Overview
The Python integration allows you to collect and monitor your Python application logs, traces, and custom metrics.
Setup
Metric collection
See the dedicated documentation for collecting Python custom metrics with DogStatsD.
Trace collection
See the dedicated documentation for instrumenting your Python application to send its traces to Datadog.
Log collection
Available for Agent v6.0+
See the dedicated documentation on how to setup Python log collection to forward your logs to Datadog.
Profile collection
See the dedicated documentation for enabling the Python profiler.
Data Collected
Metrics
| |
|---|
runtime.python.cpu.time.sys
(gauge) | Number of seconds executing in the kernel
Shown as second |
runtime.python.cpu.time.user
(gauge) | Number of seconds executing outside the kernel
Shown as second |
runtime.python.cpu.percent
(gauge) | CPU utilization percentage
Shown as percent |
runtime.python.cpu.ctx_switch.voluntary
(gauge) | Number of voluntary context switches
Shown as invocation |
runtime.python.cpu.ctx_switch.involuntary
(gauge) | Number of involuntary context switches
Shown as invocation |
runtime.python.gc.count.gen0
(gauge) | Number of generation 0 objects
Shown as resource |
runtime.python.gc.count.gen1
(gauge) | Number of generation 1 objects
Shown as resource |
runtime.python.gc.count.gen2
(gauge) | Number of generation 2 objects
Shown as resource |
runtime.python.mem.rss
(gauge) | Resident set memory
Shown as byte |
runtime.python.thread_count
(gauge) | Number of threads
Shown as thread |
Troubleshooting
Need help? Contact Datadog support.
Further Reading
Additional helpful documentation, links, and articles:
