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feat(alerts): CH search

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Taha Yassine Kraiem 2022-08-26 16:27:32 +01:00
parent 8e4f48678f
commit aa0a24f56a
5 changed files with 218 additions and 1 deletions
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1
ee/api/.gitignore vendored
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@ -184,6 +184,7 @@ Pipfile
/chalicelib/core/announcements.py
/chalicelib/core/autocomplete.py
/chalicelib/core/collaboration_slack.py
/chalicelib/core/countries.py
/chalicelib/core/errors.py
/chalicelib/core/errors_favorite.py
/chalicelib/core/events.py

6
ee/api/chalicelib/core/__init__.py
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@ -26,3 +26,9 @@ if config("EXP_METRICS", cast=bool, default=False):
from . import metrics_exp as metrics
else:
from . import metrics as metrics
if config("EXP_ALERTS", cast=bool, default=False):
print(">>> Using experimental alerts")
from . import alerts_processor_exp as alerts_processor
else:
from . import alerts_processor as alerts_processor

208
ee/api/chalicelib/core/alerts_processor_exp.py Normal file
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@ -0,0 +1,208 @@
import decimal
import logging
import schemas
from chalicelib.core import alerts_listener, alerts_processor
from chalicelib.core import sessions, alerts
from chalicelib.utils import pg_client, ch_client
from chalicelib.utils.TimeUTC import TimeUTC
LeftToDb = {
schemas.AlertColumn.performance__dom_content_loaded__average: {
"table": "events.pages INNER JOIN public.sessions USING(session_id)",
"formula": "COALESCE(AVG(NULLIF(dom_content_loaded_time ,0)),0)"},
schemas.AlertColumn.performance__first_meaningful_paint__average: {
"table": "events.pages INNER JOIN public.sessions USING(session_id)",
"formula": "COALESCE(AVG(NULLIF(first_contentful_paint_time,0)),0)"},
schemas.AlertColumn.performance__page_load_time__average: {
"table": "events.pages INNER JOIN public.sessions USING(session_id)", "formula": "AVG(NULLIF(load_time ,0))"},
schemas.AlertColumn.performance__dom_build_time__average: {
"table": "events.pages INNER JOIN public.sessions USING(session_id)",
"formula": "AVG(NULLIF(dom_building_time,0))"},
schemas.AlertColumn.performance__speed_index__average: {
"table": "events.pages INNER JOIN public.sessions USING(session_id)", "formula": "AVG(NULLIF(speed_index,0))"},
schemas.AlertColumn.performance__page_response_time__average: {
"table": "events.pages INNER JOIN public.sessions USING(session_id)",
"formula": "AVG(NULLIF(response_time,0))"},
schemas.AlertColumn.performance__ttfb__average: {
"table": "events.pages INNER JOIN public.sessions USING(session_id)",
"formula": "AVG(NULLIF(first_paint_time,0))"},
schemas.AlertColumn.performance__time_to_render__average: {
"table": "events.pages INNER JOIN public.sessions USING(session_id)",
"formula": "AVG(NULLIF(visually_complete,0))"},
schemas.AlertColumn.performance__image_load_time__average: {
"table": "events.resources INNER JOIN public.sessions USING(session_id)",
"formula": "AVG(NULLIF(resources.duration,0))", "condition": "type='img'"},
schemas.AlertColumn.performance__request_load_time__average: {
"table": "events.resources INNER JOIN public.sessions USING(session_id)",
"formula": "AVG(NULLIF(resources.duration,0))", "condition": "type='fetch'"},
schemas.AlertColumn.resources__load_time__average: {
"table": "events.resources INNER JOIN public.sessions USING(session_id)",
"formula": "AVG(NULLIF(resources.duration,0))"},
schemas.AlertColumn.resources__missing__count: {
"table": "events.resources INNER JOIN public.sessions USING(session_id)",
"formula": "COUNT(DISTINCT url_hostpath)", "condition": "success= FALSE"},
schemas.AlertColumn.errors__4xx_5xx__count: {
"table": "events.resources INNER JOIN public.sessions USING(session_id)", "formula": "COUNT(session_id)",
