#monitoring

#monitoring

Robust IT systems support uninterrupted operations through resilience, security, and proactive monitoring. CIOs report that 87% of digital-first businesses rely on automated failover systems to reduce service disruption. Continuous monitoring helps detect failures before they impact users. Recovery plans activate system redundancies and restore functions with minimal input. Automated backup schedules and patch management prevent gaps in continuity. IT managers emphasise the role of configuration management and centralised monitoring tools.

Sentry is a great tool for monitoring celery tasks, and alerting when they fail or don't run on time. But it requires a bit of work to setup properly. Below is some sample code for setting up sentry monitoring of periodic tasks, followed by an explanation. import math import sentry_sdk from celery import signals from sentry_sdk import monitor from sentry_sdk.integrations.celery import CeleryIntegration @signals.beat_init.connect # if you use beats @signals.celeryd_init.connect def init_sentry(**kwargs): sentry_sdk.init( dsn=..., integrations=[ CeleryIntegration(monitor_beat_tasks=False) ] ) @signals.worker_shutdown.connect @signals.task_postrun.connect def flush_sentry(**kwargs): sentry_sdk.flush(timeout=5) def add_periodic_task(celery, schedule, task): max_runtime = math.ceil(schedule * 4 / 60) monitor_config = { "recovery_threshold": 1, "failure_issue_threshold": 10, "checkin_margin": max_runtime, "max_runtime": max_runtime, "schedule": { "type": "interval", "value": math.ceil(schedule / 60.0) "unit": "minute" } } name = task.__name__ task = monitor(monitor_slug=name, monitor_config=monitor_config)(task) celery.add_periodic_task(schedule, celery.task(task).s(), name=name)

On August 5, a magnitude 2.7 earthquake struck near Hillsdale, New Jersey, at a depth of approximately seven miles, affecting parts of New York and New Jersey.

Centreon has introduced an open-source agent that combines IT and operational technology monitoring with OpenTelemetry support, aiming to provide unified observability for IT teams.

Visibility is a key issue in early AI agent deployments, and Agentforce 3 addresses this by enhancing control and monitoring capabilities for businesses.