*From Blind Spots to Big Savings: How Cloudshot Helped Save $267K
*
It began with a slight CPU irregularity at 3:12 AM—barely noticeable.
But by 4:00 AM, customers were filing support tickets.
By the time leadership got involved, the team was already deep into recovery mode—dealing with missed SLAs, frustrated users, and a $40K loss.

For this high-growth SaaS company running critical workloads across AWS, Azure, and GCP, this scenario was becoming all too familiar.
Despite using multiple monitoring solutions, they couldn’t prevent issues—they could only react to them.

Each cloud had its own view.
Alerts were inconsistent—some came too late, others too often.
Disjointed tags and ownership ambiguity meant every incident became a four-team scramble involving logs, graphs, billing files, and guesswork.

The real failure wasn’t technical. It was the lack of unified, intelligent visibility.

Then they tried Cloudshot.

Instead of layering on yet another tool, Cloudshot replaced fragmentation with clarity.
Within 24 hours, it was deployed across their multi-cloud stack.
It automatically discovered infrastructure components, mapped live dependencies, and surfaced both operational risk and cost inefficiencies—visually.

The game-changer was Cloudshot’s AI-powered anomaly detection.
It learned system behavior and flagged subtle deviations—before they escalated into customer-facing problems.
Whether it was a memory leak, network anomaly, or cost drift, Cloudshot alerted early and in context.

The platform gave each stakeholder what they needed:

Engineers saw real-time logs, metrics, and resource dependencies in one place.

Finance tracked live cost exposure per service.

The CTO got a single, always-updated dashboard highlighting risk, usage trends, and service interconnections.

Within the first month, Cloudshot helped the team identify and act on:

Idle and oversized compute instances

Redundant traffic patterns

Unused storage volumes

Misallocated spend across departments

Altogether, these optimizations saved the company $267K in projected waste and emergency response costs.

Even better?
Their mean time to resolution dropped 58%, and team confidence surged.
Instead of reacting to issues and scrambling to explain post-mortems, they started getting ahead of them.

As their Head of Platform said:
“Cloudshot paid for itself in less than a month. We don’t fear outages anymore—we prevent them.”

This is the quiet strength of proactive cloud monitoring.
Not louder alerts or extra dashboards—but real-time clarity that helps teams act with precision.

🎯 Ready to move from reaction to prevention?
Start your free trial of Cloudshot – no credit card required.
Or book a personalized demo and see what you’ve been missing.

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