensity factors by total energy consumed calculated with previous methodology.

Assumptions for carbon emissions

Carbon intensity data sources

Public price list costs calculation

Cost & Carbon Optimization can collect public price list data from cloud providers available data on a daily basis, limited to the regions where OneAgents are deployed and cloud extensions are configured.

Every hour, the same workflow that generates the data for energy and emissions also calculates the hourly cost of a host based on the public price list matched with its cloud vendor, region, and instance type.

Both business events follow the Dynatrace Semantic Dictionary schema.

Data centers and hosts

The Data center emissions table on the landing page shows costs, energy, and CO2e consumption per data center. Select a data center name to view details of its hosts.

The Hosts tab details cost, energy, and CO2e consumption per host. You can narrow your search using filters. For example, you can view underutilized hosts in a specific data center or top CO2e emitters.

Expand a hostname to see key infrastructure metrics: CPU in use, Memory in use, and Receiving network traffic. Select a host name to view the host details page in Infrastructure & Operations.

Cost & Carbon Optimization is automatically connected to Dynatrace Smartscape® topology modeling, so it's easy to see the host details or use Notebooks for ad hoc analysis with DQL.

Measure the energy of Dynatrace Kubernetes platform monitoring

Use Cost & Carbon Optimization to measure energy and carbon emissions of your Kubernetes infrastructure.

Cost & Carbon Optimization calculates the energy consumed (in Watt-hours) and carbon emissions (in grams of carbon dioxide emissions) of Kubernetes clusters and namespaces, and nodes, monitored by Dynatrace. All Dynatrace Kubernetes monitoring modes are supported, and data is calculated hourly and stored as carbon Kubernetes events.

Organizations using Kubernetes today, or looking to migrate workloads to Kubernetes, should consider using Cost & Carbon Optimization in addition to the Dynatrace Kubernetes monitoring for the following reasons:

Energy use is a direct driver of cost

Cloud infrastructure costs are largely driven by energy consumption. CPU, memory, storage, and networking all consume power, and cloud providers factor this into pricing. By measuring energy usage, you're essentially tracking the underlying metric that influences cost.

Carbon footprint adds environmental context

Carbon footprint translates energy consumption into environmental impact. This is especially valuable for organizations with sustainability goals or ESG (Environmental, Social, and Governance) reporting requirements.

Optimization opportunities align

Inefficient clusters, namespaces, and nodes that consume more energy (and thus emit more carbon) are often the ones driving up cloud costs. Identifying high-carbon workloads can highlight areas for cost and environmental optimization.

The app will generate carbon Kubernetes bizevents in addition to regular carbon bizevents when the Enable energy and emission data generation option is enabled within the app's settings.

You can report on Kubernetes infrastructure energy and carbon emissions using custom DQL and dashboards.

Cluster calculations

Each Kubernetes node within the cluster is identified as a host, and Cost & Carbon Optimization uses the host processor, and utilization information to calculate energy and carbon every hour using the Cost & Carbon Optimization Calculation workflow. The carbon and energy metrics of all nodes are summed and stored as a bizevent using: type="carbon.measurement.k8s.cluster".

Namespace calculations

Namespace carbon and energy values are derived by determining the % utilization of each namespace across the Kubernetes nodes it runs on, proportionally allocating energy and carbon from each node to the namespace. The carbon and energy metrics of all nodes are summed and stored as a bizevent using: type="carbon.measurement.k8s.namespace".