merge from main

This commit is contained in:
Kenneth Kehl
2025-01-14 12:01:46 -08:00
12 changed files with 121 additions and 15 deletions

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@@ -46,7 +46,7 @@ jobs:
- name: Run scan
run: bandit -r app/ -f txt -o /tmp/bandit-output.txt --confidence-level medium
- name: Upload bandit artifact
uses: actions/upload-artifact@v3
uses: actions/upload-artifact@v4
with:
name: bandit-report
path: /tmp/bandit-output.txt

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@@ -52,7 +52,8 @@ run-celery: ## Run celery, TODO remove purge for staging/prod
-A run_celery.notify_celery worker \
--pidfile="/tmp/celery.pid" \
--loglevel=INFO \
--concurrency=4
--pool=threads
--concurrency=10
.PHONY: dead-code

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@@ -18,6 +18,7 @@ from sqlalchemy import event
from werkzeug.exceptions import HTTPException as WerkzeugHTTPException
from werkzeug.local import LocalProxy
from app import config
from app.clients import NotificationProviderClients
from app.clients.cloudwatch.aws_cloudwatch import AwsCloudwatchClient
from app.clients.document_download import DocumentDownloadClient
@@ -58,15 +59,28 @@ class SQLAlchemy(_SQLAlchemy):
def apply_driver_hacks(self, app, info, options):
sa_url, options = super().apply_driver_hacks(app, info, options)
if "connect_args" not in options:
options["connect_args"] = {}
options["connect_args"]["options"] = "-c statement_timeout={}".format(
int(app.config["SQLALCHEMY_STATEMENT_TIMEOUT"]) * 1000
)
return (sa_url, options)
db = SQLAlchemy()
# Set db engine settings here for now.
# They were not being set previous (despite environmental variables with appropriate
# sounding names) and were defaulting to low values
db = SQLAlchemy(
engine_options={
"pool_size": config.Config.SQLALCHEMY_POOL_SIZE,
"max_overflow": 10,
"pool_timeout": config.Config.SQLALCHEMY_POOL_TIMEOUT,
"pool_recycle": config.Config.SQLALCHEMY_POOL_RECYCLE,
"pool_pre_ping": True,
}
)
migrate = Migrate()
ma = Marshmallow()
notify_celery = NotifyCelery()

View File

@@ -24,6 +24,7 @@ from app.dao.jobs_dao import (
find_missing_row_for_job,
)
from app.dao.notifications_dao import (
dao_close_out_delivery_receipts,
dao_update_delivery_receipts,
notifications_not_yet_sent,
)
@@ -130,9 +131,9 @@ def check_job_status():
)
)
jobs_not_complete_after_allotted_time = (
db.session.execute(jobs_not_completed_after_allotted_time).all()
)
jobs_not_complete_after_allotted_time = db.session.execute(
jobs_not_completed_after_allotted_time
).all()
# temporarily mark them as ERROR so that they don't get picked up by future check_job_status tasks
# if they haven't been re-processed in time.
@@ -247,6 +248,8 @@ def check_for_services_with_high_failure_rates_or_sending_to_tv_numbers():
bind=True, max_retries=7, default_retry_delay=3600, name="process-delivery-receipts"
)
def process_delivery_receipts(self):
# If we need to check db settings do it here for convenience
# current_app.logger.info(f"POOL SIZE {app.db.engine.pool.size()}")
"""
Every eight minutes or so (see config.py) we run this task, which searches the last ten
minutes of logs for delivery receipts and batch updates the db with the results. The overlap
@@ -261,7 +264,7 @@ def process_delivery_receipts(self):
cloudwatch = AwsCloudwatchClient()
cloudwatch.init_app(current_app)
start_time = aware_utcnow() - timedelta(minutes=10)
start_time = aware_utcnow() - timedelta(minutes=3)
end_time = aware_utcnow()
delivered_receipts, failed_receipts = cloudwatch.check_delivery_receipts(
start_time, end_time
@@ -283,3 +286,10 @@ def process_delivery_receipts(self):
current_app.logger.error(
"Failed process delivery receipts after max retries"
)
@notify_celery.task(
bind=True, max_retries=2, default_retry_delay=3600, name="cleanup-delivery-receipts"
)
def cleanup_delivery_receipts(self):
dao_close_out_delivery_receipts()

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@@ -13,8 +13,7 @@ AWS_CLIENT_CONFIG = Config(
"addressing_style": "virtual",
},
use_fips_endpoint=True,
# This is the default but just for doc sake
max_pool_connections=10,
max_pool_connections=50, # This should be equal or greater than our celery concurrency
)

View File

@@ -81,7 +81,7 @@ class Config(object):
SQLALCHEMY_DATABASE_URI = cloud_config.database_url
SQLALCHEMY_RECORD_QUERIES = False
SQLALCHEMY_TRACK_MODIFICATIONS = False
SQLALCHEMY_POOL_SIZE = int(getenv("SQLALCHEMY_POOL_SIZE", 5))
SQLALCHEMY_POOL_SIZE = int(getenv("SQLALCHEMY_POOL_SIZE", 40))
SQLALCHEMY_POOL_TIMEOUT = 30
SQLALCHEMY_POOL_RECYCLE = 300
SQLALCHEMY_STATEMENT_TIMEOUT = 1200
@@ -200,7 +200,12 @@ class Config(object):
},
"process-delivery-receipts": {
"task": "process-delivery-receipts",
"schedule": timedelta(minutes=8),
"schedule": timedelta(minutes=2),
"options": {"queue": QueueNames.PERIODIC},
},
"cleanup-delivery-receipts": {
"task": "cleanup-delivery-receipts",
"schedule": timedelta(minutes=82),
"options": {"queue": QueueNames.PERIODIC},
},
"expire-or-delete-invitations": {

