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Catchpoint Blog

SRE Report: AI optimism and the economics of effort SRE Report: Why fast is what users trust SRE Report 2026: What surprised us, what didn't, and why the gaps matter most The SRE Report 2026: Defensible Ns Why Synthetic Tracing Delivers Better Data, Not Just More Data A New Chapter: LogicMonitor + Catchpoint – A Personal Note from Mehdi Mezmo + Catchpoint deliver observability SREs can rely on The four pillars holding up your digital business, and what happens when they crumble When payments pause: lessons from a global payments outage Observability 2025 Decoded: What the DZone Report Means for SLO-Driven Ops The next evolution of WebPageTest has arrived, and it’s a game-changer The Monitoring Blind Spot That Could Cost You Black Friday Powering Mexico’s Digital Future: Expanded Internet Observability with Catchpoint The Next Chapter of WebPageTest: Your New Experience Starts Soon SRE Report Retrospectives — Have AIOps Predictions Held Up? When BGP becomes UX: The inside story of a SaaS routing decision gone wrong (or right) Session Replay explained: A guide to seeing digital experience through your user’s eyes Making the invisible visible: Are your cloud firewalls and DDoS protection really working? Why it’s time to move beyond APM: Monitoring from the user’s perspective When metrics mislead: Inside the 2025 Retail Web Performance Benchmark The vendor trap: why your next outage won’t be your fault—but will be your problem LLMs don’t stand still: How to monitor and trust the models powering your AI Semantic Caching: What We Measured, Why It Matters The Annual SRE Survey Is Open—We Want to Hear from You Observability isn’t about the tool. It’s about the truth Invisible dependencies, visible impact: Lessons from the Google Cloud outage Real-time detection of BGP blackholing and prefix hijacks Leading analyst firm reveals the real cost of internet disruptions The Power of Over 3000 Intelligent Observability Agents Monitoring in the Age of Complexity: 5 Assumptions CIOs Need to Rethink Why Intelligent Traffic Steering is Critical for Performance and Cost Optimization Retail digital performance event recap: Key insights from IBM & Catchpoint Zendesk outage: A case for proactive monitoring and faster incident response Silence during chaos: Why the X outage is a call to arms for proactive monitoring The $1 Million Lesson: Building a Culture of Quality Through SLAs When AI tools fail: How to map your AI dependencies for proactive visibility Why Super Bowl 2025 was a triumph for Internet Resilience Why Internet Performance Monitoring is the new health check for IT organizations Why use Playwright in Catchpoint for synthetic monitoring Introducing WebPageTest Expert Plan: Real-Time Insights, Synthetic + RUM together in One Platform The shift to digital: How businesses are reshaping their priorities for 2025 The SRE Report 2025's Call to Action Monitoring in the Age of the Internet: DEM, IPM, and APM—What You Need to Know SSL Monitoring, Trust, and McLOVIN Performing for the holidays: Look beyond uptime for season sales success Lessons from Microsoft’s office 365 Outage: The Importance of third-party monitoring Web Performance Experts Look into the Future of Web Performance The hidden challenges of Internet Resilience: Key insights from 2024 report When SSL Issues aren’t just about SSL: A deep dive into the TIBCO Mashery outage The curious case of Marriott and the untold impact of web performance on revenue Preparing for the unexpected: Lessons from the AJIO and Jio Outage It’s time to stop neglecting the elephant in the room: Performance Matters! The Need for Speed: Highlights from IBM and Catchpoint’s Global DNS Performance Study Learnings from ServiceNow’s Proactive Response to a Network Breakdown Webinar Recap: Taking Web Performance to the Next Level Use the Catchpoint Terraform Provider in your CI/CD workflows Is the Internet ready for L4S? Takeaways from the CrowdStrike outage: third-parties can pose risk July 19th global IT outage reminds us of digital complexity 5 Actions you can take to improve digital performance 2024: A banner year for Internet Resilience APM vs Observability: Both-and, not either-or AppAssure: Ensuring the resilience of your Tier-1 applications just became easier APM vs observability: why your definitions are broken APM vs Observability: What comes next? APM vs Observability: Observing beyond APM Achieving stability with agility in your CI/CD pipeline AWS Outage: How do you prepare for the failure of your own safety net? Agentic AI: Powerful But Fragile—What You Need to Know Catch frustration before it costs you: New tools for a better user experience Catchpoint Expands Observability Network to Barcelona: A Growing Internet Hub Catchpoint Peak Performance Summit 2025: Redefining Observability for the Outcome Economy Catchpoint named a leader in the 2024 Gartner® Magic Quadrant™ for Digital Experience Monitoring Consolidation and Modernization in Enterprise Observability Connected Devices: Unlocking the next frontier of Internet Performance Monitoring Cloud Monitoring's Blind Spot: The User Perspective Cloudflare’s Resolver Outage: More Than Just DNS Cloudflare outage: another wake-up call for resilience planning Demystifying API Monitoring and Testing with IPM Creating the IPM Category: Catchpoint’s Journey to Leadership and the LogicMonitor Era Critical Requirements for Modern API Monitoring Customer Survey 2024: Unveiling insights and impact Did Delta's slow web performance signal trouble before CrowdStrike? Diagnosing Wi-Fi failures that traditional tools miss: a case study DNS misconfiguration can happen to anyone - the question is how fast can you detect it? ECN explained: Navigate congestion for faster, smoother data delivery Don’t get caught in the dark: Lessons from a Lumen & AWS micro-outage Escalating risk, shrinking margins: The 2025 Internet Resilience Report From refresh to results: the metrics that shaped Election Day 2024 coverage Fast and furious: The importance of performance in the digital age Getting Started with Traceroute From the source to the edge: the six agent types you can’t ignore From SEO to AEO: Why Web Performance Is the Key to AI Search Success Going for gold: Testing the resilience of Olympic websites Here’s the proof: What the fastest sites on the web have in common Google’s Agent-to-Agent (A2A) Protocol is here—Now Let’s Make it Observable How IPM helped a top tech brand catch an OpenAI outage before it became a crisis How SAP achieved world-class uptime through modern observability How to Monitor AI Agents in Commerce Systems
How AI Turns Monitoring From “What Now?” Into “What’s Next?”
2026-05-31 · via Catchpoint Blog

