What was your Python up to at 3am?
summary
Shows how to get actionable traces from Python with OpenTelemetry and Honeycomb, wiring Flask and requests into OpenTelemetry tracing and using context managers to create spans, counters and baggage that carry end user and account IDs. Covers boilerplate hookup, automatic instrumentation with 33 automatic integrations, sampling strategies, and practical limits like 100 kilobytes per event and cardinality costs so the result is searchable, usable telemetry rather than noisy logs.
AI-written summary · about
chapters (9)
- 0:00Intro
- 1:12Welcome
- 1:59What is Open Telemetry
- 2:56What are logs metrics and traces
- 5:36OpenTelemetry
- 9:37Python
- 13:12Vendors
- 19:12Advice
- 26:32Questions
related talks
17mEfficient Python Observability with OpenTelemetry
24m"Introduction to OpenTelemetry with Python"
23mGetting Started with OpenTelemetry in Python
24mHow To Monitor and Troubleshoot Applications using OpenTelemetry
14mGetting Started with OpenTelemetry in Python
38mEnhance your Python application observability
28m"What Happened in Production?! Instrumenting with OpenTelemetry"
30mObserving Python applications with OpenTelemetry