Operations | Monitoring | ITSM | DevOps | Cloud

Most of what shows up in a JavaScript error tracker isn't a bug you need to fix; it's noise. Third-party scripts, browser extensions, and edge-case devices flood the feed, and the errors actually hurting your users get lost in it. This guide covers 12 production-tested practices for setting up JavaScript error monitoring that surfaces real, user-impacting bugs, not console spam, plus the error types you'll run into most often and how to configure alerting so your team stops getting paged for noise.

Your website or API rarely depends on just one thing. Cloud providers, CDNs, DNS, identity services, and other third-party platforms can all affect availability. That’s why we’ve added a new Dependencies tab for Website, Ping, and Custom monitors, making it easy to document the services your infrastructure relies on and quickly reference them during an incident.

Keeping meeting rooms ready for the next call is just as important as monitoring your cloud services. That’s why we’re excited to introduce our new Zoom Rooms integration. With a single connection, StatusGator continuously monitors the connectivity of your Zoom Rooms deployment, making it easy to spot offline rooms and device issues before they disrupt meetings.

A long requested feature, Bulk import, is now live on StatusGator. Paste a list of service names or upload a.txt or.csv, and we will match them against our directory of nearly 10,000 services so you can add every monitor you need at once instead of searching for them one at a time. You will find it in the top right corner of the Service Directory above the Search bar.

In July, StatusGator detected 938 Early Warning Signals across SaaS, cloud infrastructure, AI platforms, and business applications. Of those incidents, 187 (19.94%) were eventually acknowledged by providers, while 751 (80.06%) were never officially acknowledged at all.

Most engineering leaders are drowning in data but starved for insight. We have dashboards full of metrics, but they often create more questions than answers and rarely tell us what to do next. In the age of AI, where development velocity is accelerating at an unprecedented rate, this problem is only getting worse. Shipping code faster than you can fix it is an existential risk, and a dashboard that doesn't lead to action is just a distraction.

Cloud outage preparedness stopped being a nice-to-have this month. In a span of roughly 48 hours, Microsoft Azure lost a big chunk of its West US footprint and Amazon Web Services dropped connectivity between its us-west-2 region in Oregon and the Seattle metro. The AWS event alone rippled outward and knocked DoorDash, Reddit, Hulu, Apple Pay, Snapchat, Fortnite, and the PlayStation Network offline for millions of users, according to incident trackers. Neither outage was caused by anything exotic.

A recent IDC Spotlight report based on a survey of 685 public sector respondents found that 72% describe scaling AI from pilot to production as "very" or "somewhat" difficult.¹ Choosing the right model is only part of the challenge. Agencies also need to get their data ready for AI.