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.
Coursera PlusMonthly 3 个月 课程4 折优惠 ,让你轻松掌握闪耀技能。立即节省
推荐体验
推荐体验
中级
Ideal for DevOps engineers, site reliability engineers, cloud engineers, and developers implementing modern observability practices.
推荐体验
推荐体验
中级
Ideal for DevOps engineers, site reliability engineers, cloud engineers, and developers implementing modern observability practices.
您将学到什么
Explain observability concepts including metrics, logs, traces, and modern monitoring practices.
Apply Prometheus and Grafana to collect, visualize, and monitor system performance metrics.
Analyze system behavior by correlating metrics, logs, and traces across distributed services.
Design an end to end observability architecture using Prometheus, Grafana, Loki, and Jaeger.
您将获得的技能
- Service Level
- Performance Metric
- Issue Tracking
- Event Monitoring
- Devops Tools
- Site Reliability Engineering
- Distributed Computing
- Incident Response
- Reliability
- Software Visualization
- System Monitoring
- Performance Analysis
- Anomaly Detection
- Dashboard Creation
- Time Series Analysis and Forecasting
- Systems Analysis
- Continuous Monitoring
要了解的详细信息
了解顶级公司的员工如何掌握热门技能

该课程共有4个模块
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.
涵盖的内容
16个视频7篇阅读材料4个作业
16个视频•总计92分钟
- Course Introduction•6分钟
- Scenario: Investigating Unexpected System Behaviour•6分钟
- What is Observability?•4分钟
- What is Monitoring?•4分钟
- Observability vs Monitoring in Modern Systems•5分钟
- The Three Pillars of Observability•7分钟
- Demonstration: Installing Prometheus for Metrics Collection•6分钟
- Demonstration: Configuring Node Exporter for Host Metrics•7分钟
- Metrics, Golden Signals, and Reliability Indicators•6分钟
- Service Reliability with SLIs, SLOs, and Error Budgets•6分钟
- Demonstration: Exploring Application Metrics Exposed with Prometheus•7分钟
- Demonstration:PromQL Queries for Latency and Error Metrics•5分钟
- Demonstration: Defining Service-Level Indicators Using Prometheus Metrics•4分钟
- Prometheus Architecture and Time-Series Data Model•7分钟
- Demonstration: Scraping Metrics from a Sample Application•6分钟
- Demonstration: Using PromQL for Aggregation and Filtering•6分钟
7篇阅读材料•总计105分钟
- Course Syllabus•15分钟
- System Signals and Telemetry Sources•15分钟
- Observability Terminology and Core Signals•15分钟
- SLIs and Reliability Metrics in Engineering•15分钟
- Persisting Metrics Using Prometheus Local Storage•15分钟
- Prometheus Querying Patterns•15分钟
- Module Summary: Observability Foundations and Metrics Engineering•15分钟
4个作业•总计33分钟
- Practice Assignment: Fundamentals of Observability and System Signals•6分钟
- Practice Assignment: Metrics Design, SLIs, and Reliability Targets•6分钟
- Practice Assignment: Metrics Storage and Querying with Prometheus•6分钟
- Knowledge Check: Observability Foundations and Metrics Engineering•15分钟
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.
涵盖的内容
12个视频4篇阅读材料4个作业
12个视频•总计63分钟
- Metrics Visualization and Dashboard Design•5分钟
- Demonstration: Installing Grafana and Connecting Prometheus•5分钟
- Demonstration: Creating Time-Series Dashboards in Grafana•5分钟
- Demonstration: Configuring Thresholds and Annotations in Grafana•5分钟
- Alerting Strategies and Alert Fatigue•5分钟
- Demonstration: Creating Alert Rules in Prometheus•5分钟
- Demonstration: Configuring Alertmanager for Notifications•5分钟
- Demonstration: Alert Trigger and Recovery Validation•6分钟
- Structured Logging and Log Pipelines•5分钟