View File

@@ -44,8 +44,9 @@ def dao_get_job_by_service_id_and_job_id(service_id, job_id):
def dao_get_unfinished_jobs():
stmt = select(Job).where(Job.processing_finished.is_(None))
return db.session.execute(stmt).all()
stmt = select(Job).filter(Job.processing_finished.is_(None))
return db.session.execute(stmt).scalars().all()
def dao_get_jobs_by_service_id(

View File

@@ -1,5 +1,6 @@
import json
from datetime import timedelta
from time import time
from flask import current_app
from sqlalchemy import (
@@ -745,6 +746,7 @@ def get_service_ids_with_notifications_on_date(notification_type, date):
def dao_update_delivery_receipts(receipts, delivered):
start_time_millis = time() * 1000
new_receipts = []
for r in receipts:
if isinstance(r, str):
@@ -791,3 +793,27 @@ def dao_update_delivery_receipts(receipts, delivered):
)
db.session.execute(stmt)
db.session.commit()
elapsed_time = (time() * 1000) - start_time_millis
current_app.logger.info(
f"#loadtestperformance batch update query time: \
updated {len(receipts)} notification in {elapsed_time} ms"
)
def dao_close_out_delivery_receipts():
THREE_DAYS_AGO = utc_now() - timedelta(minutes=3)
stmt = (
update(Notification)
.where(
Notification.status == NotificationStatus.PENDING,
Notification.sent_at < THREE_DAYS_AGO,
)
.values(status=NotificationStatus.FAILED, provider_response="Technical Failure")
)
result = db.session.execute(stmt)
db.session.commit()
if result:
current_app.logger.info(
f"Marked {result.rowcount} notifications as technical failures"
)

View File

@@ -577,7 +577,16 @@ class Service(db.Model, Versioned):
return self.inbound_number.number
def get_default_sms_sender(self):
default_sms_sender = [x for x in self.service_sms_senders if x.is_default]
# notify-api-1513 let's try a minimalistic fix
# to see if we can get the right numbers back
default_sms_sender = [
x
for x in self.service_sms_senders
if x.is_default and x.service_id == self.id
]
current_app.logger.info(
f"#notify-api-1513 senders for service {self.name} are {self.service_sms_senders}"
)
return default_sms_sender[0].sms_sender
def get_default_reply_to_email_address(self):

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@@ -0,0 +1,23 @@
# Make best use of celery worker pools
Status: N/A
Date: N/A
### Context
Our API application started with initial celery pool support of 'prefork' (the default) and concurrency of 4. We continuously encountered instability, which we initially attributed to a resource leak. As a result of this we added the configuration `worker-max-tasks-per-child=500` which is a best practice. When we ran a load test of 25000 simulated messages, however, we continued to see stability issues, amounting to a crash of the app after 4 hours requiring a restage. Based on running `cf app notify-api-production` and observing that `cpu entitlement` was off the charts at 10000% to 12000% for the works, and after doing some further reading, we came to the conclusion that perhaps `prefork` pool support is not the best type of pool support for the API application.
The problem with `prefork` is that each process has a tendency to hang onto the CPU allocated to it, even if it is not being used. Our application is not computationally intensive and largely consists of downloading strings from S3, parsing the strings, and sending them out as SMS messages. Based on the determination that our app is likely I/O bound, we elected to do an experiment where we changed pool support to `threads` and increased concurrency to `10`. The expectation is that memory usage will decrease and CPU usage will decrease and the app will not become unavailable.
### Decision
### Consequences
### Author
@kenkehl
### Stakeholders
@ccostino
@stvnrlly
### Next Steps
- Run an after-hours load test with production configured to --pool=threads and --concurrency=10 (concurrency can be cautiously increased once we know it works)

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@@ -26,7 +26,7 @@ applications:
- type: worker
instances: ((worker_instances))
memory: ((worker_memory))
command: newrelic-admin run-program celery -A run_celery.notify_celery worker --loglevel=INFO --concurrency=4
command: newrelic-admin run-program celery -A run_celery.notify_celery worker --loglevel=INFO --pool=threads --concurrency=10 --prefetch-multiplier=2
- type: scheduler
instances: 1
memory: ((scheduler_memory))

View File

@@ -11,6 +11,7 @@ from sqlalchemy.orm.exc import NoResultFound
from app import db
from app.dao.notifications_dao import (
dao_close_out_delivery_receipts,
dao_create_notification,
dao_delete_notifications_by_id,
dao_get_last_notification_added_for_job_id,
@@ -2030,6 +2031,23 @@ def test_update_delivery_receipts(mocker):
assert "provider_response" in kwargs
def test_close_out_delivery_receipts(mocker):
mock_session = mocker.patch("app.dao.notifications_dao.db.session")
mock_update = MagicMock()
mock_where = MagicMock()
mock_values = MagicMock()
mock_update.where.return_value = mock_where
mock_where.values.return_value = mock_values
mock_session.execute.return_value = None
with patch("app.dao.notifications_dao.update", return_value=mock_update):
dao_close_out_delivery_receipts()
mock_update.where.assert_called_once()
mock_where.values.assert_called_once()
mock_session.execute.assert_called_once_with(mock_values)
mock_session.commit.assert_called_once()
@pytest.mark.parametrize(
"created_at_utc,date_to_check,expected_count",
[