"condition": "status/100!=2"},
schemas.AlertColumn.errors__4xx__count: {"table": "events.resources INNER JOIN public.sessions USING(session_id)",
"formula": "COUNT(session_id)", "condition": "status/100=4"},
schemas.AlertColumn.errors__5xx__count: {"table": "events.resources INNER JOIN public.sessions USING(session_id)",
"formula": "COUNT(session_id)", "condition": "status/100=5"},
schemas.AlertColumn.errors__javascript__impacted_sessions__count: {
"table": "events.resources INNER JOIN public.sessions USING(session_id)",
"formula": "COUNT(DISTINCT session_id)", "condition": "success= FALSE AND type='script'"},
schemas.AlertColumn.performance__crashes__count: {
"table": "(SELECT *, start_ts AS timestamp FROM public.sessions WHERE errors_count > 0) AS sessions",
"formula": "COUNT(DISTINCT session_id)", "condition": "errors_count > 0"},
schemas.AlertColumn.errors__javascript__count: {
"table": "events.errors INNER JOIN public.errors AS m_errors USING (error_id)",
"formula": "COUNT(DISTINCT session_id)", "condition": "source='js_exception'", "joinSessions": False},
schemas.AlertColumn.errors__backend__count: {
"table": "events.errors INNER JOIN public.errors AS m_errors USING (error_id)",
"formula": "COUNT(DISTINCT session_id)", "condition": "source!='js_exception'", "joinSessions": False},
}
# This is the frequency of execution for each threshold
TimeInterval = {
15: 3,
30: 5,
60: 10,
120: 20,
240: 30,
1440: 60,
}
def Build(a):
params = {"project_id": a["projectId"], "now": TimeUTC.now()}
full_args = {}
j_s = True
if a["seriesId"] is not None:
a["filter"]["sort"] = "session_id"
a["filter"]["order"] = schemas.SortOrderType.desc
a["filter"]["startDate"] = -1
a["filter"]["endDate"] = TimeUTC.now()
full_args, query_part = sessions.search_query_parts(
data=schemas.SessionsSearchPayloadSchema.parse_obj(a["filter"]), error_status=None, errors_only=False,
issue=None, project_id=a["projectId"], user_id=None, favorite_only=False)
subQ = f"""SELECT COUNT(session_id) AS value
{query_part}"""
else:
colDef = LeftToDb[a["query"]["left"]]
subQ = f"""SELECT {colDef["formula"]} AS value
FROM {colDef["table"]}
WHERE project_id = %(project_id)s
{"AND " + colDef["condition"] if colDef.get("condition") is not None else ""}"""
j_s = colDef.get("joinSessions", True)
q = f"""SELECT coalesce(value,0) AS value, coalesce(value,0) {a["query"]["operator"]} {a["query"]["right"]} AS valid"""
if a["detectionMethod"] == schemas.AlertDetectionMethod.threshold:
if a["seriesId"] is not None:
q += f""" FROM ({subQ}) AS stat"""
else:
q += f""" FROM ({subQ} AND timestamp>=%(startDate)s AND timestamp<=%(now)s
{"AND sessions.start_ts >= %(startDate)s AND sessions.start_ts <= %(now)s" if j_s else ""}) AS stat"""
params = {**params, **full_args, "startDate": TimeUTC.now() - a["options"]["currentPeriod"] * 60 * 1000}
else:
if a["options"]["change"] == schemas.AlertDetectionChangeType.change:
if a["seriesId"] is not None:
sub2 = subQ.replace("%(startDate)s", "%(timestamp_sub2)s").replace("%(endDate)s", "%(startDate)s")
sub1 = f"SELECT (({subQ})-({sub2})) AS value"
q += f" FROM ( {sub1} ) AS stat"
params = {**params, **full_args,
"startDate": TimeUTC.now() - a["options"]["currentPeriod"] * 60 * 1000,
"timestamp_sub2": TimeUTC.now() - 2 * a["options"]["currentPeriod"] * 60 * 1000}
else:
sub1 = f"""{subQ} AND timestamp>=%(startDate)s
{"AND sessions.start_ts >= %(startDate)s" if j_s else ""}"""
params["startDate"] = TimeUTC.now() - a["options"]["currentPeriod"] * 60 * 1000
sub2 = f"""{subQ} AND timestamp<%(startDate)s
AND timestamp>=%(timestamp_sub2)s
{"AND sessions.start_ts < %(startDate)s AND sessions.start_ts >= %(timestamp_sub2)s" if j_s else ""}"""
params["timestamp_sub2"] = TimeUTC.now() - 2 * a["options"]["currentPeriod"] * 60 * 1000
sub1 = f"SELECT (( {sub1} )-( {sub2} )) AS value"
