Reduce On‑Call Alert Fatigue with Rootly’s AI Filtering

Alert fatigue is the desensitization engineers experience when they are overwhelmed by excessive notifications. This is a critical issue in high-stakes fields. In cybersecurity, for instance, Security Operations Centers (SOCs) can receive over 10,000 alerts daily [1]. A similar phenomenon in healthcare, alarm fatigue, is correlated with an increased tendency for medical errors [2].

Traditional rule-based systems often worsen the problem by creating more noise than signal. Rootly’s AI-powered filtering is a modern solution designed to restore the signal from the noise, helping your team focus on what truly matters.

The High Cost of Alert Fatigue for On-Call Teams

Alert fatigue is more than an annoyance; it’s a significant operational risk with tangible costs. A constant barrage of notifications leads to missed critical incidents, slower response times, and engineer burnout. This not only compromises system reliability but also damages team morale and retention.

Why Traditional Alerting Systems Fall Short

Rule-based alerting relies on static, manually-set thresholds to trigger notifications. While straightforward, this approach is prone to several common problems:

• Alert Storms: A single failure can trigger dozens of redundant alerts across connected services.
• Lack of Context: Each alert is treated in isolation, without understanding its relationship to other system events.
• High Maintenance: Engineers must constantly tune and update rules as systems evolve, creating a significant maintenance burden.

These limitations mean that rule-based alerts struggle to cut through the noise, making it difficult for engineers to identify real emergencies.

The Business Impact: Burnout, Turnover, and Financial Loss

Alert fatigue is a direct contributor to employee burnout. More than half of cybersecurity professionals cite workload as a major stressor, with overwhelmed SOCs reportedly ignoring up to 67% of the alerts they receive [3].

This burnout has a steep financial cost. In the US cybersecurity sector alone, burnout costs an estimated $626 million annually in lost productivity and turnover [4]. With the cost to replace a specialized employee ranging from 10-30% of their annual salary, the financial case for solving alert fatigue is clear [5].

How Rootly’s AI Filtering Reduces On-Call Noise

Rootly’s AI is a purpose-built solution to the problems of traditional alerting. It moves beyond simple rules to intelligently analyze, group, and prioritize alerts, so your on-call team can focus on what’s important.

Intelligent Alert Correlation and Deduplication

Rootly’s AI automatically analyzes and groups related alerts from various sources—like Datadog, PagerDuty, and Sentry—into a single, contextualized incident. This prevents "alert storms" and gives on-call engineers a clear, consolidated view instead of a flood of notifications. Its alert deduplication feature also silences repeated notifications for an ongoing issue. You can review our documentation for more details on how Rootly handles alerts.

AI-Powered Prioritization Using Machine Learning

Rootly uses machine learning trained on your organization’s historical incident data. The AI learns to recognize patterns that signal a high-impact incident versus low-priority noise. This dynamic prioritization is key to how to reduce alert fatigue on-call, ensuring engineers are only paged for issues that genuinely require their attention. By understanding the unique patterns of your environment, Rootly can prioritize alerts faster and more accurately with machine learning. It's worth noting that the model's effectiveness improves over time as it ingests more of your incident data, making it a progressively smarter partner in your operations.

Smart Routing and Noise Suppression

Rootly’s workflow engine can be configured to intelligently handle alerts based on their content, source, or severity. For example, you can create a workflow to automatically acknowledge a low-priority alert from a development environment at 3 AM without paging an engineer. This preserves your team's focus for actionable incidents, which is a crucial part of Rootly's approach to smart escalation without alert fatigue.

Rootly vs. PagerDuty: A Modern Approach to On-Call Management

Tools like PagerDuty are essential for scheduling and basic notifications. The discussion around a Rootly vs PagerDuty pricing 2025 comparison is less about cost and more about the value Rootly adds. Rootly isn't a replacement but an evolution—it's the intelligence layer that makes on-call management more efficient and less taxing.

Beyond Static Rules: Adding Intelligence to On-Call Schedules

While PagerDuty ensures someone gets notified, Rootly's AI ensures they are notified for the right reasons. Traditional tools often rely on rigid, rule-based escalation policies that contribute to alert noise. This is a widespread issue; a recent survey found that 64% of SOC teams experience alert fatigue from an overwhelming number of false positives [6].

Rootly solves this by integrating seamlessly with PagerDuty and Opsgenie schedules. It uses AI to filter and prioritize alerts before deciding whether to page someone, enhancing your existing tools with a powerful layer of intelligence without requiring you to rip and replace what already works.

Optimizing On-Call with a Holistic AI Platform

Rootly’s AI extends far beyond alert filtering to cover the entire incident lifecycle, providing effective Rootly AI on-call scheduling optimization. This holistic platform creates a more efficient workflow with features like:

• AI-generated incident summaries
• Automated post-mortem drafts
• Natural language queries with "Ask Rootly AI"

By integrating intelligent alerting with a full suite of incident management tools, Rootly creates an efficient workflow from initial alert to final resolution. You can get a complete overview of Rootly's AI capabilities to see how it transforms incident response.

Conclusion: Move from Alert Fatigue to Focused, Effective Response

Alert fatigue is a solvable problem that costs businesses in productivity and employee well-being. While traditional rule-based systems are often part of the problem, Rootly's AI-native platform offers a clear solution.

By leveraging intelligent correlation, ML-based prioritization, and smart noise suppression, Rootly transforms a noisy alert stream into a clear, actionable signal. Adopting an AI-driven approach is a crucial step for any organization looking to build more resilient systems and foster a sustainable on-call culture.

Ready to see how Rootly can silence the noise and empower your on-call team? Book a demo to see our AI in action.

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