PulseBoard Update: Turning an uptime monitor into an AI incident response system 🚀
Quick PulseBoard progress update 🚀
When I first shared PulseBoard, the goal was simple: build an uptime monitoring tool that could do more than just send "your service is down" alerts.
Since then, I’ve focused heavily on making it production-ready and improving the hardest part of monitoring:
Understanding incidents.
Here are some of the latest developments:
🤖 Vigil AI got a major upgrade
Vigil is now more than a chatbot.
It acts as an AI incident companion that takes raw monitoring failures and converts them into structured incident reports:
Incident Summary
Root Cause Analysis
Impact Assessment
Resolution Steps
Prevention Recommendations
It also includes Text-to-Speech support, so teams can listen to incident summaries instead of digging through logs during stressful outages.
The biggest focus was making AI reliable:
Instead of confidently guessing a cause, Vigil now follows strict guardrails and responds:
"Cause unknown from available data"
when there isn't enough evidence.
No fabricated deployment stories. No false confidence.
🛡️ Production reliability improvements
While building an uptime monitoring system, I realized the monitoring system itself has to be extremely careful.
Added:
✅ Circuit breakers
Only trigger incidents after consecutive failures to reduce false alarms caused by temporary network/CDN issues.
✅ Anti-flapping protection
Repeated intermittent failures are grouped into one incident instead of creating alert spam.
✅ Smarter AI/database handling
Optimized long-running incidents to prevent unnecessary processing and token usage.
🌐 Status pages improvements
Public status pages now provide:
Shareable customer-facing uptime history
Service timelines
90-day uptime visibility
Helping companies communicate transparently during incidents.
The biggest lesson from building PulseBoard:
Monitoring is not the hard part anymore.
The hard part is answering:
"Why did this happen, and what should we do next?"
That is the problem I’m trying to solve with PulseBoard + Vigil AI.
Would love feedback from founders and developers:
How do you currently handle incidents?
Do you write postmortems manually?
Would an AI incident companion save your team time?
Building in public 🚀
Axon ERP
Gestión inteligente: Facturación, Punto de Venta e IA en la nube
Comments (3)
This lines up almost exactly with something I hit building FounderFlow — I ended up grading every AI insight as Verified, Very Likely, Needs Review, or Monitor Only instead of giving one confident-sounding answer, because a wrong guess that sounds certain is worse than an honest "not sure yet." Glad to see Vigil taking the same "cause unknown from available data" approach instead of fabricating a root cause. How are users reacting to the AI admitting uncertainty — does it build trust faster, or do some still expect a definitive answer?
I completely agree. One thing I learned while building Vigil is that false confidence is often more dangerous than uncertainty, especially during production incidents. If the AI invents a root cause, engineers can end up investigating the wrong thing and lose valuable time.
So I decided it's better for Vigil to explicitly say "cause unknown from available data" and explain what evidence it does have, rather than fabricate a confident answer.
So far, the feedback has been positive because it feels more like working with a cautious engineer than an overconfident chatbot. My long-term goal is to reduce those "unknown" cases by giving Vigil more real evidence to reason over—monitoring history, GitHub code changes, infrastructure context, and other signals—rather than simply making the model more creative.
I think AI earns trust by being transparent about what it knows, what it doesn't know, and why it reached a conclusion.
Md_haseeb, that reframe of AI earning trust by being transparent about what it doesn't know is exactly right, and it matches what we're seeing too. People seem to trust the confidence labels more once they've caught the tool being honest about uncertainty at least once, almost like it has to earn the benefit of the doubt first. Good sign the feedback's been positive already.
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