I’ve spent the last two decades deep in network operations, application performance monitoring (APM), and observability. Across 18 years at HP and Cisco, and another 6 years at Dynatrace, I’ve worked with IT operations teams spanning NASDAQ, telecom, retail, and manufacturing.
Over that time, the industry was sold a persistent promise. First it was application performance monitoring tools, then it was “Single Pane of Glass” dashboards, then it was AIOps. The pitch was always the same: this new tool will finally end the 3:00 AM war room.
But let’s be honest about what actually happened. The toil never stopped. The war rooms never ended.
Instead of unification, we got more fragmentation. We ended up with logs in Splunk or Elastic fighting for data ownership against observability platforms, cloud solutions, and GitOps pipelines. Even modern application performance monitoring tools operate in silos. Everyone guards their own domain. Nobody has the full picture. And when a Sev-1 incident hits, teams are still manually scrambling to connect the dots across a dozen different screens.
I realized that traditional observability and ITSM had hit a wall. That is why I joined Ciroos.
Why Application Performance Monitoring Tools Haven’t Solved the Problem
Despite years of innovation, most application performance monitoring tools still focus on collecting and visualizing data, not understanding it.
Dashboards don’t investigate. Alerts don’t reason. And when systems span multiple domains, the burden still falls on humans to correlate signals manually.
That’s why war rooms still exist.
The Shift from Dashboards to AI SRE Solutions
The next generation of operations isn’t about building another dashboard or fighting a political battle to force all your data into one massive, expensive lake. It’s about leveraging multi-agentic AI to cut through the noise and turn fragmented telemetry into actionable answers.
This is where a new category of AI SRE tools and AI SRE solutions begins to emerge. They are not focused on more data, but on faster understanding.
Ciroos is an AI SRE Teammate that acts exactly how a seasoned human expert would. It fetches data on demand from your existing observability tools, logging platforms, and Kubernetes environments—without copying or duplicating anything.
https://www.youtube.com/watch?v=QQVvwklzJJc
This zero-copy architecture means no data consolidation battles, no tool-to-tool migrations, and no domain ownership politics. Ciroos fetches what it needs, investigates the anomaly, correlates the signals across every domain, surfaces the true root cause, and then discards the data. Clean. Purposeful. Precise.
Your domain tools aren’t going anywhere. Your engineers won’t let go of Splunk, Grafana, or whatever they’ve built their workflows around—and they shouldn’t have to. Ciroos doesn’t ask you to rip and replace your stack or your existing application performance monitoring tools. It asks you to finally connect the dots.
We need to stop normalizing late nights and reactive war rooms. It’s time to put something in place that actually moves teams from chasing symptoms to resolving causation.
Frequently asked questions about Application Performance Monitoring and AI SRE
Get quick answers to common questions about why traditional monitoring approaches fall short, and how AI-driven SRE is changing incident response.
Why haven’t application performance monitoring tools eliminated war rooms?
While modern application performance monitoring tools and observability platforms provide deep visibility into systems, they primarily focus on collecting and visualizing data. They don’t investigate incidents or connect signals across domains automatically. As a result, during critical outages, teams still rely on manual correlation across multiple tools, leading to the same war room scenarios that have existed for years.
How are AI SRE tools different from traditional observability platforms?
Traditional observability platforms help teams understand what is happening by surfacing metrics, logs, and traces. In contrast, AI SRE tools go a step further by helping teams understand why something is happening. They use AI to correlate signals across systems, investigate anomalies, and identify root causes, reducing the need for manual triage and accelerating incident resolution.
What are AI SRE solutions, and how do they improve incident response?
AI SRE solutions are designed to augment or act as an SRE teammate by automating investigation and reasoning during incidents. Instead of relying solely on dashboards and alerts from application performance monitoring tools, these solutions pull data from across your stack, analyze it in context, and surface actionable insights. This enables teams to move faster from detection to root cause, reducing downtime and minimizing the need for reactive war rooms.