March 10, 2026

Build an SRE Observability Stack for Kubernetes with Rootly

Learn to build an SRE observability stack for Kubernetes using Prometheus & OpenTelemetry. See how to integrate Rootly to automate incident response.

Kubernetes is the standard for container orchestration, but its dynamic nature makes traditional monitoring ineffective. With ephemeral pods and complex microservice interactions, you need more than just dashboards; you need observability to ask detailed questions about your system's behavior. Observability is the ability to understand a system's internal state from its external outputs.

This guide provides a blueprint for building an effective sre observability stack for kubernetes. We'll cover the core components, recommend best-in-class tools, and show how to integrate an incident management platform that turns data into decisive action.

The Three Pillars of a Modern Observability Stack

A complete observability strategy is built on three types of telemetry data. Integrating all three is essential for rapid troubleshooting and maintaining system health [5].

Metrics: Numerical data measured over time, like CPU usage, request latency, or error rates. Metrics are ideal for creating real-time dashboards and alerting on when a problem is happening.
Logs: Time-stamped records of discrete events. A log entry offers detailed context about a specific event, like an application error or a completed transaction, helping you uncover why a problem happened.
Traces: A representation of a single request's journey as it travels through a distributed system. Traces are crucial for pinpointing performance bottlenecks and understanding service dependencies in microservice architectures [2].

Building Your Stack: Core Components and Tools

You can build a powerful and flexible sre observability stack for kubernetes using widely adopted, open-source tools that have become industry standards.

Metrics Collection and Visualization with Prometheus and Grafana

Prometheus is the de-facto standard for metrics collection in cloud-native environments. It uses a pull-based model to scrape metrics from services it discovers automatically within Kubernetes. It's a core component of many production-grade observability stacks [4].

For visualization, Grafana is the leading open-source platform. It connects to data sources like Prometheus to build real-time dashboards, allowing SRE teams to monitor system health, track Service Level Objectives (SLOs), and quickly identify anomalies.

Log Aggregation with Loki

Searching logs from thousands of pods across a cluster is a major operational challenge. Loki is a log aggregation system designed to be cost-effective and easy to operate. Inspired by Prometheus, Loki only indexes a small set of metadata (labels) for each log stream—such as a pod's name or namespace—instead of the full text. This makes it a natural fit with Prometheus and allows you to correlate metrics with logs in Grafana seamlessly [7].

Distributed Tracing with OpenTelemetry and Jaeger

OpenTelemetry (OTel) is the vendor-neutral standard for generating and collecting telemetry data. By providing a single set of APIs and instrumentation libraries, OTel helps you avoid vendor lock-in and future-proof your observability strategy [1].

While OTel provides instrumentation, you still need a backend to store and visualize trace data. The OpenTelemetry Collector can process and export this data to popular backends like Jaeger or Grafana Tempo. These tools provide a UI to analyze a request's full lifecycle, helping you diagnose latency issues quickly [6].

From Insight to Action: Integrating Incident Management

Collecting observability data is only half the battle. When an alert fires from Prometheus, the real work of incident response begins. Manually correlating signals, finding the right on-call engineers, and coordinating a response is slow and error-prone, often stretching troubleshooting time from minutes to hours [3].

An incident management platform connects your observability tools to your people and processes, orchestrating the entire response lifecycle. Having effective SRE tools for incident tracking is what separates teams that are merely reactive from those that are truly resilient.

How Rootly Centralizes Your Kubernetes Incident Response

Rootly acts as the central command center for incidents, integrating with your observability stack to automate workflows and accelerate resolution. It transforms raw alerts from tools like Prometheus's Alertmanager into a streamlined, collaborative response.

When an alert triggers an incident, Rootly automatically:

Creates a dedicated Slack channel for the incident.
Assembles the correct on-call responders based on team schedules.
Pulls relevant Grafana dashboards directly into the incident channel for immediate context.
Attaches predefined runbooks with step-by-step remediation guides.
Manages stakeholder communications and automates status page updates.

Rootly handles the administrative work of incident management, freeing up engineers to focus on diagnosing the problem and restoring service. This integration is the key that allows you to build a powerful SRE observability stack for Kubernetes with Rootly.

Conclusion: Build a More Reliable System with Rootly

A complete sre observability stack for kubernetes requires more than just data collection. It demands an integrated system that combines powerful tools like Prometheus, Loki, and OpenTelemetry with an intelligent incident management platform like Rootly.

This approach empowers SRE teams to not only see what’s happening inside their Kubernetes environments but also to respond faster and more effectively when things go wrong. By connecting insight to action, you can move beyond simple monitoring and build a truly resilient system.

Ready to see how Rootly can unify your observability and incident response? Book a demo to get started.