learning path

Implementing Observability - Level 1

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Observability is an important SRE concept in the field of IT operations. It refers to the ability to monitor and understand the behavior and performance of complex systems and services in real time. This is essential for ensuring the availability and reliability of these systems, and for identifying and addressing issues that arise.

In this learning objective, we will explore the concept of observability in more detail, and discuss the steps involved in implementing observability in a real-world system. We will begin by looking at the different components and systems that need to be monitored, and how to identify the most important ones. We will then discuss how to configure and establish monitoring policies, and how to set up and configure robust real-time alerting systems.

By the end of this learning objective, you will have a solid understanding of the concept of observability, and you will be able to implement observability in your own systems and services. You will be able to identify the systems and components that need to be monitored, configure and establish monitoring policies, and set up and configure robust real-time alerting systems.

The content in this learning path will teach you Implementing Observability to a level 1 standard. 

Learning Objectives

  • Be able to identify systems and components which need to be monitored
  • Be able to configure and establish monitoring policies
  • Be able to set up and configure robust real time alerting systems
  • Understand and implement the concept of Observability
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About the Author
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Jeremy Cook
Content Lead Architect
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Jeremy is a Content Lead Architect and DevOps SME here at Cloud Academy where he specializes in developing DevOps technical training documentation.

He has a strong background in software engineering, and has been coding with various languages, frameworks, and systems for the past 25+ years. In recent times, Jeremy has been focused on DevOps, Cloud (AWS, Azure, GCP), Security, Kubernetes, and Machine Learning.

Jeremy holds professional certifications for AWS, Azure, GCP, Terraform, Kubernetes (CKA, CKAD, CKS).

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