in this blog post

It's 3 AM. Your phone starts buzzing with alerts, and you stumble to your laptop only to be greeted by a dashboard that looks like the control panel of a nuclear reactor in meltdown: Red lights everywhere. Numbers that should be green are decidedly not green. And your brain, still foggy from sleep, is asking the most fundamental question in all of IT operations: "Okay, yes, there's clearly a problem... but, now what?"

Anyone who's ever been responsible for keeping digital services running has asked that question at one time or another. Whatever time of day it happens, the effect is the same: your system is down and you need answers fast. But here's the uncomfortable truth we don't often admit out loud: even the best monitoring tools, for all their sophistication and insight-generating prowess, can be frustratingly unintuitive and overwhelming in the heat of an incident.

Why knowing the problem isn’t enough in monitoring

Look, we've built an incredibly powerful Internet Performance Monitoring (IPM) platform. We can tell you with surgical precision exactly what's happening across your entire Internet stack, from synthetic transactions to real user monitoring, from BGP routing to DNS resolution times. We can show you dependency maps of every DNS, CDN, and API connection in your service delivery chain.

But here's what we've realized from listening to our customers: knowing what is broken and knowing what to do about it are two entirely different things.

It's like having the world's most detailed medical diagnostic equipment that can tell you exactly which cells in your body are misbehaving, but then leaving you to figure out whether you need aspirin or emergency surgery. The data is there. The insights are there. But the bridge between "here's what's wrong" and "here's how you fix it" more often than not, has been built by tribal knowledge, experience, and a lot of frantic Slack messages to whoever's been around long enough to remember the last time this particular flavor of chaos occurred.

This gap is exactly what we set out to close with our latest platform enhancements: AI-powered Root Cause Analysis (RCA) and Advisor.  

What does Root Cause Analysis do?

