March 11, 2026

Build an SRE Observability Stack for Kubernetes with Rootly

Build a powerful SRE observability stack for Kubernetes. Turn data into action by connecting it to Rootly, the SRE tool for automated incident tracking.

Kubernetes is the engine of modern applications, but its dynamic nature can make it a black box when performance degrades or an outage occurs. To gain visibility into these complex systems, Site Reliability Engineering (SRE) teams need a robust observability stack. This guide provides a blueprint for how to build a powerful SRE observability stack for Kubernetes using essential open-source tools. It also shows you how to connect that stack to an incident management platform like Rootly to make your data truly actionable.

The Three Pillars of Kubernetes Observability

Observability isn't just about collecting data; it's the ability to ask any question about your system's internal state to understand its behavior without shipping new code [8]. A complete observability strategy rests on three pillars of telemetry data [2].

Metrics: Numerical measurements recorded over time, like CPU utilization, request latency, or error counts. Metrics are ideal for understanding overall system health, identifying trends, and triggering alerts.
Logs: Timestamped records of discrete events, such as application errors or completed requests. Logs provide the deep, event-specific context needed for root cause analysis.
Traces: A representation of a single request's end-to-end journey as it travels through a distributed system. Traces are essential for debugging performance bottlenecks and understanding service dependencies [3].

Building Your Kubernetes Observability Stack: Core Tools

A production-grade observability stack doesn't require a massive budget. A combination of powerful open-source tools has become the standard for many engineering teams.

Metrics Collection and Storage with Prometheus

Prometheus is the de facto standard for metrics in the cloud-native world. It uses a pull model to scrape time-series data from instrumented application endpoints. With its powerful query language (PromQL) and a robust alerting component called Alertmanager, Prometheus forms the backbone of monitoring for any Kubernetes environment [7].

Log Aggregation with Loki

Loki is a log aggregation system designed to be highly cost-effective and easy to run. Its core principle is to index only the metadata (labels) associated with logs, not the full text. This design makes it a natural companion to Prometheus, as it uses the same labeling system to correlate logs with metrics, which simplifies investigations [6].

Visualization and Dashboards with Grafana

Grafana is the leading open-source platform for visualizing observability data. It connects to various data sources, including Prometheus for metrics and Loki for logs. Grafana excels at creating unified dashboards that allow teams to view and correlate different data types in one place, dramatically speeding up troubleshooting [5].

Tracing and Instrumentation with OpenTelemetry

OpenTelemetry (OTel) is the emerging industry standard for generating and collecting telemetry data. It provides a single, vendor-neutral set of APIs and libraries for instrumenting your applications to produce traces, metrics, and logs [4]. Adopting OTel helps you avoid vendor lock-in and ensures your instrumentation is future-proof, no matter which backend you choose for data storage and analysis [1].

From Observability to Action: Integrating Rootly for Incident Management

An effective observability stack provides critical data, but an alert from Prometheus is just a signal. The real work is in coordinating the response, communicating with stakeholders, and learning from the incident. This is where teams often stumble, slowed down by manual processes and scattered communication.

Rootly acts as the central command center for your incident response, integrating directly with your observability stack to turn data into decisive action. It’s one of the most critical SRE tools for incident tracking and resolution.

Automated Incident Creation: Connect Alertmanager to a Rootly webhook. When a critical alert fires, Rootly automatically declares an incident, creates a dedicated Slack channel, pulls in the on-call engineer, and posts the alert details.
Centralized Context: Instead of switching between tools, engineers use simple commands directly in Slack. They can pull relevant Grafana dashboards, query logs, or link to traces all within the incident channel, keeping everyone on the same page.
Streamlined Workflow: Rootly manages the entire incident lifecycle. You can set severity levels, assign roles, update a status page, and track action items without leaving Slack. This structured approach ensures nothing falls through the cracks.
AI-Powered Insights: Rootly uses AI to help you unlock log and metric insights fast. It enables faster incident detection and helps you boost accuracy and cut noise by intelligently grouping alerts and surfacing critical signals, allowing for a quicker, more focused response.

Example Workflow: An Incident in Action

Let's see how this works with a concrete example:

A new code deployment to a Kubernetes cluster causes a spike in API error rates.
Prometheus detects the anomaly in the http_requests_total{status="5xx"} metric and sends an alert to Alertmanager.
Alertmanager forwards the critical alert to its configured Rootly webhook.
Rootly instantly creates the #incident-api-errors Slack channel, pages the SRE on-call, and posts the initial alert context.
The SRE runs /rootly query grafana in the channel to pull the service's dashboard directly into Slack, confirming the error spike and correlating it with the recent deployment.
The team collaborates in the channel, identifies the faulty deployment as the likely cause, and initiates a rollback.
Once the incident is resolved, the SRE uses Rootly to automatically generate a postmortem document, complete with a timeline and key findings, ready for the retrospective.

Conclusion

A solid SRE observability stack for Kubernetes, built on tools like Prometheus, Grafana, and OpenTelemetry, gives you the visibility needed to understand your systems. But to master reliability, you must operationalize that data.

By integrating your stack with Rootly, you transform raw telemetry into a fast, automated, and collaborative incident management process. It closes the loop between detection and resolution, freeing your engineers to solve problems rather than manage process. This is how you build a superior SRE observability stack for Kubernetes with Rootly.

Ready to connect your observability stack to a world-class incident management platform? Book a demo or start your free trial today.