Ever had your app crash at the worst moment, during checkout or a key transaction? When that happens, users leave fast. Behind each crash is a bigger story: alerts firing, teams scrambling and no clear root cause. Modern systems are fast, complex and full of hidden failure points. One small issue can ripple out quickly. This talk frames observability not as an ops task but as core engineering. Built on open standards like OpenTelemetry, it avoids vendor lock-in and puts you in control. You’ll learn how to instrument Python app, process telemetry and export it for analysis. It's not just about logs, metrics, or traces—it’s about clarity. If you're a developer or the one on-call when things break, this session will give you practical skills and a new way to think about shared system insight.

Key topics:

• The evolution of observability and why it has become essential over the past few decades.

• A deep dive into core telemetry signals: Logs, Metrics, and Traces.

• The challenges developers face with modern observability, and how adopting OpenTelemetry can address these issues.

• A comparison between traditional approaches and the OpenTelemetry method, focusing on everything from easy Python code instrumentation to advanced data processing and seamless telemetry export to any observability backend—without vendor lock-in.

• Different sampling techniques like head, tail, probabilistic, allow you to have full control over the data you ingest and its associated costs with different setup strategies.

• Best practices for reducing observability costs with telemetry pipelines.

• Getting started with OpenTelemetry, including a live code demo.

• Future of AI in the of open-source observability and few ongoing work on OpenTelemetry with eBPF.