Calculate your consumption of Full-Stack Monitoring (DPS)

This page describes how the Full-Stack Monitoring DPS capability is consumed and billed. For an overview of the capability, including its main features, see Full-Stack Monitoring.

Each installed instance of Dynatrace OneAgent running on an operating system instance (deployed on either K8s, a container platform, or a physical or virtual machine) in Full-Stack Monitoring mode consumes GiB-hours based on the monitored host's physical or virtual RAM, calculated in 15-minute intervals (see the diagram example below).

The RAM of each VM or host is rounded up to the next multiple of 0.25 GiB (which equates to 256 MiB) before monitoring consumption is calculated. A 4 GiB minimum is applied to GiB-hour consumption for physical and virtual hosts. For example, a host with 8.3 GiB memory is counted as an 8.5 GiB host, being the next multiple of 0.25 GiB, while a host with 2 GiB memory is counted as a 4 GiB host (no rounding needed, but application of the 4 GiB minimum).

In cloud-native environments, services and hosts are often short-lived. Therefore, calculating monitoring consumption in 15-minute time intervals, rather than full hours, better reflects actual usage. Containers, which are an essential mechanism in cloud-native environments, typically use less memory than hosts. Therefore, the minimum memory threshold for containers is 256 MiB, rather than 4 GiB, the minimum memory threshold for hosts.

The same rounding as for hosts, to the next multiple of 0.25 GiB, also applies to containers. For example, a container with 780 MiB memory is counted as a 1 GiB container (780 MiB, which equals 0.78 GiB, being rounded up to the next multiple of 0.25 GiB).

The diagram below illustrates how memory is counted for GiB-hour consumption calculations at 15-minute intervals.

GiB-hour consumption for hosts and containers is based on memory size, calculated in 15-minute intervals each hour. Each interval is divided by 4 in order to reach the GiB-hour consumption unit of measure.

Considering the example shown in Figure 1, here are the calculations for the included metric data point volumes for each of the four 15-minute intervals, assuming a volume of 900 included metric data points for each 15-minute interval.

If Metrics powered by Grail does not exist on your rate card, metric data points are charged as Custom Metrics Classic.

You can monitor the total memory-GiB-hour consumption aggregated across all Full-Stack monitored hosts for different intervals (15 min, hour, day, or week) for any selected timeframe using the "(DPS) Full-Stack Monitoring billing usage" metric. The example below shows memory GiB monitored in 1-hour intervals. Between 11:00 and 14:00, 523 memory-GiB were monitored each 1 hour. This results in 523 memory-GiB-hours consumed.

You can break down the total memory-GiB-hour consumption using the "(DPS) Full-Stack Monitoring billing usage per host" metric. The example below shows the list of all hosts that contributed to the 523 memory-GiB-hour consumption between 13:00 and 14:00. The respective number of memory-GiB-hours per host is displayed as well.

Platform and cluster owners can monitor their Kubernetes clusters using Kubernetes Platform Monitoring. Application owners can leverage container-based Full-Stack Monitoring to monitor applications running within Kubernetes clusters.

To get consumption insights for monitored Kubernetes clusters or namespaces, you can query memory-GiB-hour consumption by leveraging the "(DPS) Full-Stack Monitoring billing usage per container" metric, as shown in the following query:

builtin:billing.full_stack_monitoring.usage_per_container:filter(eq("application_only_type","kubernetes")):splitBy()

In the example below, 1.58 TiB of memory was consumed by the Kubernetes cluster within the past 30 days.

Of course, you can filter your analysis for deeper insights (for example, add a split for Kubernetes namespaces).

To monitor your metrics budget for the whole pool of metric data points in your environment, you can track available included metric data points against total reported metrics data points using these two metrics: "(DPS) Available included metric data points for Full-Stack monitored hosts" and "(DPS) Total metric data points reported by Full-Stack monitored hosts". The example below shows data for a full day. At no time was the number of included metrics for this environment's metric pool (purple line) overspent.

In cases where the number of included metrics for an environment's metric pool are overspent, the following analysis can help you to identify the hosts that are contributing to the overspending. Use the metric "(DPS) Metric data points reported and split by Full-Stack monitored hosts" for this analysis.

The example below shows that between 10:45 and 11:00, each of the first 3 hosts in the list reported far more than 2,000 metric data points. In the same period, each of these 3 hosts shows a memory-GiB-hour consumption of 2 GiB. Dynatrace offers 900 included custom metric data points for each GiB of host memory, calculated at 15-minute intervals. This means that the first 3 hosts contribute 1,800 (2*900) metric data points to the environment's pool of available data points. However these hosts consumed more data points than they contributed during the same time period.

When using the metric "(DPS) Total metric data points billed for Full-Stack monitored hosts" from Custom Metrics Classic you can see that no overspending occurred for this environment's Full-Stack Monitoring metric pool between 10:45 and 11:00 because no metric data points were billed.