Predict Reliability Regressions Early with Rootly’s AI

In fast-paced development, a "reliability regression" is a costly setback where a new change degrades system performance or stability. The financial impact is staggering; system outages can cost Global 2000 companies an estimated $400 billion annually. Instead of just reacting to problems after they impact users, what if you could predict and prevent them? Rootly AI helps your team do exactly that, shifting your organization from a reactive to a proactive reliability posture.

What Are Reliability Regressions and Why Do They Happen?

A reliability regression is a state where a system’s stability or performance worsens after a change, such as a code deployment or a configuration update. These issues can be difficult to trace and often stem from a few common sources.

Common causes include:

• New code deployments with unforeseen side effects.
• Infrastructure changes in complex cloud environments.
• Configuration drift where small, untracked changes accumulate over time.
• Failures in third-party dependencies that your system relies on.

The complexity of modern systems, including non-deterministic AI agents and distributed architectures, makes these regressions difficult to predict. To manage this complexity, many organizations are turning to AIOps (Artificial Intelligence for IT Operations), which leverages AI to automate and enhance IT management [1].

How can Rootly’s AI predict and prevent reliability regressions?

Rootly’s AI helps you get ahead of reliability regressions by combining predictive analytics, real-time monitoring, and automated response. It transforms how your team manages system stability.

Proactive Risk Assessment with Predictive Analytics

Rootly AI analyzes historical data from past incidents, changes, and system metrics to identify patterns that precede failures. Its machine learning models provide AI-suggested risk information, allowing your teams to evaluate a change's potential impact without manual effort. This proactive risk assessment can flag upcoming changes with a high probability of causing a regression, helping you make data-driven decisions about deployments.

Real-Time Anomaly Detection

Traditional monitoring relies on fixed thresholds, which can't keep up with dynamic systems. Rootly establishes a dynamic baseline of a system’s normal behavior and uses machine learning to detect subtle anomalies that may signal an emerging regression. This proactive approach helps teams find and fix problems before they become serious, user-impacting incidents. By identifying issues and their root causes, AI enables teams to resolve incidents more autonomously and efficiently [2].

Automated Mitigation and Response Workflows

When Rootly AI detects a high-risk change or an active anomaly, it can automatically trigger predefined workflows to ensure a fast, consistent response.

Examples of automated actions include:

• Creating a new incident directly in Rootly.
• Notifying the correct on-call engineers.
• Populating the incident with relevant data and context.
• Suggesting or initiating rollback procedures.

This automation is powered by an advanced API designed for AI agents to handle complex, multi-step processes, ensuring every incident follows a clear management lifecycle [3].

How does Rootly support data-driven reliability decisions?

To improve reliability, teams need centralized data and the right tools for analysis. Rootly provides the platform you need to support data-driven decisions at every stage.

Centralized Data for Deeper Insights

Rootly acts as a single source of truth, capturing comprehensive data for every incident and regression. The powerful analytics on the Executive Dashboard transform this complex data into actionable business intelligence. You can track key metrics like Mean Time to Recovery (MTTR) and visualize trends to strengthen your systems. Rootly also integrates with tools like Cortex to create a unified service catalog, ensuring data consistency across your software ecosystem.

Automated Post-Incident Analysis for Continuous Learning

Learning from incidents is key to how Rootly uses AI for continuous reliability improvement. Rootly AI automates the time-consuming process of creating post-incident reports so your team can focus on insights, not paperwork.

Key AI features that facilitate this include:

• Incident Summarization: Generates on-demand reports of an incident’s status.
• Mitigation and Resolution Summary: Automatically documents the steps taken to fix the issue.
• "Ask Rootly AI": Allows users to ask questions in plain English to understand the incident.

You can explore more about these specific AI tools within Rootly.

How does Rootly use AI for continuous reliability improvement?

Adopting Rootly AI is about empowering engineers and creating a stronger, more resilient team culture.

Augmenting Engineering Expertise

Rootly AI is a human-in-the-loop system that enhances your team's existing expertise. The Rootly AI Editor enables users to review, edit, and approve all AI-generated content to ensure accuracy and context. This partnership lets AI handle repetitive work, freeing up your engineers to focus on complex problem-solving and innovation [4].

Shifting from Firefighting to Strategic Prevention

Rootly AI helps your organization shift its approach from reactive firefighting to proactive prevention. By predicting and preventing regressions, it reduces incident frequency and alleviates engineer burnout. This builds a more resilient system and a sustainable work environment, allowing teams to focus on innovation. The thoughtful use of AI in this way has transformative potential for incident management [5].

Conclusion

Rootly’s AI offers a proactive, data-driven solution to the challenge of reliability regressions. By leveraging predictive analytics, real-time anomaly detection, automated workflows, and a centralized data platform, Rootly empowers your team to move beyond reactive firefighting. You can build a culture of continuous reliability improvement and start preventing failures instead of just responding to them.

See how Rootly is pioneering this change and build a more resilient future today.

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