This program explores how observability enables engineers to understand, monitor, and troubleshoot modern distributed systems by using metrics, logs, and traces. You’ll begin by learning the foundational principles of observability, understanding how it differs from traditional monitoring, and exploring the three pillars of observability. Through hands-on demonstrations with Prometheus and Node Exporter, you will learn how system telemetry is collected and how metrics provide visibility into infrastructure and application behavior.
You’ll then design reliability-focused metrics strategies using concepts such as Golden Signals, Service-Level Indicators (SLIs), Service-Level Objectives (SLOs), and error budgets. Practical demonstrations show how to collect application metrics, write PromQL queries, and analyze latency and error patterns. You will also explore metrics visualization and alerting by building Grafana dashboards, configuring thresholds, and creating alert rules with Prometheus and Alertmanager to detect operational incidents quickly.
Next, you’ll examine centralized logging and distributed tracing, learning how logs and traces provide deeper insight into system behavior. Using Loki, Fluent Bit, OpenTelemetry, and Jaeger, you will explore how logs are aggregated, how requests are traced across microservices, and how engineers analyze service dependencies and request latency. You will also learn how modern observability platforms use AI-powered anomaly detection in Grafana to identify unusual system behavior and support proactive monitoring.
By the end of this program, you will be able to:
-Explain the principles of observability and differentiate it from monitoring.
-Collect and analyze system metrics using Prometheus and PromQL.
-Design dashboards and visualizations using Grafana.
-Configure alerts and incident notifications using Prometheus and Alertmanager.
-Implement centralized logging pipelines using Loki and Fluent Bit.
-Instrument distributed systems with OpenTelemetry and analyze traces using Jaeger.
This program is designed for DevOps engineers, site reliability engineers, software developers, and cloud engineers who want to improve system reliability and operational visibility. A basic understanding of cloud infrastructure, containerized systems, and application architecture will help maximize your learning experience.
Learners need a reliable internet connection, a modern web browser, and access to commonly used observability tools; no specialized hardware or complex infrastructure setup is required.
Join us to master modern observability practices and learn how engineering teams monitor, diagnose, and optimize distributed systems using powerful open-source observability technologies.
Explore core observability and metrics engineering concepts by examining telemetry signals in modern systems. Learn to collect and analyze metrics using Prometheus and Node Exporter, query data with PromQL, and design service-level indicators to monitor performance and system behavior.
Das ist alles enthalten
16 Videos7 Lektüren4 Aufgaben
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16 Videos•Insgesamt 92 Minuten
Course Introduction•6 Minuten
Scenario: Investigating Unexpected System Behaviour•6 Minuten
What is Observability?•4 Minuten
What is Monitoring?•4 Minuten
Observability vs Monitoring in Modern Systems•5 Minuten
The Three Pillars of Observability•7 Minuten
Demonstration: Installing Prometheus for Metrics Collection•6 Minuten
Demonstration: Configuring Node Exporter for Host Metrics•7 Minuten
Metrics, Golden Signals, and Reliability Indicators•6 Minuten
Service Reliability with SLIs, SLOs, and Error Budgets•6 Minuten
Demonstration: Exploring Application Metrics Exposed with Prometheus•7 Minuten
Demonstration:PromQL Queries for Latency and Error Metrics•5 Minuten
Demonstration: Defining Service-Level Indicators Using Prometheus Metrics•4 Minuten
Prometheus Architecture and Time-Series Data Model•7 Minuten
Demonstration: Scraping Metrics from a Sample Application•6 Minuten
Demonstration: Using PromQL for Aggregation and Filtering•6 Minuten
7 Lektüren•Insgesamt 105 Minuten
Course Syllabus•15 Minuten
System Signals and Telemetry Sources•15 Minuten
Observability Terminology and Core Signals•15 Minuten
SLIs and Reliability Metrics in Engineering•15 Minuten
Persisting Metrics Using Prometheus Local Storage•15 Minuten
Prometheus Querying Patterns•15 Minuten
Module Summary: Observability Foundations and Metrics Engineering•15 Minuten
4 Aufgaben•Insgesamt 33 Minuten
Practice Assignment: Fundamentals of Observability and System Signals•6 Minuten
Practice Assignment: Metrics Design, SLIs, and Reliability Targets•6 Minuten
Practice Assignment: Metrics Storage and Querying with Prometheus•6 Minuten
Knowledge Check: Observability Foundations and Metrics Engineering•15 Minuten
Visualization, Alerting, and Logging Pipelines
Modul 2•3 Stunden abzuschließen
Moduldetails
Explore how observability platforms enable visualization, alerting, and centralized logging for effective monitoring. Learn how dashboards, alerts, and log pipelines provide system visibility. Gain hands-on experience with Grafana, Prometheus Alertmanager, and Loki to support monitoring and incident investigation.
