Your Modern Incident Stack: Rootly, OTel, Grafana & Jira

In today's complex tech environments, managing incidents with isolated tools is no longer sufficient. A modern incident management stack connects observability, alerting, collaboration, and tracking into a single, seamless workflow. This cohesive approach helps teams resolve issues faster and more efficiently.

This article explores how to build that stack using four key players: Rootly as the central command center, OpenTelemetry (OTel) for standardized observability data, Grafana for powerful visualization, and Jira for tracking follow-up actions.

The Core Components of Your Modern Incident Stack

Each tool in this stack plays a specialized role, but their true power is unlocked when they're integrated. By working together, they create an automated incident response engine that streamlines everything from detection to resolution.

Rootly: The Central Command Center

At the heart of the modern incident stack is a platform that automates manual tasks and centralizes communication. Rootly serves as this core, orchestrating the entire incident lifecycle, from the moment an issue is declared to the final retrospective.

Rootly uses powerful, customizable workflows to connect with other tools in your stack. Instead of responders manually creating communication channels or updating stakeholders, Rootly handles it all, freeing up your team to focus on fixing the problem. The platform's flexibility, powered by the ability to create custom automations for incident control, allows you to unify your entire ecosystem.

How does Rootly integrate with OpenTelemetry for unified observability?

OpenTelemetry (OTel) is a crucial standard for modern observability. It provides a vendor-neutral framework for collecting telemetry data—specifically metrics, logs, and traces—from your applications and infrastructure. In simple terms, OTel ensures all your systems speak the same language, giving you a unified view of your system's health.

Rootly leverages the insights derived from OTel data. When observability tools process OTel data to identify an issue, they can pass that rich, contextual information to Rootly. This context is critical for faster root cause analysis, as it helps responders understand an incident's scope without piecing together data from multiple, disconnected sources. This AI-driven approach to correlating anomalies is key to reducing Mean Time To Resolution (MTTR) [1].

What’s the best way to use Rootly alongside Prometheus and Grafana?

Prometheus is a popular open-source tool that collects metrics from your services, while its Alertmanager component fires alerts based on predefined rules. Grafana sits on top, acting as the visualization layer where you can build dashboards to monitor system health in real-time.

The best way to use these tools with Rootly is to configure alerts in Prometheus or Grafana to automatically trigger workflows in Rootly. For example, when Prometheus detects an issue and fires an alert, that alert can be sent directly to Rootly via a webhook. From there, Rootly can automatically create a new incident, start a dedicated Slack channel, and page the on-call engineer.

This setup transforms a simple alert into an actionable incident response process without human intervention. You can learn more about setting up these webhooks in both the Prometheus Alertmanager and Grafana Alerts documentation. Other resources are also available that detail how to configure the Prometheus Alertmanager webhook [2].

The Rootly Jira Integration for Action and Resolution

Jira is the system of record for most engineering teams, used for bug tracking, project management, and planning follow-up work. The Rootly Jira integration acts as the crucial bridge between real-time incident response and long-term engineering work.

With the integration, action items and follow-up tasks identified during an incident in Rootly can be automatically created as Jira tickets. This eliminates manual data entry and guarantees that post-incident work is captured, assigned, and tracked through to completion. The Rootly API enables custom automations that make this seamless Jira integration possible, ensuring that incident follow-up is never missed.

Building the Integrated Workflow: From Alert to Resolution

Let's walk through how a typical incident flows through this integrated stack, from the initial alert to the final resolution.

Step 1: Detection and Alerting in Grafana

It all starts with detection. Imagine a key service metric, like CPU usage or API error rate, crosses a critical threshold defined in Prometheus. Grafana, which is visualizing this metric on a dashboard, immediately shows the anomaly.

Because you've configured your Grafana integration, it knows exactly what to do next. It sends an alert payload via a webhook directly to a designated Rootly endpoint. This process can be easily automated, connecting your visualization layer directly to your incident response command center [3].

Step 2: Automated Incident Creation in Rootly

When Rootly receives the webhook from Grafana, the automation kicks in. A pre-configured Rootly workflow is triggered, parsing the alert's payload to gather important details. Within seconds, Rootly performs a series of actions automatically:

• Creates a new incident, naming it based on the alert description.
• Sets the incident severity (for example, SEV1, SEV2) based on data in the alert.
• Creates a dedicated Slack channel (for example, #inc-20251026-high-api-errors) and invites the on-call team.
• Starts a Zoom or Google Meet call and posts the link in the channel for the war room.
• Pages the primary on-call engineer using an integration like PagerDuty or Rootly's native on-call scheduling. You can see how alert-based automation works with our PagerDuty integration.

Step 3: Investigation and Action in Jira

As responders work to resolve the incident in the Slack channel, they identify the root cause and determine what follow-up actions are needed to prevent a recurrence.

Instead of needing to open another tab and manually create a Jira ticket, a responder can use a simple Slack command directly in the incident channel (for example, /rootly new task). Rootly prompts them for a title and description, then automatically creates a ticket in the appropriate Jira project. This ticket is instantly populated with relevant context, such as the incident ID, a link to the incident timeline, and a summary of the issue. This creates a clear, auditable trail from incident detection all the way to permanent resolution.

Conclusion: Build a Resilient, Automated Incident Response Engine

By combining Rootly for command and control, OTel for standardized data, Grafana for visualization, and Jira for tracking, you create a truly modern incident management stack. This integrated approach reduces Mean Time to Resolution (MTTR), eliminates manual toil for your engineers, and ensures that valuable lessons from incidents are translated into actionable improvements.

When you connect these best-in-class tools, you build a resilient, efficient, and automated incident response process that scales with your organization.

Ready to build a more automated and intelligent incident management process? Explore Rootly's extensive integrations and see how you can create a more streamlined workflow today with an overview of our incident management capabilities.

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