def startMonitoringWithRetries():
"""
:returns: metricId
"""
with self.connectionFactory() as conn:
with conn.begin():
repository.lockOperationExclusive(
conn, repository.OperationLock.METRICS)
# Check if the metric is already monitored
matchingMetrics = repository.getAutostackMetricsWithMetricName(
conn,
autostackId,
nameColumnValue,
fields=[schema.metric.c.uid])
matchingMetric = next(iter(matchingMetrics), None)
if matchingMetric:
msg = (
"monitorMetric: Autostack modelId=%s is already "
"monitoring metric=%s on resource=%s; model=%r" %
(matchingMetric.uid, nameColumnValue,
canonicalResourceName, matchingMetric))
self._log.warning(msg)
raise YOMP.app.exceptions.MetricAlreadyMonitored(
msg, uid=matchingMetric.uid)
# Add a metric row for the requested metric
metricDict = repository.addMetric(
conn,
datasource=self._DATASOURCE,
name=nameColumnValue,
description=metricDescription,
server=canonicalResourceName,
location=autostack.region,
tag_name=autostack.name,
parameters=htmengine.utils.jsonEncode(modelSpec),
poll_interval=period,
status=MetricStatus.UNMONITORED)
metricId = metricDict["uid"]
repository.addMetricToAutostack(conn, autostackId,
metricId)
# Start monitoring
scalar_metric_utils.startMonitoring(
conn=conn,
metricId=metricId,
swarmParams=swarmParams,
logger=self._log)
self._log.info("monitorMetric: monitoring metric=%s, stats=%r",
metricId, stats)
return metricId
def startMonitoringWithRetries():
"""
:returns: metricId
"""
with self.connectionFactory() as conn:
with conn.begin():
repository.lockOperationExclusive(conn,
repository.OperationLock.METRICS)
# Check if the metric is already monitored
matchingMetrics = repository.getAutostackMetricsWithMetricName(
conn,
autostackId,
nameColumnValue,
fields=[schema.metric.c.uid])
matchingMetric = next(iter(matchingMetrics), None)
if matchingMetric:
msg = ("monitorMetric: Autostack modelId=%s is already "
"monitoring metric=%s on resource=%s; model=%r"
% (matchingMetric.uid, nameColumnValue,
canonicalResourceName, matchingMetric))
self._log.warning(msg)
raise YOMP.app.exceptions.MetricAlreadyMonitored(
msg,
uid=matchingMetric.uid)
# Add a metric row for the requested metric
metricDict = repository.addMetric(
conn,
datasource=self._DATASOURCE,
name=nameColumnValue,
description=metricDescription,
server=canonicalResourceName,
location=autostack.region,
tag_name=autostack.name,
parameters=htmengine.utils.jsonEncode(modelSpec),
poll_interval=period,
status=MetricStatus.UNMONITORED)
metricId = metricDict["uid"]
repository.addMetricToAutostack(conn, autostackId, metricId)
# Start monitoring
scalar_metric_utils.startMonitoring(
conn=conn,
metricId=metricId,
swarmParams=swarmParams,
logger=self._log)
self._log.info("monitorMetric: monitoring metric=%s, stats=%r",
metricId, stats)
return metricId
def startMonitoringWithRetries():
""" :returns: metricId """
with self.connectionFactory() as conn:
with conn.begin():
repository.lockOperationExclusive(
conn, repository.OperationLock.METRICS)
# Check if the metric is already monitored
matchingMetrics = repository.getCloudwatchMetricsForNameAndServer(
conn,
nameColumnValue,
canonicalResourceName,
fields=[
schema.metric.c.uid, schema.metric.c.parameters
])
for m in matchingMetrics:
parameters = htmengine.utils.jsonDecode(m.parameters)
if (parameters["metricSpec"]["dimensions"] ==
metricSpec["dimensions"]):
msg = (
"monitorMetric: Cloudwatch modelId=%s is already "
"monitoring metric=%s on resource=%s; model=%r"
% (m.uid, nameColumnValue,
canonicalResourceName, m))
self._log.warning(msg)
raise htm.it.app.exceptions.MetricAlreadyMonitored(
msg, uid=m.uid)
# Add a metric row for the requested metric
metricDict = repository.addMetric(
conn,
name=nameColumnValue,
description=metricDescription,
server=canonicalResourceName,
location=resourceLocation,
poll_interval=metricPeriod,
status=MetricStatus.UNMONITORED,
datasource=self._DATASOURCE,
parameters=htmengine.utils.jsonEncode(modelSpec),
tag_name=resourceName)
metricId = metricDict["uid"]
self._log.info("monitorMetric: metric=%s, stats=%r",
metricId, stats)
# Start monitoring
scalar_metric_utils.startMonitoring(
conn=conn,
metricId=metricId,
swarmParams=swarmParams,
logger=self._log)
return metricId
def startMonitoringWithRetries():
""" :returns: metricId """
with self.connectionFactory() as conn:
with conn.begin():
repository.lockOperationExclusive(conn, repository.OperationLock.METRICS)
# Check if the metric is already monitored
matchingMetrics = repository.getCloudwatchMetricsForNameAndServer(
conn,
nameColumnValue,