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12 Videos4 Lektüren4 Aufgaben
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12 Videos•Insgesamt 63 Minuten
Metrics Visualization and Dashboard Design•5 Minuten
Demonstration: Installing Grafana and Connecting Prometheus•5 Minuten
Demonstration: Creating Time-Series Dashboards in Grafana•5 Minuten
Demonstration: Configuring Thresholds and Annotations in Grafana•5 Minuten
Alerting Strategies and Alert Fatigue•5 Minuten
Demonstration: Creating Alert Rules in Prometheus•5 Minuten
Demonstration: Configuring Alertmanager for Notifications•5 Minuten
Demonstration: Alert Trigger and Recovery Validation•6 Minuten
Structured Logging and Log Pipelines•5 Minuten
Demonstration: Installing Loki for Log Aggregation•5 Minuten
Demonstration: Shipping Application Logs to Loki•6 Minuten
Demonstration: Querying Logs Using LogQL•8 Minuten
4 Lektüren•Insgesamt 60 Minuten
Visualization Design for Observability•15 Minuten
Alerting and Incident Response Patterns•15 Minuten
Logging Architecture and Retention•15 Minuten
Module Summary: Visualization, Alerting, and Logging Pipelines•15 Minuten
4 Aufgaben•Insgesamt 33 Minuten
Practice Assignment: Metrics Visualization with Grafana•6 Minuten
Practice Assignment: Alerting Strategies and Incident Signals•6 Minuten
Practice Assignment: Centralized Logging Architecture•6 Minuten
Knowledge Check: Visualization, Alerting, and Logging Pipelines•15 Minuten
Distributed Tracing and End-to-End Observability
Modul 3•4 Stunden abzuschließen
Moduldetails
Strengthen system visibility by implementing distributed tracing and end-to-end observability. Learn how requests flow across microservices using OpenTelemetry and Jaeger to analyze dependencies and latency. Correlate metrics, logs, and traces to investigate incidents, and use AI-powered anomaly detection in Grafana to improve system reliability.
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14 Videos6 Lektüren5 Aufgaben
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14 Videos•Insgesamt 79 Minuten
Distributed Tracing Concepts and Terminology•5 Minuten
Trace Context, Spans, and Service Dependencies•6 Minuten
Demonstration: Instrumenting an Application with OpenTelemetry SDK•6 Minuten
Demonstration: Exporting Traces to Jaeger•6 Minuten
Demonstration: Analyzing Request Latency Across Services in Jaeger•6 Minuten
Observability Challenges in Kubernetes Environments•5 Minuten
Demonstration: Collecting Kubernetes Metrics Using Prometheus•6 Minuten
Demonstration: Collecting Container Logs with Fluent Bit•5 Minuten
Demonstration: Tracing Requests Across Microservices in Jaeger•6 Minuten
Correlation Strategies Across Telemetry Signals•6 Minuten
Demonstration: Analyzing Request Latency Using Distributed Traces•7 Minuten
Introduction to AI and Machine Learning in Observability•5 Minuten
How Grafana Uses AI for Anomaly Detection and Insight•5 Minuten
Demonstration: Enabling Machine Learning - Based Anomaly Detection in Grafana•7 Minuten
6 Lektüren•Insgesamt 90 Minuten
Distributed Tracing with OpenTelemetry and Jaeger•15 Minuten
Cloud-Native Observability Patterns•15 Minuten
Investigating System Incident Using Metrics and Logs•15 Minuten
Correlating Metrics, Logs, and Traces for Complete Observability•15 Minuten
AI-Assisted Observability Patterns in Grafana•15 Minuten
Module Summary: Distributed Tracing and End-to-End Observability•15 Minuten
5 Aufgaben•Insgesamt 39 Minuten
Practice Assignment: Distributed Tracing and Context Propagation•6 Minuten
Practice Assignment: Observability for Containerized Applications•6 Minuten
Practice Assignment: Correlating Metrics, Logs, and Traces•6 Minuten
Practice Assignment: AI-Powered Observability with Grafana•6 Minuten
Knowledge Check: Distributed Tracing and End-to-End Observability•15 Minuten
Course Wrap-Up and Assessment
Modul 4•2 Stunden abzuschließen
Moduldetails
This module assesses your understanding of the observability concepts covered in the course. Apply your knowledge by designing a complete observability stack that integrates metrics, dashboards, alerting, logging, and tracing. Complete a graded assessment to demonstrate your ability to design end-to-end observability architectures.
