Streamlining Telemetry Data with Observability Pipelines

Introduction

Imagine you’re running a cloud-native system. Everything seems fine, until suddenly, something breaks. You rush to check your logs, but there are millions of entries. Your dashboards are flooded with too much data but too few answers. Meanwhile, your Kubernetes clusters are generating even more telemetry, making it harder to pinpoint the issue.
Modern applications produce massive amounts of metrics, logs, and traces, but without a proper system, all this information turns into noise, slowing down troubleshooting and increasing costs. Observability Pipelines offer a smarter way to collect, process, and route telemetry data, ensuring that only the most relevant insights reach your monitoring tools.

Takeaways

In this session, we’ll explore how to streamline observability data using Grafana Alloy, OpenTelemetry Collector, and Grafana’s Mimir, Tempo, and Loki. Learn how to efficiently handle telemetry, reduce noise, and improve system performance. By the end, you’ll have a roadmap to build an observability pipeline that keeps your cloud-native environments efficient, cost-effective, and easy to troubleshoot.

Target Audience

This talk will be helpful for SREs, DevOps, and platform engineers working with on-prem and cloud-native systems, especially those facing telemetry overload or high observability costs. While the topic leans intermediate, the session is beginner-friendly. No matter your experience level, you’ll walk away with something valuable.

About Me

Aftab is a DevOps Engineer specializing in cloud-native technologies, Observability, and platform reliability. He’s also a Grafana Champion and an active contributor to the Grafana ecosystem. With expertise in Cloud, Containerization, and Observability, he builds reliable platforms and contributes to open-source projects. He is also a frequent speaker at tech conferences, and actively shares his insights through talks, workshops, and community meetups.