- Demonstration: Installing Loki for Log Aggregation•5分钟
- Demonstration: Shipping Application Logs to Loki•6分钟
- Demonstration: Querying Logs Using LogQL•8分钟
4篇阅读材料•总计60分钟
- Visualization Design for Observability•15分钟
- Alerting and Incident Response Patterns•15分钟
- Logging Architecture and Retention•15分钟
- Module Summary: Visualization, Alerting, and Logging Pipelines•15分钟
4个作业•总计33分钟
- Practice Assignment: Metrics Visualization with Grafana•6分钟
- Practice Assignment: Alerting Strategies and Incident Signals•6分钟
- Practice Assignment: Centralized Logging Architecture•6分钟
- Knowledge Check: Visualization, Alerting, and Logging Pipelines•15分钟
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.
涵盖的内容
14个视频6篇阅读材料5个作业
14个视频•总计79分钟
- Distributed Tracing Concepts and Terminology•5分钟
- Trace Context, Spans, and Service Dependencies•6分钟
- Demonstration: Instrumenting an Application with OpenTelemetry SDK•6分钟
- Demonstration: Exporting Traces to Jaeger•6分钟
- Demonstration: Analyzing Request Latency Across Services in Jaeger•6分钟
- Observability Challenges in Kubernetes Environments•5分钟
- Demonstration: Collecting Kubernetes Metrics Using Prometheus•6分钟
- Demonstration: Collecting Container Logs with Fluent Bit•5分钟
- Demonstration: Tracing Requests Across Microservices in Jaeger•6分钟
- Correlation Strategies Across Telemetry Signals•6分钟
- Demonstration: Analyzing Request Latency Using Distributed Traces•7分钟
- Introduction to AI and Machine Learning in Observability•5分钟
- How Grafana Uses AI for Anomaly Detection and Insight•5分钟
- Demonstration: Enabling Machine Learning - Based Anomaly Detection in Grafana•7分钟
6篇阅读材料•总计90分钟
- Distributed Tracing with OpenTelemetry and Jaeger•15分钟
- Cloud-Native Observability Patterns•15分钟
- Investigating System Incident Using Metrics and Logs•15分钟
- Correlating Metrics, Logs, and Traces for Complete Observability•15分钟
- AI-Assisted Observability Patterns in Grafana•15分钟
- Module Summary: Distributed Tracing and End-to-End Observability•15分钟
5个作业•总计39分钟
- Practice Assignment: Distributed Tracing and Context Propagation•6分钟
- Practice Assignment: Observability for Containerized Applications•6分钟
- Practice Assignment: Correlating Metrics, Logs, and Traces•6分钟
- Practice Assignment: AI-Powered Observability with Grafana•6分钟
- Knowledge Check: Distributed Tracing and End-to-End Observability•15分钟
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.
涵盖的内容
1个视频1篇阅读材料2个作业1个讨论话题
1个视频•总计3分钟
- Course Summary•3分钟
1篇阅读材料•总计30分钟
- Practice Project: Building a Complete Observability Platform for QuantumOps Technologies•30分钟
2个作业•总计60分钟
- End Course Knowledge Check: Observability Engineering: Metrics, Logs, and Trace •30分钟
- Designing a Modern Observability Architecture Using Metrics, Logs, and Traces•30分钟
1个讨论话题•总计5分钟
- Describe Your Learning Journey•5分钟
位教师

提供方

提供方

Edureka is an online education platform focused on delivering high-quality learning to working professionals. We have the highest course completion rate in the industry and we strive to create an online ecosystem for our global learners to equip themselves with industry-relevant skills in today’s cutting edge technologies.
人们为什么选择 Coursera 来帮助自己实现职业发展

Felipe M.

Jennifer J.

Larry W.

Chaitanya A.
常见问题
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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¹ 本课程的部分作业采用 AI 评分。对于这些作业,将根据 Coursera 隐私声明使用您的数据。



