def _os(self) -> Iterator[Metric]:
os_dict = self._metrics_dict["os"]
yield from (
TimestampGaugeMetricFamily(
"kibana_os_load_%s" % key, "Kibana OS load %s" % key, value=value, timestamp=self._timestamp
)
for key, value in os_dict["load"].items()
)
yield from (
TimestampGaugeMetricFamily(
"kibana_os_memory_%s_bytes" % key.split("_")[0],
"Kibana %s OS memory" % key.split("_")[0],
value=value,
timestamp=self._timestamp,
)
for key, value in os_dict["memory"].items()
)
yield TimestampCounterMetricFamily(
"kibana_os_uptime_seconds",
"Kibana OS uptime in seconds",
value=os_dict["uptime_in_millis"] / 1000,
timestamp=self._timestamp,
)
def test_timestamp_metric_family_keeps_timestamp_from_add_metric(self):
timestamp = 214
t = TimestampGaugeMetricFamily("some_name",
"some description",
timestamp=timestamp)
t.add_metric(labels=[], value=123, timestamp=234)
self.assertEqual(t.samples[0].timestamp, 234)
def test_timestamp_metric_family_sets_timestamp_on_metrics_implicit_metrics(
self):
timestamp = 214
t = TimestampGaugeMetricFamily("some_name",
"some description",
timestamp=timestamp,
value=2)
self.assertEqual(t.samples[0].timestamp, timestamp)
def _response_times(self) -> Iterator[Metric]:
rt_dict = self._metrics_dict["response_times"]
yield TimestampGaugeMetricFamily(
"kibana_response_time_max_seconds",
"Kibana maximum response time in seconds",
value=rt_dict["max_in_millis"] / 1000,
timestamp=self._timestamp,
)
# Kibana statistics lib can sometimes return NaN for this value.
# If that is the case, this is set to 0 in order to avoid gaps in the time series.
# Reference: https://github.com/elastic/kibana/blob/6.7/src/server/status/lib/metrics.js#L73
# NaN is converted to `undefined` which then has the whole field removed from the response JSON
yield TimestampGaugeMetricFamily(
"kibana_response_time_avg_seconds",
"Kibana average response time in seconds",
value=rt_dict.setdefault("avg_in_millis", 0) / 1000,
timestamp=self._timestamp,
)
def _process(self) -> Iterator[Metric]:
process_dict = self._metrics_dict["process"]
yield TimestampGaugeMetricFamily(
"kibana_process_memory_heap_total_bytes",
"Total heap size in bytes",
value=process_dict["memory"]["heap"]["total_in_bytes"],
timestamp=self._timestamp,
)
yield TimestampGaugeMetricFamily(
"kibana_process_memory_heap_used_bytes",
"Used heap size in bytes",
value=process_dict["memory"]["heap"]["used_in_bytes"],
timestamp=self._timestamp,
)
yield TimestampGaugeMetricFamily(
"kibana_process_memory_heap_size_limit_bytes",
"Heap size limit in bytes",
value=process_dict["memory"]["heap"]["size_limit"],
timestamp=self._timestamp,
)
yield TimestampGaugeMetricFamily(
"kibana_process_memory_resident_set_size_bytes",
"Memory resident set size",
value=process_dict["memory"]["resident_set_size_in_bytes"],
timestamp=self._timestamp,
)
yield TimestampCounterMetricFamily(
"kibana_process_uptime_seconds",
"Kibana process uptime in seconds",
value=process_dict["uptime_in_millis"] / 1000,
timestamp=self._timestamp,
)
def _requests(self) -> Iterator[Metric]:
req_dict = self._metrics_dict["requests"]
yield TimestampGaugeMetricFamily(
"kibana_requests_total", "Total requests serviced", value=req_dict["total"], timestamp=self._timestamp
)
yield TimestampGaugeMetricFamily(
"kibana_requests_disconnects",
"Total requests disconnected",
value=req_dict["disconnects"],
timestamp=self._timestamp,
)
per_status = TimestampGaugeMetricFamily(
"kibana_requests", "Total requests by status code", labels=["status_code"], timestamp=self._timestamp
)
for code, count in req_dict["status_codes"].items():
per_status.add_metric(labels=[code], value=count)
yield per_status
def test_timestamp_metric_family_has_timestamp_if_set(self):
timestamp = 214
t = TimestampGaugeMetricFamily("some_name",
"some description",
timestamp=timestamp)
self.assertEqual(t._timestamp, timestamp)
def test_timestamp_metric_family_has_none_timestamp_if_unset(self):
t = TimestampGaugeMetricFamily("some_name", "some description")
self.assertIsNone(t._timestamp)