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.
What's included
16 videos7 readings4 assignments
Show info about module content
16 videos•Total 92 minutes
Course Introduction•6 minutes
Scenario: Investigating Unexpected System Behaviour•6 minutes
What is Observability?•4 minutes
What is Monitoring?•4 minutes
Observability vs Monitoring in Modern Systems•5 minutes
The Three Pillars of Observability•7 minutes
Demonstration: Installing Prometheus for Metrics Collection•6 minutes
Demonstration: Configuring Node Exporter for Host Metrics•7 minutes
Metrics, Golden Signals, and Reliability Indicators•6 minutes
Service Reliability with SLIs, SLOs, and Error Budgets•6 minutes
Demonstration: Exploring Application Metrics Exposed with Prometheus•7 minutes
Demonstration:PromQL Queries for Latency and Error Metrics•5 minutes
Demonstration: Defining Service-Level Indicators Using Prometheus Metrics•4 minutes
Prometheus Architecture and Time-Series Data Model•7 minutes
Demonstration: Scraping Metrics from a Sample Application•6 minutes
Demonstration: Using PromQL for Aggregation and Filtering•6 minutes
7 readings•Total 105 minutes
Course Syllabus•15 minutes
System Signals and Telemetry Sources•15 minutes
Observability Terminology and Core Signals•15 minutes
SLIs and Reliability Metrics in Engineering•15 minutes
Persisting Metrics Using Prometheus Local Storage•15 minutes
Prometheus Querying Patterns•15 minutes
Module Summary: Observability Foundations and Metrics Engineering•15 minutes
4 assignments•Total 33 minutes
Practice Assignment: Fundamentals of Observability and System Signals•6 minutes
Practice Assignment: Metrics Design, SLIs, and Reliability Targets•6 minutes
Practice Assignment: Metrics Storage and Querying with Prometheus•6 minutes
Knowledge Check: Observability Foundations and Metrics Engineering•15 minutes
Visualization, Alerting, and Logging Pipelines
Module 2•3 hours to complete
Module details
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.
What's included
12 videos4 readings4 assignments
Show info about module content
12 videos•Total 63 minutes
Metrics Visualization and Dashboard Design•5 minutes
Demonstration: Installing Grafana and Connecting Prometheus•5 minutes
Demonstration: Creating Time-Series Dashboards in Grafana•5 minutes
Demonstration: Configuring Thresholds and Annotations in Grafana•5 minutes
Alerting Strategies and Alert Fatigue•5 minutes
Demonstration: Creating Alert Rules in Prometheus•5 minutes
Demonstration: Configuring Alertmanager for Notifications•5 minutes
Demonstration: Alert Trigger and Recovery Validation•6 minutes
Structured Logging and Log Pipelines•5 minutes
Demonstration: Installing Loki for Log Aggregation•5 minutes
Demonstration: Shipping Application Logs to Loki•6 minutes
Demonstration: Querying Logs Using LogQL•8 minutes
4 readings•Total 60 minutes
Visualization Design for Observability•15 minutes
Alerting and Incident Response Patterns•15 minutes
Logging Architecture and Retention•15 minutes
Module Summary: Visualization, Alerting, and Logging Pipelines•15 minutes
4 assignments•Total 33 minutes
Practice Assignment: Metrics Visualization with Grafana•6 minutes
Practice Assignment: Alerting Strategies and Incident Signals•6 minutes
Practice Assignment: Centralized Logging Architecture•6 minutes
Knowledge Check: Visualization, Alerting, and Logging Pipelines•15 minutes
Distributed Tracing and End-to-End Observability
Module 3•4 hours to complete
Module details
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.
What's included
14 videos6 readings5 assignments
Show info about module content
14 videos•Total 79 minutes
Distributed Tracing Concepts and Terminology•5 minutes
Trace Context, Spans, and Service Dependencies•6 minutes
Demonstration: Instrumenting an Application with OpenTelemetry SDK•6 minutes
Demonstration: Exporting Traces to Jaeger•6 minutes
Demonstration: Analyzing Request Latency Across Services in Jaeger•6 minutes
Observability Challenges in Kubernetes Environments•5 minutes
Demonstration: Collecting Kubernetes Metrics Using Prometheus•6 minutes
Demonstration: Collecting Container Logs with Fluent Bit•5 minutes
Demonstration: Tracing Requests Across Microservices in Jaeger•6 minutes
Correlation Strategies Across Telemetry Signals•6 minutes
Demonstration: Analyzing Request Latency Using Distributed Traces•7 minutes
Introduction to AI and Machine Learning in Observability•5 minutes
How Grafana Uses AI for Anomaly Detection and Insight•5 minutes
Demonstration: Enabling Machine Learning - Based Anomaly Detection in Grafana•7 minutes
6 readings•Total 90 minutes
Distributed Tracing with OpenTelemetry and Jaeger•15 minutes
Cloud-Native Observability Patterns•15 minutes
Investigating System Incident Using Metrics and Logs•15 minutes
Correlating Metrics, Logs, and Traces for Complete Observability•15 minutes
AI-Assisted Observability Patterns in Grafana•15 minutes
Module Summary: Distributed Tracing and End-to-End Observability•15 minutes
5 assignments•Total 39 minutes
Practice Assignment: Distributed Tracing and Context Propagation•6 minutes
Practice Assignment: Observability for Containerized Applications•6 minutes
Practice Assignment: Correlating Metrics, Logs, and Traces•6 minutes
Practice Assignment: AI-Powered Observability with Grafana•6 minutes
Knowledge Check: Distributed Tracing and End-to-End Observability•15 minutes
Course Wrap-Up and Assessment
Module 4•2 hours to complete
Module details
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.
What's included
1 video1 reading2 assignments1 discussion prompt
Show info about module content
1 video•Total 3 minutes
Course Summary•3 minutes
1 reading•Total 30 minutes
Practice Project: Building a Complete Observability Platform for QuantumOps Technologies•30 minutes
2 assignments•Total 60 minutes
End Course Knowledge Check: Observability Engineering: Metrics, Logs, and Trace •30 minutes
Designing a Modern Observability Architecture Using Metrics, Logs, and Traces•30 minutes
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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.