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Monitoring and Observability for Development and DevOps

IBM via Coursera


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Application developers and DevOps professionals must ensure their app works at its best. However, these app may need help with bugs, slow speed, or subpar performance. Professionals need to monitor and observe its performance continually. Application monitoring involves identifying, measuring, and evaluating the effectiveness of an application. On the other hand, Observability refers to how well an app can be monitored by the data obtained from monitoring. Both monitoring and observability are necessary to gain insights into the system and ensure its proper functioning. This course thoroughly introduces monitoring and observability, covering fundamental concepts and popular tools like Prometheus, Grafana, Mezmo (LogDNA), and Instana. You will also learn about the three pillars of observability and tracing for container applications and gain hands-on experience with the OpenTelemetry framework. Throughout the course, you will complete interactive hands-on labs to apply your knowledge, and gain experience with the tools and techniques used by software and DevOps professionals. By the end of this course, you will be able to demonstrate your knowledge of monitoring and observability, and you will gain the confidence to perform these tasks in a practical setting.


  •  Introduction to Monitoring for Applications
    • This week, you will be introduced to application monitoring, common terms used in monitoring, and why monitoring matters to developers. You'll also learn about the types of monitoring that give you visibility into app performance and connected information technology (IT) systems. You'll become familiar with the four Golden Signals of Monitoring and learn to use the Golden Signals to improve your monitoring systems. Then, you will explore the differences between the Monitoring and Evaluation processes. You'll learn that monitoring is a routine, ongoing process, while evaluation is a long-term process. You'll learn more about the components of monitoring, including metrics, observability, and alerts. You'll also explore the importance of tracking host-based, application, network and connectivity, and server pool metrics. Finally, you'll learn about the need for application monitoring and its importance.
  • Monitoring Systems and Techniques
    • This week, you will learn about synthetic monitoring and its importance. You’ll also explore the synthetic monitoring tools, their uses, as well as features. You will gain insights into how application monitoring allows developers to observe applications and how monitoring can provide valuable insights into application performance. You’ll learn about Prometheus and the benefits of using an analytics tool. You’ll also learn about Grafana, which is typically used with Prometheus. You’ll explore how a visualization tool, like Grafana, can organize all of your monitoring data. Additionally, you’ll discover how the right visualization tool can help your organization and that visualization includes many options, like charts, graphs, and timelines. Finally, you’ll learn about alerting, the responsive part of a monitoring system, and you’ll learn about the metric, log, activity log, and smart detection alerts.
  • Methodologies and Tools in Logging
    • In this module, you will explore the concept of application logging and its importance. You will discover the benefits of using log monitoring tools and their features. Further, you will be introduced to distributed logging and tracing techniques. You’ll also learn about the key concepts in distributed tracing and the steps to implement distributed logging. You will explore how to implement logging and the different types of logs. You will gain insight into formatting, parsing, and retention of logs. Further, you will identify the major reasons to store log data. You will explore the analytical dimensions that suggest how long the retention period for log data should be. You will also learn about a few best practices for storing logs. Further, you will explore Mezmo, its use cases, and its features. Finally, you will be introduced to working with Mezmo and the methods for ingesting log data on the Mezmo platform.
  • Observability and Concepts
    • In this module, you will learn about observability, its benefits, and the three pillars of observability. You’ll explore the concept of cloud native observability, its tools, and the pillars of cloud enterprise observability Further, you will be introduced to the concept of sampling in logging and its advantages and disadvantages and also learn about Instana and its use cases. You will gain insights into Telemetry and explain its importance and benefits. You will discover the working of telemetry and the steps to implement it in application development. You will also differentiate between distributed tracing and telemetry while learning about popular telemetry and distributed tracing tools. You will explore why tracing for container applications is required and the best practices for implementing tracing in application development.
  • Final Project and Assessment
    • In this module, you’ll complete two practice projects where you'll be able to apply monitoring and observability skills using applicable tools. In the first part, you will create and set up an Instana account to explore the credentials for application and infrastructure monitoring. You will also get the opportunity to create an Instana dashboard and a website and save their credentials for future use. In the next part, you will explore Instana to monitor an application named Robotshop using Docker. You will delve into the process of connecting the Robotshop application with Instana for efficient monitoring and analysis. Using Docker commands in the terminal, you will establish a seamless connection between the Instana dashboard and the Robotshop application. This hands-on practice project will equip you with the knowledge and skills to monitor your application's performance effectively and make data-driven decisions to optimize its efficiency.

Taught by

John Rofrano and Ramanujam Srinivasan


4.6 rating at Coursera based on 36 ratings

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