Our new RCA capability quickly identifies outages and pinpoints the primary service responsible for an issue. Think of it as your middle-of-the-night detective. When everything's on fire and your brain is running on caffeine and adrenaline, RCA cuts through the noise to tell you, in plain English, what's actually causing the problem. No more manually inspecting every dependency in your service chain. No more playing "guess the culprit" while your users are getting error pages.

It leverages Internet Stack Map — the family tree of all your digital dependencies — and combines that with event intelligence to automatically analyze backend waterfall data. The result? When something breaks, you don't just know that it's broken, you know what's breaking it.

What about Catchpoint Advisor?

A screenshot of a computerAI-generated content may be incorrect.

Catchpoint Advisor is like having that one senior engineer who's been around forever and somehow always knows exactly where the skeletons are buried, which wire to jiggle, and how to keep the show rolling. In this context, it looks at your monitoring setup and makes intelligent recommendations about coverage gaps, suggests additional tests, and even pre-configures them for you.

How do our new AI capabilities actually work?

Both Root Cause Analysis and Advisor work contextually within your existing Stack Map. The AI isn't making wild guesses based on generic patterns - it's analyzing the specific services in your environment, during your timeline, using your actual data.

When RCA kicks in, it's examining waterfall data to determine whether a service outage is actually impacting your primary service. It only surfaces root causes that are relevant to what you're looking at, when you're looking at it. That means less noise and fewer false positives.

The Advisor recommendations are equally precise. They suggest adding existing – or new - tests you might have overlooked, recommend Internet Sonar services for dependencies you're not yet monitoring, and can even pre-configure new tests with alerts already set up. We're talking about HTTP, Chrome browser tests, SSL checks, traceroutes, DNS monitoring, and more.  

And here's the kicker: these aren't buried in some separate AI dashboard you'll never remember to check. They appear automatically in your Stack Map interface when you have relevant data. No special enablement requests, no additional costs beyond what you're already using Stack Map for.

AI that actually solves problems, not create them

This is where I need to be crystal clear about something: we're not jumping on the AI bandwagon because it's trendy. As our CEO Mehdi Daoudi put it, "AI should remove complexity, not add to it." And our Chief Product Officer Matt Izzo was even more direct: "There is a lot of AI-washing in the industry, we do not want to add AI capabilities just to check the box."

Our new enhancements exist because our customers were telling us that they needed help making sense of what their monitoring data was actually telling them. They also aren’t our first rodeo with practical AI. In November 2023, we announced a raft of AI capabilities that solve real problems, including:  

  • Internet Sonar answers the question “Is it us or something else?” with real-time global Internet health insights.
  • Website Experiments uncovers performance improvement opportunities and validates them without requiring code changes, powered by WebPageTest.
  • Smartboards automatically spotlight performance issues affecting user experience and consolidate them into a single interactive view.
  • Trend Shift detects critical trend shifts in your IPM data before they escalate into incidents, serving as an early warning system.
  • User Engagement Estimator models “what-if” scenarios (e.g., impact of reducing page load times) to predict ROI from optimization efforts.
  • Experience Scores consolidate multiple disparate metrics into a single index for a clear top-line view of user experience.
  • SLI/SLO Tracking uses AI to remove guesswork and help operations teams stay confident about meeting service objectives.

In July 2025, we took another major step forward with two new solutions designed for the age of AI-driven workflows:

  • AI Assistant Reliability Monitoring: Gives IT teams visibility into the health of AI APIs, LLMs, and chatbots, detecting latency, outages, or dependency failures before they impact users.
  • Agentic AI Resilience Monitoring: Provides full-stack visibility for complex, autonomous AI workflows that rely on multiple dependencies, ensuring uptime, speed, and resilience.

RCA and Advisor are the next logical enhancements to our IPM platform, guiding you after detection by pinpointing the cause and recommending what to do about it.

Why does this matter now?

Look, every monitoring vendor is talking about AI these days. Most of them are adding chatbots that can summarize your dashboards or generate reports that look impressive in PowerPoint presentations. That's not what we're doing here.

