Uploaded December 2025 | Updated September 2026, 3 days ago
Your users are complaining about slow response times—sometimes 8 seconds, other times 2 seconds—but your metrics show everything is fine. Average response times look acceptable, all services report healthy, and your dashboards are green. So what's really happening? The problem is that what looks like a single user request is actually dozens of separate, independent requests cascading through your microservices. Each service only sees its own operations, with no way to know they're part of the same logical transaction. Your logs show individual services completed successfully, but you can't correlate these entries across services or identify which specific operation is causing the delay.
This video shows you exactly how to solve this blindness using distributed tracing with OpenTelemetry. You'll learn the difference between automatic and manual instrumentation, see real examples of tracing implementation in TypeScript, and analyze actual traces using Jaeger to understand request flows through complex systems. We'll cover traces, spans, context propagation, semantic conventions, sampling strategies, and how to export trace data to any backend without vendor lock-in. By the end, you'll understand why traditional observability tools can't see what's happening in distributed systems and how to implement tracing that reveals the complete journey of every request through your architecture.
#DistributedTracing #OpenTelemetry #Microservices
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Sponsor: DevStats
🔗 https://devstats.plug.dev/5W1oh9J
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Consider joining the channel: youtube.com/c/devopstoolkit/join
▬▬▬▬▬▬ 🔗 Additional Info 🔗 ▬▬▬▬▬▬
➡ Transcript and commands: https://devopstoolkit.live/observability/distributed-tracing-explained-opentelemetry--jaeger-tutorial
🔗 OpenTelemetry: opentelemetry.io
▬▬▬▬▬▬ 💰 Sponsorships 💰 ▬▬▬▬▬▬
If you are interested in sponsoring this channel, please visit https://devopstoolkit.live/sponsor for more information. Alternatively, feel free to contact me over Twitter or LinkedIn (see below).
▬▬▬▬▬▬ 👋 Contact me 👋 ▬▬▬▬▬▬
➡ BlueSky: https://vfarcic.bsky.social
➡ LinkedIn: linkedin.com/in/viktorfarcic
▬▬▬▬▬▬ 🚀 Other Channels 🚀 ▬▬▬▬▬▬
🎤 Podcast: devopsparadox.com
💬 Live streams: youtube.com/c/DevOpsParadox
▬▬▬▬▬▬ ⏱ Timecodes ⏱ ▬▬▬▬▬▬
00:00 Distributed Tracing with OpenTelemetry (OTEL)
01:18 DevStats (sponsor)
02:34 Microservices Performance Mystery
06:24 OpenTelemetry Distributed Tracing
10:57 Analyzing Traces with Jaeger
14:53 Understanding OpenTelemetry Traces
20:14 Tracing Solves Observability Blindness
Your users are complaining about slow response times—sometimes 8 seconds, other times 2 seconds—but your metrics show everything is fine. Average response times look acceptable, all services report healthy, and your dashboards are green. So what's really happening? The problem is that what looks like a single user request is actually dozens of separate, independent requests cascading through your microservices. Each service only sees its own operations, with no way to know they're part of the same logical transaction. Your logs show individual services completed successfully, but you can't correlate these entries across services or identify which specific operation is causing the delay.
This video shows you exactly how to solve this blindness using distributed tracing with OpenTelemetry. You'll learn the difference between automatic and manual instrumentation, see real examples of tracing implementation in TypeScript, and analyze actual traces using Jaeger to understand request flows through complex systems. We'll cover traces, spans, context propagation, semantic conventions, sampling strategies, and how to export trace data to any backend without vendor lock-in. By the end, you'll understand why traditional observability tools can't see what's happening in distributed systems and how to implement tracing that reveals the complete journey of every request through your architecture.
#DistributedTracing #OpenTelemetry #Microservices
▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
Sponsor: DevStats
🔗 https://devstats.plug.dev/5W1oh9J
▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
Consider joining the channel: youtube.com/c/devopstoolkit/join
▬▬▬▬▬▬ 🔗 Additional Info 🔗 ▬▬▬▬▬▬
➡ Transcript and commands: https://devopstoolkit.live/observability/distributed-tracing-explained-opentelemetry--jaeger-tutorial
🔗 OpenTelemetry: opentelemetry.io
▬▬▬▬▬▬ 💰 Sponsorships 💰 ▬▬▬▬▬▬
If you are interested in sponsoring this channel, please visit https://devopstoolkit.live/sponsor for more information. Alternatively, feel free to contact me over Twitter or LinkedIn (see below).
▬▬▬▬▬▬ 👋 Contact me 👋 ▬▬▬▬▬▬
➡ BlueSky: https://vfarcic.bsky.social
➡ LinkedIn: linkedin.com/in/viktorfarcic
▬▬▬▬▬▬ 🚀 Other Channels 🚀 ▬▬▬▬▬▬
🎤 Podcast: devopsparadox.com
💬 Live streams: youtube.com/c/DevOpsParadox
▬▬▬▬▬▬ ⏱ Timecodes ⏱ ▬▬▬▬▬▬
00:00 Distributed Tracing with OpenTelemetry (OTEL)
01:18 DevStats (sponsor)
02:34 Microservices Performance Mystery
06:24 OpenTelemetry Distributed Tracing
10:57 Analyzing Traces with Jaeger
14:53 Understanding OpenTelemetry Traces
20:14 Tracing Solves Observability Blindness
