How SRE Teams Leverage Prometheus & Grafana with Rootly

Site Reliability Engineering (SRE) teams are tasked with keeping complex digital services online and performant, but they often struggle with a high volume of alerts from powerful yet siloed observability tools. With 60% of outages costing over $100,000, the pressure to resolve incidents quickly is immense. While Prometheus and Grafana are cornerstones for modern monitoring, they primarily identify problems, leaving the critical response process manual and slow.

This is where Rootly connects monitoring to action. It serves as an automation and orchestration layer that integrates with your existing tools to automate the entire incident response lifecycle. The goal is to reduce Mean Time to Resolution (MTTR), minimize manual toil, and build a more resilient incident management practice.

The Classic SRE Observability Duo: How SRE Teams Use Prometheus and Grafana

For many SRE teams, the combination of Prometheus and Grafana forms the foundation of their monitoring strategy. This duo is highly effective for gaining visibility into system health, but it's not a complete solution and comes with inherent limitations.

Prometheus is an open-source tool used to scrape and store time-series metric data from various application and infrastructure components, especially in dynamic Kubernetes environments. Grafana then acts as the visualization layer, allowing teams to build powerful, interactive dashboards that display Prometheus data. This provides essential visibility, but it is only one piece of the puzzle. While traditional monitoring is reactive, AI-powered monitoring offers a proactive approach that can better manage the complexities of modern systems.

The Limitations of Monitoring Without Automated Response

The primary drawback of relying solely on Prometheus and Grafana is that the stack is reactive. It tells you when something is wrong but offers little help in automating what to do next. This leads to several common pain points for on-call engineers:

• Alert Fatigue: A high volume of alerts from various systems can desensitize engineers, making it difficult to distinguish critical issues from noise.
• Manual Toil: When a critical alert fires, engineers must manually perform a sequence of repetitive tasks: diagnosing the issue, creating a dedicated incident channel, paging team members, and notifying stakeholders.
• Increased MTTR: Context-switching between monitoring dashboards, communication tools, and ticketing systems to piece together information slows down the entire response process, leading to longer and more costly outages.

Bridging the Gap: Automating Incident Response with Rootly

The most effective strategy to overcome these limitations is to create a seamless workflow that connects alert detection in Prometheus directly to incident resolution orchestrated by Rootly. This integration transforms your passive monitoring setup into an active, automated response system. By connecting these tools, you can automate your entire response with Rootly, Prometheus, and Grafana to build a more efficient workflow.

Step 1: Centralize Alerts with the Prometheus Alertmanager Integration

The first step is to configure Prometheus's Alertmanager to forward all alert notifications to a unique Rootly webhook URL. This direct integration ensures every alert your monitoring system fires is securely and instantly ingested by Rootly. The labels and annotations from the incoming Prometheus alert can then be used to trigger specific, context-aware workflows, ensuring the right process is kicked off every time.

Step 2: Build Automated, Context-Aware Workflows

Once an alert is ingested, Rootly's automation engine takes over. You can build custom workflows that execute a series of actions automatically, saving engineers valuable time and reducing the risk of human error. Common automated actions include:

• Creating a dedicated Slack or Microsoft Teams channel for incident collaboration.
• Paging the correct on-call engineer using Rootly's native scheduling or through its integrations with tools like PagerDuty, Splunk, and Datadog.
• Generating a Jira or Shortcut ticket to track the incident and any follow-up work.
• Enriching the incident context by automatically attaching a link to the relevant Grafana dashboard right in the incident channel.

Step 3: Manage the Full Incident Lifecycle in One Place

This integrated setup effectively turns your communication platform, like Slack or Microsoft Teams, into a centralized incident command center. Rootly acts as the single source of truth, automatically capturing all actions, communications, and timeline events to create a complete and accurate audit trail. This data is invaluable for generating detailed post-mortems and uncovering insights to improve system reliability. With this approach, you can centralize observability and secure operations at enterprise scale.

Full-Stack Observability Platforms Comparison: Where Rootly Fits In

The industry is rapidly moving toward unified, full-stack observability platforms that consolidate metrics, logs, and traces into a single solution. Choosing the right platform is a key decision for engineering teams in 2026, with a growing focus on end-to-end visibility and intelligent automation [1]. Dozens of vendors offer compelling solutions, each with different strengths and potential trade-offs regarding cost, complexity, and vendor lock-in [2].

While these platforms are excellent for data collection and analysis, Rootly occupies a unique and complementary position. Rootly is not a data collection tool; it is an action and orchestration platform that sits on top of your entire observability stack. Whether you use an open-source stack like Prometheus and Grafana or a commercial full-stack platform, Rootly enhances its value by automating the response to the signals these tools generate. This allows teams to select the best observability tools for their needs without sacrificing a consistent and automated incident response process.

AI Observability and Automation SRE Synergy

The rise of AIOps (Artificial Intelligence for IT Operations) is creating a powerful synergy between observability and automation, fundamentally changing how SRE teams manage incidents. As noted by industry analysts, the AIOps landscape continues to evolve with a greater emphasis on predictive analytics and automated remediation [3]. This shift is moving incident management from a reactive discipline to a proactive and even predictive one.

Intelligent Noise Reduction and Accelerated Root Cause Analysis

Rootly leverages AI to help SRE teams manage incidents more effectively. By analyzing and grouping related alerts from Prometheus and other sources, Rootly’s AI capabilities can intelligently reduce alert fatigue and present engineers with a single, actionable incident. Responders can use features like Ask Rootly AI to ask plain-language questions and receive data-backed answers directly within Slack, dramatically speeding up investigation. This AI-driven approach helps accelerate root cause analysis by correlating signals and highlighting contributing factors that a human might miss, all while leveraging Rootly's best third-party integrations to power incident ops.

The Path to Autonomous Remediation

The future of SRE is moving toward self-healing systems that can resolve issues without human intervention. The synergy between AI-powered observability and automation is key to achieving this goal. Rootly's workflows can be configured to trigger automated remediation tasks in response to specific alerts. For example, a workflow could automatically restart a failing service, roll back a problematic deployment, or scale resources via integrations with tools like AWS Lambda. This is the ultimate goal of the AI observability and automation synergy: freeing up SREs from firefighting to focus on building more resilient and reliable systems.

Conclusion: Build a More Resilient and Efficient SRE Practice

By combining the powerful monitoring capabilities of Prometheus and Grafana with the intelligent automation of Rootly, SRE teams can build a truly end-to-end incident management solution. This integrated approach delivers significant benefits, including drastically reduced MTTR, less engineer burnout from manual toil, and a consistent, auditable incident process every time.

In today's world of complex, large-scale systems, an AI-augmented response strategy is no longer a luxury—it's essential. By bridging the gap between monitoring and action, you empower your team to resolve incidents faster and build more reliable software. For more insights on building a robust SRE toolkit, explore these 10 SRE tools the most reliable engineering teams actually use.

Ready to see how Rootly can automate your incident response? Book a demo today.

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