What we're doing is solving the fundamental problem that keeps SREs, DevOps engineers, and IT ops teams awake at night: the gap between detection and resolution. The space between "I see the problem" and "I know what to do about it." The difference between mean time to detect and mean time to repair.

The AI capabilities we've built so far represent the foundation of something bigger – a monitoring platform that doesn't just tell you what's happening, but helps you understand what it means and guides you toward resolution, especially when you're tired, stressed, and needing answers fast.

The 3 AM call will always be part of running Internet-scale services. What’s changing is our ability to answer the question that comes right after: “What’s wrong, and what do we do about it?”

At Catchpoint, our answer increasingly is: "Here's exactly what's wrong, and here's exactly what you should do about it."

And honestly? That feels like progress.

Learn more about AI monitoring

Ready to try it yourself?

Explore our interactive tours and see how Catchpoint can help you bridge the gap between detection and resolution.

Summary

Monitoring tools often overwhelm teams with data but fail to bridge the gap between detection and resolution. Catchpoint’s new AI-powered Root Cause Analysis (RCA) and Advisor close that gap by pinpointing the exact cause of outages and recommending next steps. Unlike generic AI add-ons, these features analyze real service dependencies within your Internet Stack Map, cut noise, reduce false positives, and surface actionable insights right where teams work. This continues Catchpoint’s push to make monitoring not just powerful, but practical—helping IT teams go from “What’s wrong?” to “Here’s how to fix it” faster, even at 3 AM.

It's 3 AM. Your phone starts buzzing with alerts, and you stumble to your laptop only to be greeted by a dashboard that looks like the control panel of a nuclear reactor in meltdown: Red lights everywhere. Numbers that should be green are decidedly not green. And your brain, still foggy from sleep, is asking the most fundamental question in all of IT operations: "Okay, yes, there's clearly a problem... but, now what?"

Anyone who's ever been responsible for keeping digital services running has asked that question at one time or another. Whatever time of day it happens, the effect is the same: your system is down and you need answers fast. But here's the uncomfortable truth we don't often admit out loud: even the best monitoring tools, for all their sophistication and insight-generating prowess, can be frustratingly unintuitive and overwhelming in the heat of an incident.

Why knowing the problem isn’t enough in monitoring

Look, we've built an incredibly powerful Internet Performance Monitoring (IPM) platform. We can tell you with surgical precision exactly what's happening across your entire Internet stack, from synthetic transactions to real user monitoring, from BGP routing to DNS resolution times. We can show you dependency maps of every DNS, CDN, and API connection in your service delivery chain.

But here's what we've realized from listening to our customers: knowing what is broken and knowing what to do about it are two entirely different things.

It's like having the world's most detailed medical diagnostic equipment that can tell you exactly which cells in your body are misbehaving, but then leaving you to figure out whether you need aspirin or emergency surgery. The data is there. The insights are there. But the bridge between "here's what's wrong" and "here's how you fix it" more often than not, has been built by tribal knowledge, experience, and a lot of frantic Slack messages to whoever's been around long enough to remember the last time this particular flavor of chaos occurred.

This gap is exactly what we set out to close with our latest platform enhancements: AI-powered Root Cause Analysis (RCA) and Advisor.  

What does Root Cause Analysis do?

Our new RCA capability quickly identifies outages and pinpoints the primary service responsible for an issue. Think of it as your middle-of-the-night detective. When everything's on fire and your brain is running on caffeine and adrenaline, RCA cuts through the noise to tell you, in plain English, what's actually causing the problem. No more manually inspecting every dependency in your service chain. No more playing "guess the culprit" while your users are getting error pages.

It leverages Internet Stack Map — the family tree of all your digital dependencies — and combines that with event intelligence to automatically analyze backend waterfall data. The result? When something breaks, you don't just know that it's broken, you know what's breaking it.

What about Catchpoint Advisor?

A screenshot of a computerAI-generated content may be incorrect.

Catchpoint Advisor is like having that one senior engineer who's been around forever and somehow always knows exactly where the skeletons are buried, which wire to jiggle, and how to keep the show rolling. In this context, it looks at your monitoring setup and makes intelligent recommendations about coverage gaps, suggests additional tests, and even pre-configures them for you.