canonicalResourceName,
fields=[schema.metric.c.uid, schema.metric.c.parameters],
)
for m in matchingMetrics:
parameters = htmengine.utils.jsonDecode(m.parameters)
if parameters["metricSpec"]["dimensions"] == metricSpec["dimensions"]:
msg = (
"monitorMetric: Cloudwatch modelId=%s is already "
"monitoring metric=%s on resource=%s; model=%r"
% (m.uid, nameColumnValue, canonicalResourceName, m)
)
self._log.warning(msg)
raise grok.app.exceptions.MetricAlreadyMonitored(msg, uid=m.uid)
# Add a metric row for the requested metric
metricDict = repository.addMetric(
conn,
name=nameColumnValue,
description=metricDescription,
server=canonicalResourceName,
location=resourceLocation,
poll_interval=metricPeriod,
status=MetricStatus.UNMONITORED,
datasource=self._DATASOURCE,
parameters=htmengine.utils.jsonEncode(modelSpec),
tag_name=resourceName,
)
metricId = metricDict["uid"]
self._log.info("monitorMetric: metric=%s, stats=%r", metricId, stats)
# Start monitoring
scalar_metric_utils.startMonitoring(
conn=conn, metricId=metricId, swarmParams=swarmParams, logger=self._log
)
return metricId
def _startMonitoringWithRetries(self, metricId, modelSpec, swarmParams):
""" Perform the start-monitoring operation atomically/reliably
:param metricId: unique identifier of the metric row
:param modelSpec: same as `modelSpec`` from `monitorMetric`
:param swarmParams: object returned by
scalar_metric_utils.generateSwarmParams()
:raises htmengine.exceptions.ObjectNotFoundError: if referenced metric
doesn't exist
:raises htmengine.exceptions.MetricNotSupportedError: if requested metric
isn't supported
:raises htmengine.exceptions.MetricAlreadyMonitored: if the metric is
already being monitored
"""
with self.connectionFactory() as conn:
with conn.begin():
# Lock the metric to synchronize with metric streamer; must be first
# call at start of transaction
metricObj = repository.getMetricWithUpdateLock(conn, metricId)
if metricObj.datasource != self._DATASOURCE:
raise TypeError("Not an HTM metric=%r; modelSpec=%r" %
(metricObj, modelSpec))
if metricObj.status != MetricStatus.UNMONITORED:
self._log.info(
"monitorMetric: already monitored; metric=%r",
metricObj)
raise app_exceptions.MetricAlreadyMonitored(
("Custom metric=%s is already monitored by model=%r" %
(
metricObj.name,
metricObj,
)),
uid=metricId)
# Save model specification in metric row
update = {"parameters": htmengine.utils.jsonEncode(modelSpec)}
instanceName = self.getInstanceNameForModelSpec(modelSpec)
if instanceName is not None:
update["server"] = instanceName
repository.updateMetricColumns(conn, metricId, update)
modelStarted = scalar_metric_utils.startMonitoring(
conn=conn,
metricId=metricId,
swarmParams=swarmParams,
logger=self._log)
if modelStarted:
scalar_metric_utils.sendBacklogDataToModel(
conn=conn, metricId=metricId, logger=self._log)
def _startMonitoringWithRetries(self, metricId, modelSpec, swarmParams):
""" Perform the start-monitoring operation atomically/reliably
:param metricId: unique identifier of the metric row
:param modelSpec: same as `modelSpec`` from `monitorMetric`
:param swarmParams: object returned by
scalar_metric_utils.generateSwarmParams()
:raises htmengine.exceptions.ObjectNotFoundError: if referenced metric
doesn't exist
:raises htmengine.exceptions.MetricNotSupportedError: if requested metric
isn't supported
:raises htmengine.exceptions.MetricAlreadyMonitored: if the metric is
already being monitored
"""
with self.connectionFactory() as conn:
with conn.begin():
# Lock the metric to synchronize with metric streamer; must be first
# call at start of transaction
metricObj = repository.getMetricWithUpdateLock(conn, metricId)
if metricObj.datasource != self._DATASOURCE:
raise TypeError("Not an HTM metric=%r; modelSpec=%r"
% (metricObj, modelSpec))
if metricObj.status != MetricStatus.UNMONITORED:
self._log.info("monitorMetric: already monitored; metric=%r",
metricObj)
raise app_exceptions.MetricAlreadyMonitored(
("Custom metric=%s is already monitored by model=%r"
% (metricObj.name, metricObj,)),
uid=metricId)
# Save model specification in metric row
update = {"parameters": htmengine.utils.jsonEncode(modelSpec)}
instanceName = self.getInstanceNameForModelSpec(modelSpec)
if instanceName is not None:
update["server"] = instanceName
repository.updateMetricColumns(conn, metricId, update)
modelStarted = scalar_metric_utils.startMonitoring(
conn=conn,
metricId=metricId,
swarmParams=swarmParams,
logger=self._log)
if modelStarted:
scalar_metric_utils.sendBacklogDataToModel(
conn=conn,
metricId=metricId,
logger=self._log)
