At 3:12 AM, a subtle CPU spike went unnoticed.
By 4:00 AM, customers started logging tickets.
By morning, the damage had been done—downtime, missed SLAs, and over $40K in recovery costs.
This wasn't the first incident. For a fast-scaling SaaS company juggling workloads across AWS, Azure, and GCP, these disruptions had become a painful pattern. Despite having half a dozen monitoring tools, their teams were still playing catch-up with problems that had already unfolded.
The Visibility Challenge
Each cloud provider had its own dashboards. Alerts fired too late or too often.
Tagging inconsistencies across departments made it impossible to trace issues back to ownership or cost centers.
When something broke, four different teams were pulled in, flipping through graphs, logs, and billing files to piece together a timeline.
The real problem wasn't the incident. It was the lack of unified visibility and intelligent early warning.
That's when they turned to Cloudshot.
The Cloudshot Solution
Instead of adding another tool to the pile, Cloudshot replaced chaos with clarity. It was deployed across their entire cloud footprint in under 24 hours. Within minutes, it auto-discovered their infrastructure and built a live topology map that made service relationships, risk zones, and high-cost areas instantly visible.
What changed wasn't just tooling—it was mindset.
Early Detection Through AI
Cloudshot's AI-driven anomaly detection didn't wait for thresholds to be crossed. It flagged deviations early, contextualized them, and visualized their potential impact. A drift in memory usage? A shift in network patterns? Cloudshot caught them before customers did.
Unified Visibility for All Stakeholders
More importantly, it brought every stakeholder onto the same page. Engineering got real-time health metrics with logs and resource dependencies in one view. Finance saw cost implications per service in real time. The CTO had a single executive dashboard showing operational risk, spend velocity, and service interdependencies—all updated live.
The Results: $267K Saved in 30 Days
The first 30 days revealed more than just issues—they revealed savings.
Cloudshot identified a mix of:
- Idle workloads
- Over-provisioned instances
- Unused storage
- Redundant traffic flows
By acting on those insights, the team saved $267K in projected cost overruns and reactive response expenses.
Incidents didn't vanish—but surprises did.
Their mean time to resolve dropped by 58%.
Instead of jumping between Slack threads and dashboards, they responded with precision.
"Cloudshot paid for itself in 3 weeks. We didn't just avoid downtime—we finally stopped fearing it."
That's the quiet power of proactive visibility. Not loud alerts. Not yet another dashboard. Just one source of truth—for every role, every cloud, every second.
If your team is still reacting to incidents after the fact, maybe it's time to see what you're missing—before it costs you more.
Ready to discover what you're missing in your cloud?
If your team is still reacting to incidents after the fact, maybe it’s time to see what you’re missing—before it costs you more.