PagerDuty incidents get 3 ranked root causes + confidence in seconds. Direct webhook. Human-in-loop training. Free 25/mo → https://xitter.cf/t.co/RsPVvI2s2w #SRE
Joined March 2026
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SpringAgents retweeted
Introducing Claude Opus 4.7, our most capable Opus model yet.
It handles long-running tasks with more rigor, follows instructions more precisely, and verifies its own outputs before reporting back.
You can hand off your hardest work with less supervision.
ALT Claude Opus 4.7 Benchmarks
🚨 From alert to insight in seconds.
Watch how Spring Agents turns PagerDuty fires into actionable intelligence:
• Monitoring triggers → PagerDuty alert
• Spring Agents enriches with live cloud context & ranked root causes
• Structured note auto-posts to the incident
Faster fixes. Fewer repeats. Better outcomes.
The Root Cause Copilot for PagerDuty.
springagents.tech
#SRE #DevOps #PagerDuty #IncidentResponse #AIOps
🤖 Made with AI
PagerDuty drops a "Fatal Memory Shortage on Windows" alert at 6 AM 😵
Spring Agents hits the note seconds later:
🤖 "#1 SQL Server eating all the RAM again (82% sure)
#2 Some other process leaking?
#3 Threshold too aggressive?"
Plus the usual chaos: 274 incidents this quarter on that service (~3 a day 💀).
Real context. Ranked causes. Next steps that actually make sense at 6 AM.
Thumbs up/down and it gets smarter for the next one.
5-minute webhook setup. Stays inside PagerDuty.
springagents.tech #PagerDuty #SRE #DevOps
1: Woke up to 14 alerts and zero context.
2: Added one webhook between PagerDuty and Spring Agents.
3: Every alert now lands with a confidence-scored diagnosis.
4: The bottleneck was never speed. It was information.
25 years in IT ops. Built this because I was tired of tools that promise "AI-powered" and deliver a chatbot that summarizes your own docs back to you.
Spring Agents analyzes real incidents with real context. Open source.
springagents.tech
No ML pipeline. No training data. No 6-month integration project.
Python + Claude + your existing monitoring stack.
Works with PagerDuty, any log source, any cloud. We didn't build another platform. We built the analyst your NOC team can't hire.
Every alert your agent analyzes makes it smarter.
It learns your infrastructure. Your alert patterns. Your resolution history.
Week 1: generic incident reports.
Week 4: "This looks like the connection pool issue from March 12. Last time, restarting the app pool on us-east-1 fixed it in 6 minutes."
Your MTTR drops every single week.
What happens when an alert fires:
→ PagerDuty webhook hits your agent
→ Claude reads the logs, metrics, error traces, and recent changes
→ Structured incident report lands in your channel in ~30 seconds
Root cause, impact assessment, severity, next steps. All before your L1 finishes reading the subject line.
Most incident tools take weeks to set up.
Spring Agents takes 4 minutes.
pip install, paste your PagerDuty webhook, done. Your next alert gets analyzed by Claude before your team even opens the ticket.
After 25 years in ops I've learned one thing: the engineer who fixes the incident fastest isn't the smartest one. It's the one who's seen it before.
That's memory. And memory doesn't scale.
Free tier. 25 incidents/month. No credit card.
Built by someone who spent 25 years on the ops side of the house, not the vendor side.
springagents.tech
The part that matters most: your team's corrections make it smarter.
Thumbs up, thumbs down, or a quick correction. The AI learns what's specific to YOUR environment. Your Postgres quirks. Your deployment patterns. Your infrastructure.
It gets better the more you use it.
It's not another dashboard. Nothing new to log into.
The analysis shows up where your team already works — inside the PagerDuty incident. One less tab. One less context switch.
Setup is a webhook URL. Takes about 4 minutes.
Spring Agents hooks into PagerDuty via webhook.
When an incident fires, AI analyzes it and posts 3 ranked hypotheses directly as notes on the incident. With confidence percentages.
Your engineer opens PagerDuty and the diagnosis is already there.
The on-call ritual hasn't changed in 20 years.
Alert fires. Engineer wakes up. Spends 20 minutes in Grafana and CloudWatch trying to figure out what broke.
Half the time it's something they've seen before. They just don't remember at 3 AM.
Your on-call engineer gets paged at 3 AM. They open PagerDuty. Instead of digging through dashboards half-asleep, there are already 3 ranked root causes waiting with confidence scores.
That's what we built. Here's why.
34 agents running a trading firm autonomously and dude calls it his "holy s***" moment. Meanwhile in IT ops we've had 34 things running autonomously for years — we just called them "cron jobs nobody documented" and hoped for the best 😅
Open models crossing the agentic threshold is the real story of 2025. Gemma 4, LangChain confirming it — you no longer need a vendor API key to run capable agents. The cost barrier to agent ops just evaporated. What's your excuse now? #AIAgents
Shadow AI is the new shadow IT. KiloClaw launching agent governance tooling tells you exactly where the market is headed — autonomous agents are already running in your org, you just don't know about them yet. Discovery before deployment. #AgenticAI #ITOps