Ever experienced downtime on your favorite app? It’s incredibly frustrating, right? As users, we feel the impact immediately, often switching to another platform in search of stability. For companies, however, the stakes are much higher, downtime can lead to millions in lost revenue. Modern applications are complex, distributed, and constantly evolving. A single failure can cascade into major outages, frustrating users and overwhelming teams. Observability isn't just about catching issues - it’s about understanding why they happen. Traditionally seen as an SRE concern, observability is now a developer’s responsibility. Without it, debugging becomes a guessing game. Many teams start with convenient observability tools, only to realize too late that they’ve locked themselves into rigid, expensive ecosystems.

Observability shouldn’t be scary, it should be open, flexible, and built for change. But as we scale or migrate, traditional tools often become bottlenecks rather than solutions. This is where OpenTelemetry redefines everything. As an open standard, it ensures portability, cost efficiency, and true ownership of telemetry data, putting control back in developers' hands. In this talk, we’ll break down how to instrument Python applications, collect and process telemetry data, and gain actionable insights without vendor lock-in. Attendees will walk away with practical skills and a clear understanding of how adopting open observability makes debugging faster, systems more reliable, and developers more confident. Observability isn’t optional - it’s essential.

During this session, I’ll cover the following 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 getting started with OpenTelemetry, including a live code demo.

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