Are your monitoring tools leaving you blind to what's really happening in your distributed .NET systems? As applications grow more complex, surface-level dashboards and siloed logs aren't enough. OpenTelemetry for Unified Observability empowers developers, DevOps engineers, and SREs to gain full visibility into system behavior using open-source, vendor-neutral tools. In this hands-on course, you'll learn how to instrument .NET applications with the OpenTelemetry SDK, export telemetry data to Jaeger and Prometheus, and use traces, metrics, and logs to pinpoint performance issues, uncover hidden bottlenecks, and resolve incidents faster. Through real-world scenarios, coach-guided investigations, and a capstone project, you'll build a complete observability stack and gain practical experience diagnosing and optimizing production systems.
This course is ideal for developers, DevOps engineers, SREs, and platform teams who want to improve reliability and performance using open-source, vendor-neutral observability tools with OpenTelemetry.
Learners should be familiar with basic understanding of .NET applications and familiarity with containers, cloud, or distributed systems helpful.
By the end of the course, you will be equipped to integrate OpenTelemetry into your applications and use observability as a strategic advantage in DevOps, Site Reliability Engineering (SRE), and modern software development practices.
Learners will explore the fundamentals of observability by examining metrics, logs, and traces as the three essential pillars. They will also investigate the problems caused by fragmented monitoring tools and discover how OpenTelemetry addresses these challenges with a vendor-neutral, standardized approach. By the end, learners will understand how OpenTelemetry simplifies telemetry collection and strengthens troubleshooting in modern .NET systems.
Das ist alles enthalten
4 Videos2 Lektüren1 peer review
Infos zu Modulinhalt anzeigen
4 Videos•Insgesamt 27 Minuten
The Journey from Monitoring to Observability•3 Minuten
The Three Pillars: Traces, Metrics, and Logs•8 Minuten
What is OpenTelemetry•6 Minuten
How OpenTelemetry Standardizes Observability•9 Minuten
2 Lektüren•Insgesamt 10 Minuten
Welcome to the Course: Course Overview•5 Minuten
From Logs to Unified Observability•5 Minuten
1 peer review•Insgesamt 20 Minuten
Hands-On-Learning: Identify the Missing Pillar at StreamFlix Media•20 Minuten
Hands-On OpenTelemetry with .NET
Modul 2•1 Stunde abzuschließen
Moduldetails
Learners will gain hands-on experience installing and configuring the OpenTelemetry SDK in .NET applications. They will instrument an ASP.NET Core API to capture metrics, logs, and distributed traces, then export this telemetry to backends like Jaeger, Prometheus, and Azure Monitor. By the end of the course, learners will understand how to apply unified observability practices to monitor, debug, and optimize modern microservices and cloud-native systems. In this module, learners move from theory to practice by installing and configuring the OpenTelemetry SDK in a .NET API and exporting telemetry to Jaeger, Prometheus, and Azure Monitor. A coach dialogue guides them through diagnosing bottlenecks using traces and metrics, while step-by-step videos demonstrate SDK setup, configuration, and visualization with Docker-based backends. A written guide provides a lasting reference, and a hands-on lab challenges learners to instrument and trace API calls, reinforcing how unified observability enables real-world debugging and optimization.
Das ist alles enthalten
4 Videos1 Lektüre1 peer review
Infos zu Modulinhalt anzeigen
4 Videos•Insgesamt 43 Minuten
Installing the OpenTelemetry SDK in .NET •11 Minuten
Custom Spans and Metrics with OpenTelemetry in .NET •7 Minuten
Configuring Traces and Metrics•10 Minuten
Running Jaeger and Prometheus with Docker•14 Minuten
Hands-On-Learning: Instrument and Trace an API Call•20 Minuten
Unified Observability in Action
Modul 3•2 Stunden abzuschließen
Moduldetails
Learners will explore how unified observability through OpenTelemetry enables faster root cause analysis and proactive performance monitoring. They will see how combining metrics, logs, and traces provides a complete view of .NET applications in action. By applying these practices, learners will be able to diagnose issues more effectively and ensure their systems remain reliable and performant. In this final section, learners apply everything they’ve learned to diagnose real microservice issues and build confidence as observability practitioners. A coach dialogue introduces a root cause mystery, followed by demonstrations of analyzing traces in Jaeger and monitoring metrics in Prometheus, showing how these tools complement each other. A reading on reliability engineering connects observability to resilience practices, while a hands-on lab challenges learners to troubleshoot a microservice outage. The course concludes with a capstone project to build a full observability stack using OpenTelemetry, a graded knowledge check, and career resources to help learners explore observability engineering roles. An outro video and promotional piece reinforce next steps and the broader industry relevance of OpenTelemetry.
Das ist alles enthalten
4 Videos1 Lektüre1 Aufgabe2 peer reviews
Infos zu Modulinhalt anzeigen
4 Videos•Insgesamt 35 Minuten
Analyzing Traces in Jaeger•11 Minuten
Monitoring Metrics in Prometheus•12 Minuten
Bringing It All Together•8 Minuten
Next Steps with OpenTelemetry•3 Minuten
1 Lektüre•Insgesamt 5 Minuten
How Observability Transforms Reliability Engineering•5 Minuten
1 Aufgabe•Insgesamt 30 Minuten
Opentelemetry for Unified Observability•30 Minuten
2 peer reviews•Insgesamt 80 Minuten
Hands-On-Learning: Diagnose a Microservice Outage•20 Minuten
Project: Build Your Own Observability Stack with OpenTelemetry•60 Minuten
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What does unified observability with OpenTelemetry mean in this course?
In this course, unified observability with OpenTelemetry means using a vendor-neutral standard to collect traces, metrics, and logs so an application can be understood as one connected system. The focus is on using that shared telemetry to investigate performance issues and incidents instead of relying on separate dashboards or isolated log streams.
When would you use unified observability with OpenTelemetry?
You would use it when a service feels slow, unreliable, or hard to diagnose and a single signal does not explain the full problem. The course presents it as a practical way to investigate distributed application behavior by following evidence across traces, metrics, and logs.
How does unified observability with OpenTelemetry fit into a broader workflow?
It fits into the broader software workflow once an application is instrumented and then stays useful during everyday operations, debugging, and incident response. In this course, it serves as the bridge between emitting telemetry and using that telemetry to tune performance and find root causes.
How is unified observability with OpenTelemetry different from traditional monitoring?
Traditional monitoring mainly tells you that something changed, while unified observability helps you investigate why it changed across the full request path. The course emphasizes correlating traces, metrics, and logs through OpenTelemetry instead of treating each source as a separate troubleshooting tool.
Do you need any prerequisites before learning unified observability with OpenTelemetry?
A basic understanding of .NET applications is helpful, and familiarity with containers, cloud environments, or distributed systems can make the hands-on work easier. Because the course is intermediate, it assumes you can follow application setup and reason about how services interact.
What tools, platforms, or methods are used in this course?
The course centers on OpenTelemetry in .NET and uses backends such as Jaeger, Prometheus, and Azure Monitor to view telemetry. The main method is to instrument applications and then work with traces, metrics, and logs together during investigation.
What specific tasks will you practice or complete in this course?
You practice instrumenting a .NET API, configuring telemetry export, and adding both built-in and custom signals to make application behavior visible. You also work through reading traces, metrics, and logs together, and diagnosing bottlenecks or outages in a small observability setup.