Metricsedit

The Go agent periodically gathers and reports metrics. Control how often metrics are reported with the ELASTIC_APM_METRICS_INTERVAL configuration, and disable metrics with ELASTIC_APM_DISABLE_METRICS.

System metricsedit

The Go agent reports basic system-level and process-level CPU and memory metrics. For more system metrics, consider installing Metricbeat on your hosts.

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

In some cases data from multiple nodes will be combined. As of Elastic Stack version 7.5, you will be able to set a unique name for each node to avoid this problem. Otherwise, data will be aggregated separately based on container ID or host name.

system.cpu.total.norm.pct

type: scaled_float

format: percent

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

system.process.cpu.total.norm.pct

type: scaled_float

format: percent

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

Total memory.

system.memory.actual.free

type: long

format: bytes

The actual memory in bytes. It is calculated based on the OS. On Linux it consists of the free memory plus caches and buffers. On OSX it is a sum of free memory and the inactive memory. On Windows, this value does not include memory consumed by system caches and buffers.

system.process.memory.size

type: long

format: bytes

The total virtual memory the process has.

Go runtime metricsedit

The Go agent reports various Go runtime metrics.

As of now, there are no built-in visualizations for these metrics, so you will need to create custom Kibana dashboards for them.

golang.goroutines

type: long

The number of goroutines that currently exist.

golang.heap.allocations.mallocs

type: long

The number of mallocs.

golang.heap.allocations.frees

type: long

The number of frees.

golang.heap.allocations.objects

type: long

The total number of allocated objects.

golang.heap.allocations.total

type: long

format: bytes

Bytes allocated (even if freed) throughout the lifetime.

golang.heap.allocations.allocated

type: long

format: bytes

Bytes allocated and not yet freed (same as Alloc from runtime.MemStats).

golang.heap.allocations.idle

type: long

format: bytes

Bytes in idle spans.

golang.heap.allocations.active

type: long

format: bytes

Bytes in non-idle spans.

golang.heap.system.total

type: long

format: bytes

Total bytes obtained from system (sum of XxxSys from runtime.MemStats).

golang.heap.system.obtained

type: long

format: bytes

Via HeapSys from runtime.MemStats, bytes obtained from system. heap_sys = heap_idle + heap_inuse.

golang.heap.system.stack

type: long

format: bytes

Bytes of stack memory obtained from the OS.

golang.heap.system.released

type: long

format: bytes

Bytes released to the OS.

golang.heap.gc.total_pause.ns

type: long

The total garbage collection duration in nanoseconds.

golang.heap.gc.total_count

type: long

The total number of garbage collections.

golang.heap.gc.next_gc_limit

type: long

format: bytes

Target heap size of the next garbage collection cycle.

golang.heap.gc.cpu_fraction

type: float

Fraction of CPU time used by garbage collection.

Application Metricsedit

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 Go 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)