Operations | Monitoring | ITSM | DevOps | Cloud

The latest News and Information on Monitoring for Websites, Applications, APIs, Infrastructure, and other technologies.

New Beta feature: Google Cloud Private Status integration!

We are excited to announce that Google Cloud is the latest addition to our suite of Enterprise infrastructure integrations! While StatusGator has long monitored the public status of Google Cloud services, this new integration goes deeper. You can now monitor the personalized health of your specific Google Cloud projects directly within your StatusGator dashboard.

Introducing the StatusGator MCP Server

Your AI agents can now monitor, triage, and respond to cloud outages autonomously. The way enterprises manage cloud infrastructure incidents is changing. AI agents are no longer just chatbots answering questions — they’re becoming first responders in your incident management pipeline. Today, we’re launching the StatusGator MCP Server, giving AI agents direct, structured access to the full power of StatusGator’s cloud status monitoring platform.

Digital Trading: Why "Healthy Systems" Still Lose Trades

Digital trading firms operate in environments where milliseconds determine profit and loss. During volatile market conditions, platforms can appear fully operational while execution quality quietly degrades. When prices shift in so quickly, even a minor drift in your order-routing path means your competitors are exploiting the delta, while your platform appears perfectly green. For trading firms, observability is not just about uptime.

What is Error Tracking? A Beginner's Guide to Monitoring Errors in Production

Every app breaks eventually. A button stops working. A checkout flow throws an exception. An API returns a 500 error at 2 AM on a Saturday. The question isn't whether your app will have bugs; it's whether you'll find out before your users do. That's exactly what error tracking is for.

Ep 36: Do not resuscitate: Legacy tech in modern medicine

In this episode of Masters of Data, we dig into the cybersecurity nightmare that is modern healthcare IT, from ransomware attacks shutting down entire hospitals to IoT medical devices running software older than some of our passwords. We explore why healthcare organizations make such attractive targets for cybercriminals, and why the combination of life-or-death stakes, skeleton-crew security teams, and Windows-95-era equipment is a recipe for chaos.

European Compliance Requirements 2026: Key Regulations and Implementation Steps

The European regulatory landscape in 2026 looks less like a single finish line and more like a marathon with multiple checkpoints happening simultaneously. Organizations that spent years preparing for GDPR now face overlapping deadlines for AI governance, digital accessibility, operational resilience, and supply chain due diligence all converging within the same twelve-month period.

Balancing personal brand, company goals and open source in DevRel can be tricky

DevRel often means juggling goals that feel completely opposite: building trust while driving adoption, serving developers while supporting business growth. In this short, we explore why these “contradictions” are actually the secret to great Developer Relations.

Mastering the Trace Drilldown: How to Reduce MTTR with Coralogix

Stop the "Scavenger Hunt" during incidents. In this video, we walk through the new Coralogix Trace Drilldown, now GA for all customers. Learn how to move from high-level trace views to deep span insights in a single, unified workspace—without ever losing context. Whether you're investigating a latency spike or a failing microservice, the Trace Drilldown helps you answer "Where is the bottleneck?" from three different perspectives in one frame. What you’ll learn.

AI Needs Better Inputs: Why Observability Is Becoming the Foundation of Enterprise AI Maturity

Organizations across industries are accelerating their investments in AI for operations, yet the path to meaningful impact is proving far more complex than early expectations suggested. Analysts at Gartner, Forrester, Deloitte, and McKinsey continue to highlight the same structural barrier. AI cannot produce accurate predictions or safe automation when the operational data feeding it is fragmented, incomplete, or inconsistent.