Learn about MetricSets in APM π
MetricSets are key indicators, such as request rate, error rate, and durations, calculated based on your traces and spans in Splunk APM. There are two categories of MetricSets: Troubleshooting MetricSets (TMS), used for high-cardinality troubleshooting, and Monitoring MetricSets (MMS), used for real-time monitoring.
MetricSets are specific to Splunk APM, but Monitoring MetricSets are similar to the metric time series used in Splunk Infrastructure Monitoring to populate charts and generate alerts. See the following Monitoring MetricSets section for more information.
Troubleshooting MetricSets π
Troubleshooting MetricSets (TMS) are metric time series you can use for troubleshooting high-cardinality identities in APM. You can also use TMS to make historical comparisons among spans and workflows. You can index span tags and processes to generate TMS.
Splunk APM indexes and generates Troubleshooting MetricSets for several span tags by default. For more details about each of these tags, see Default indexed span tags in APM. You canβt modify or stop APM from indexing these span tags.
You can also create custom TMS by indexing specific span tags and processes. To learn how to index span tags and processes to generate new Troubleshooting MetricSets, see Index span tags to generate Troubleshooting MetricSets.
Available TMS metrics π
Every Troubleshooting MetricSet generates the following metrics, known as request, error, and duration (RED) metrics. The RED metrics appear when you select a service in the service map. See Scenario: Kai investigates the root cause of an error with the Splunk APM service map to learn more.
Request rate
Error rate
Root cause error rate
p50, p90, and p99 latency
The measurement precision of Troubleshooting MetricSets is 10 seconds. Splunk APM reports quantiles from a distribution of metrics for each 10-second reporting window.
Where can I use TMS within Splunk APM? π
TMS appear on the service map <service-map> and in Tag Spotlight. You can use TMS to filter the service map and create breakdowns across the values of a given indexed span tag or process. You can also use TMS to monitor and alert on the performance of your services.
What is the TMS retention period? π
Observability Cloud retains TMS for the same amount of time as raw traces. By default, the retention period is 8 days.
For more details about Troubleshooting MetricSets, see Reference and best practices for span tags and Troubleshooting MetricSets.
Monitoring MetricSets π
Monitoring MetricSets (MMS) are a collection of metric time series (MTS) used in Splunk Infrastructure Monitoring. See Metric time series to learn more. MMS power the real-time APM landing page and the dashboard view. MMS are also the metrics that detectors monitor and use to generate alerts.
Available MMS metrics π
Each MMS includes six metrics. For each metric, there is one MTS with responses sf_error: true
or sf_error: false
.
count
duration.min
duration.median
duration.p90
duration.p99
duration.max
MMS are available for a specific endpoint, for the aggregate of all endpoints in a service, or for a specific Business Workflow.
Endpoint-level MMS reflect the activity of a single endpoint in a service, while service-level MMS aggregate the activity of all of the endpoints in the service. Endpoint-level and service-level MMS are therefore limited to spans where the span.kind = SERVER
or span.kind = CONSUMER
.
Spans might lack a kind
value, or have a different kind
value, in the following situations:
The span originates in self-initiating operations or inferred services
An error in instrumentation occurs.
Workflow-level MMS aggregate data from all traces identified as part of a given Business Workflow.
What is the MMS retention period? π
Observability Cloud stores MMS for 13 months by default.
Comparing Monitoring MetricSets and Troubleshooting MetricSets π
Because endpoint-level and service-level MMS include a subset of the TMS metrics, you might notice that metric values for a service are different depending on the context in Splunk APM. This is because MMS are the basis of the dashboard view, and MMS can only have a kind
of SERVER
or CONSUMER
. In contrast, TMS are the basis of the Troubleshooting and Tag Spotlight views, and TMS arenβt restricted to specific metrics. For example, values for checkout
service metrics displayed in the host dashboard might be different from the metrics displayed in the service map because there are multiple span kind
values associated with this service that the MMS that power the dashboard donβt monitor.
To restrict your TMS to endpoint-only data, so that you can compare MMS and TMS directly, filter to a specific endpoint, or break down the service map by endpoint.
Default identities and MetricSets π
The total number of Troubleshooting MetricSets is the sum of all identities. The total number of Monitoring MetricSets is the sum of Service
, Endpoint
, and Workflow
identities.
Splunk APM creates the following identities and MetricSets:
APM object |
Description |
Identity example |
Troubleshooting MetricSet |
Monitoring MetricSet |
---|---|---|---|---|
Service |
Identities for all services |
Service, 1 |
Yes |
Yes |
Endpoint |
Identities for all endpoints |
Service, 1.Endpoint, 1.HTTPMethod Service, 1.InitEndpoint, 1 if HTTPMethod is absent |
Yes |
Yes |
Workflow |
Identities for all initiating endpoints |
Service, 1.InitEndpoint, 1.HTTPMethod Service, 1.InitEndpoint, 1 if HTTPMethod is absent |
Yes |
Yes |
Edge |
Identities for all edges between services |
Service, 1.Endpoint, 1.HTTPMethod, >Service, 2.Endpoint, 2.HTTPMethod |
Yes |
No |
Operation |
Identities for all spans within services |
Service, 1.Operation, 1 |
No |
No |