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1 Video1 Lektüre2 Aufgaben1 Diskussionsthema
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1 Video•Insgesamt 3 Minuten
Course Summary•3 Minuten
1 Lektüre•Insgesamt 30 Minuten
Practice Project: Building a Complete Observability Platform for QuantumOps Technologies•30 Minuten
2 Aufgaben•Insgesamt 60 Minuten
End Course Knowledge Check: Observability Engineering: Metrics, Logs, and Trace •30 Minuten
Designing a Modern Observability Architecture Using Metrics, Logs, and Traces•30 Minuten
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This course is ideal for DevOps engineers, site reliability engineers, software developers, cloud engineers, and IT professionals interested in implementing modern observability practices. It is also suitable for professionals who want to improve system monitoring, incident detection, and troubleshooting in distributed and cloud-native environments.
What topics are covered in this course?
The course covers observability fundamentals, metrics engineering, monitoring strategies, and reliability practices. You will learn how to collect and analyze metrics using Prometheus, visualize system performance with Grafana, configure alerts using Alertmanager, implement centralized logging with Loki, and trace requests across microservices using OpenTelemetry and Jaeger.
Will I get hands-on practice with observability tools?
Yes! The course includes demonstrations and practice assignments using industry-standard observability tools. You will work with Prometheus, Grafana, Loki, Fluent Bit, OpenTelemetry, and Jaeger to collect metrics, build dashboards, configure alerts, aggregate logs, and analyze distributed traces across services.
What skills will I gain from this course?
By the end of this course, you will be able to design observability architectures, collect and analyze system metrics, create monitoring dashboards, configure alerting systems, implement centralized logging pipelines, and trace requests across distributed services. You will also learn how to correlate metrics, logs, and traces to diagnose system incidents effectively.
How long will it take to complete the course?
The course is designed to be completed in about 4 weeks, with a recommended study pace of 3–4 hours per week. You can progress at your own pace, revisiting videos, demonstrations, and practice exercises whenever needed.
Do I need programming knowledge to take this course?
Basic familiarity with cloud systems, applications, or infrastructure is helpful but not strictly required. The course explains concepts step by step and demonstrates how to use observability tools such as Prometheus, Grafana, and Loki. Some exposure to DevOps or system monitoring concepts will help you get the most out of the course.
What career opportunities can this course lead to?
Mastering observability tools and practices can support roles in DevOps engineering, site reliability engineering (SRE), cloud engineering, platform engineering, and infrastructure monitoring. These skills are highly valued for managing distributed systems, improving reliability, and maintaining production environments.
Will I receive a certificate upon completion?
Yes, you will receive a certificate of completion after successfully finishing all course modules and assessments. This certificate demonstrates your knowledge of observability tools, monitoring strategies, and modern system reliability practices.
How is this course different from other observability or monitoring courses?
Unlike general monitoring courses, this program focuses on end-to-end observability practices. It combines metrics, logging, tracing, alerting, and AI-powered anomaly detection into a unified observability strategy, with hands-on demonstrations using tools such as Prometheus, Grafana, Loki, OpenTelemetry, and Jaeger.
When will I have access to the lectures and assignments?
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I purchase the Certificate?
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
Finanzielle Unterstützung verfügbar, weitere Informationen
¹ Einige Aufgaben in diesem Kurs werden mit AI bewertet. Für diese Aufgaben werden Ihre Daten in Übereinstimmung mit Datenschutzhinweis von Courseraverwendet.