How do our new AI capabilities actually work?

Both Root Cause Analysis and Advisor work contextually within your existing Stack Map. The AI isn't making wild guesses based on generic patterns - it's analyzing the specific services in your environment, during your timeline, using your actual data.

When RCA kicks in, it's examining waterfall data to determine whether a service outage is actually impacting your primary service. It only surfaces root causes that are relevant to what you're looking at, when you're looking at it. That means less noise and fewer false positives.

The Advisor recommendations are equally precise. They suggest adding existing – or new - tests you might have overlooked, recommend Internet Sonar services for dependencies you're not yet monitoring, and can even pre-configure new tests with alerts already set up. We're talking about HTTP, Chrome browser tests, SSL checks, traceroutes, DNS monitoring, and more.  

And here's the kicker: these aren't buried in some separate AI dashboard you'll never remember to check. They appear automatically in your Stack Map interface when you have relevant data. No special enablement requests, no additional costs beyond what you're already using Stack Map for.

AI that actually solves problems, not create them

This is where I need to be crystal clear about something: we're not jumping on the AI bandwagon because it's trendy. As our CEO Mehdi Daoudi put it, "AI should remove complexity, not add to it." And our Chief Product Officer Matt Izzo was even more direct: "There is a lot of AI-washing in the industry, we do not want to add AI capabilities just to check the box."

Our new enhancements exist because our customers were telling us that they needed help making sense of what their monitoring data was actually telling them. They also aren’t our first rodeo with practical AI. In November 2023, we announced a raft of AI capabilities that solve real problems, including:  

  • Internet Sonar answers the question “Is it us or something else?” with real-time global Internet health insights.
  • Website Experiments uncovers performance improvement opportunities and validates them without requiring code changes, powered by WebPageTest.
  • Smartboards automatically spotlight performance issues affecting user experience and consolidate them into a single interactive view.
  • Trend Shift detects critical trend shifts in your IPM data before they escalate into incidents, serving as an early warning system.
  • User Engagement Estimator models “what-if” scenarios (e.g., impact of reducing page load times) to predict ROI from optimization efforts.
  • Experience Scores consolidate multiple disparate metrics into a single index for a clear top-line view of user experience.
  • SLI/SLO Tracking uses AI to remove guesswork and help operations teams stay confident about meeting service objectives.

In July 2025, we took another major step forward with two new solutions designed for the age of AI-driven workflows:

  • AI Assistant Reliability Monitoring: Gives IT teams visibility into the health of AI APIs, LLMs, and chatbots, detecting latency, outages, or dependency failures before they impact users.
  • Agentic AI Resilience Monitoring: Provides full-stack visibility for complex, autonomous AI workflows that rely on multiple dependencies, ensuring uptime, speed, and resilience.

RCA and Advisor are the next logical enhancements to our IPM platform, guiding you after detection by pinpointing the cause and recommending what to do about it.

Why does this matter now?

Look, every monitoring vendor is talking about AI these days. Most of them are adding chatbots that can summarize your dashboards or generate reports that look impressive in PowerPoint presentations. That's not what we're doing here.

What we're doing is solving the fundamental problem that keeps SREs, DevOps engineers, and IT ops teams awake at night: the gap between detection and resolution. The space between "I see the problem" and "I know what to do about it." The difference between mean time to detect and mean time to repair.

What's next?

The AI capabilities we've built so far represent the foundation of something bigger – a monitoring platform that doesn't just tell you what's happening, but helps you understand what it means and guides you toward resolution, especially when you're tired, stressed, and needing answers fast.

The 3 AM call will always be part of running Internet-scale services. What’s changing is our ability to answer the question that comes right after: “What’s wrong, and what do we do about it?”

At Catchpoint, our answer increasingly is: "Here's exactly what's wrong, and here's exactly what you should do about it."

And honestly? That feels like progress.

Learn more about AI monitoring

Ready to try it yourself?

Explore our interactive tours and see how Catchpoint can help you bridge the gap between detection and resolution.