q += f" FROM ( {sub1} ) AS stat"
else:
if a["seriesId"] is not None:
sub2 = subQ.replace("%(startDate)s", "%(timestamp_sub2)s").replace("%(endDate)s", "%(startDate)s")
sub1 = f"SELECT (({subQ})/NULLIF(({sub2}),0)-1)*100 AS value"
q += f" FROM ({sub1}) AS stat"
params = {**params, **full_args,
"startDate": TimeUTC.now() - a["options"]["currentPeriod"] * 60 * 1000,
"timestamp_sub2": TimeUTC.now() \
- (a["options"]["currentPeriod"] + a["options"]["currentPeriod"]) \
* 60 * 1000}
else:
sub1 = f"""{subQ} AND timestamp>=%(startDate)s
{"AND sessions.start_ts >= %(startDate)s" if j_s else ""}"""
params["startDate"] = TimeUTC.now() - a["options"]["currentPeriod"] * 60 * 1000
sub2 = f"""{subQ} AND timestamp<%(startDate)s
AND timestamp>=%(timestamp_sub2)s
{"AND sessions.start_ts < %(startDate)s AND sessions.start_ts >= %(timestamp_sub2)s" if j_s else ""}"""
params["timestamp_sub2"] = TimeUTC.now() \
- (a["options"]["currentPeriod"] + a["options"]["currentPeriod"]) * 60 * 1000
sub1 = f"SELECT (({sub1})/NULLIF(({sub2}),0)-1)*100 AS value"
q += f" FROM ({sub1}) AS stat"
return q, params
def process():
notifications = []
all_alerts = alerts_listener.get_all_alerts()
with pg_client.PostgresClient() as cur, ch_client.ClickHouseClient() as curc:
for alert in all_alerts:
if True or alerts_processor.can_check(alert):
logging.info(f"Querying alertId:{alert['alertId']} name: {alert['name']}")
query, params = Build(alert)
query = cur.mogrify(query, params)
logging.debug(alert)
logging.debug(query)
try:
print("------------------Alerts")
print(alert)
print(query)
print("------------------")
continue
cur.execute(query)
result = cur.fetchone()
if result["valid"]:
logging.info("Valid alert, notifying users")
notifications.append({
"alertId": alert["alertId"],
"tenantId": alert["tenantId"],
"title": alert["name"],
"description": f"has been triggered, {alert['query']['left']} = {round(result['value'], 2)} ({alert['query']['operator']} {alert['query']['right']}).",
"buttonText": "Check metrics for more details",
"buttonUrl": f"/{alert['projectId']}/metrics",
"imageUrl": None,
"options": {"source": "ALERT", "sourceId": alert["alertId"],
"sourceMeta": alert["detectionMethod"],
"message": alert["options"]["message"], "projectId": alert["projectId"],
"data": {"title": alert["name"],
"limitValue": alert["query"]["right"],
"actualValue": float(result["value"]) \
if isinstance(result["value"], decimal.Decimal) \
else result["value"],
"operator": alert["query"]["operator"],
"trigger": alert["query"]["left"],
"alertId": alert["alertId"],
"detectionMethod": alert["detectionMethod"],
"currentPeriod": alert["options"]["currentPeriod"],
"previousPeriod": alert["options"]["previousPeriod"],
"createdAt": TimeUTC.now()}},
})
except Exception as e:
logging.error(f"!!!Error while running alert query for alertId:{alert['alertId']}")
logging.error(str(e))
logging.error(query)
if len(notifications) > 0:
cur.execute(
cur.mogrify(f"""UPDATE public.alerts
SET options = options||'{{"lastNotification":{TimeUTC.now()}}}'::jsonb
WHERE alert_id IN %(ids)s;""", {"ids": tuple([n["alertId"] for n in notifications])}))
if len(notifications) > 0:
alerts.process_notifications(notifications)

1
ee/api/clean.sh
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@ -5,6 +5,7 @@ rm -rf ./chalicelib/core/alerts_processor.py
rm -rf ./chalicelib/core/announcements.py
rm -rf ./chalicelib/core/autocomplete.py
rm -rf ./chalicelib/core/collaboration_slack.py
rm -rf ./chalicelib/core/countries.py
rm -rf ./chalicelib/core/errors.py
rm -rf ./chalicelib/core/errors_favorite.py
rm -rf ./chalicelib/core/events.py

3
ee/api/env.default
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@ -65,4 +65,5 @@ EXP_SESSIONS_SEARCH=true
EXP_AUTOCOMPLETE=true
EXP_ERRORS_SEARCH=true
EXP_METRICS=true
EXP_7D_MV=true
EXP_7D_MV=true
EXP_ALERTS=true