›

Metricsedit

The .NET agent tracks certain system and application metrics. Some of them have built-in visualizations and some can only be visualized with custom Kibana dashboards.

These metrics will be sent regularly to the APM Server and from there to Elasticsearch. You can adjust the interval with the setting MetricsInterval.

The metrics will be stored in the apm-* index and have the processor.event property set to metric.

"Platform: all" means that the metric is available on every platform where .NET Core is supported.

System metricsedit

As of APM version 6.6, these metrics will be visualized in the APM app.

System CPU usage metric is collected using Performance Counters on Windows. The account under which a traced application runs must be part of the Performance Monitor Users group to be able to access performance counter values.

An account can be added to the Performance Monitor Users group from the command line

net localgroup "Performance Monitor Users" "<Account Name>" /add

<Account Name> is the account under which the traced application runs

For applications running in IIS, IIS application pool identities use virtual accounts with a name following the convention IIS APPPOOL\<Application pool name>. An individual application pool identity can be added to the Performance Monitor Users group using the net localgroup command above.

For more system metrics, consider installing metricbeat on your hosts.

system.cpu.total.norm.pct

type: scaled_float

format: percent

platform: Windows and Linux only

The percentage of CPU time in states other than Idle and IOWait, normalized by the number of cores.

system.process.cpu.total.norm.pct

type: scaled_float

format: percent

platform: all

The percentage of CPU time spent by the process since the last event. This value is normalized by the number of CPU cores and it ranges from 0 to 100%.

system.memory.total

type: long

format: bytes

Platform: Windows and Linux only.

Total memory.

system.memory.actual.free

type: long

format: bytes

Platform: Windows and Linux only.

Actual free memory.

system.process.memory.size

type: long

format: bytes

platform: all

The total virtual memory the process has.

system.process.memory.rss.bytes

type: long

format: bytes

platform: all

The total physical memory the process has.

Runtime metricsedit

clr.gc.count

type: long

Platform: all.

The total number of GC collections that have occurred.

clr.gc.gen0size

type: long

format: bytes

Platform: all.

The size of the generation 0 heap.

clr.gc.gen1size

type: long

format: bytes

Platform: all.

The size of the generation 1 heap.

clr.gc.gen2size

type: long

format: bytes

Platform: all.

The size of the generation 2 heap.

clr.gc.gen3size

type: long

format: bytes

Platform: all.

The size of the generation 3 heap - also known as Large Object Heap (LOH).

clr.gc.time

type: long

format: ms

Platform: all.

The approximate accumulated collection elapsed time in milliseconds.

Built-in application metricsedit

To power the Time spent by span type graph, the agent collects summarized metrics about the timings of spans and transactions, broken down by span type.

transaction.duration

type: simple timer

This timer tracks the duration of transactions and allows for the creation of graphs displaying a weighted average.

Fields:

sum.us: The sum of all transaction durations in microseconds since the last report (the delta)
count: The count of all transactions since the last report (the delta)

You can filter and group by these dimensions:

transaction.name: The name of the transaction
transaction.type: The type of the transaction, for example request

transaction.breakdown.count

type: long

format: count (delta)

The number of transactions for which breakdown metrics (span.self_time) have been created. As the Java agent tracks the breakdown for both sampled and non-sampled transactions, this metric is equivalent to transaction.duration.count

You can filter and group by these dimensions:

transaction.name: The name of the transaction
transaction.type: The type of the transaction, for example request

span.self_time

type: simple timer

This timer tracks the span self-times and is the basis of the transaction breakdown visualization.

Fields:

sum.us: The sum of all span self-times in microseconds since the last report (the delta)
count: The count of all span self-times since the last report (the delta)

You can filter and group by these dimensions:

transaction.name: The name of the transaction
transaction.type: The type of the transaction, for example request
span.type: The type of the span, for example app, template or db
span.subtype: The sub-type of the span, for example mysql (optional)

« OpenTelemetry Bridge Logs »