SkillSoft Explore Course – Lambers, Inc.

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IT Professional Curricula Internet and Network Technologies Solution Area Cloud Computing CloudOps Explainability

CloudOps architects need to explain how their often complex, multi-cloud deployment solutions work to a wide variety of audiences - not an easy feat, but one you'll learn to overcome in this course.

You'll start by defining the concept of interpretability and explainability in CloudOps. You'll then outline how to build explainability into a CloudOps workflow, investigating the core explainability principles and benefits along the way.

You'll examine the explainability decision tree used to derive a value stream from an existing CloudOps implementation, the algorithms used to explain CloudOps practices, and the governance strategy for deploying explainable cloud applications in multi-cloud environments.

You'll examine the challenges and opportunities of explainable AI in CloudOps and identify the key applied intelligence features to derive AIOps solutions. You'll end this course by creating a basic explainability workflow using New Relic.

Asset ID	it_dpcoexdj_01_enus
Course Type	Video Course
Course Category	Internet and Network Technologies Solution Area

Objectives
Explainability for Cloud Deployments: Applying Explainability in CloudOps discover the key concepts covered in this course define the concept of interpretability and explainability and outline how these can be applied to CloudOps list the stages of the design thinking process involved in developing an empathic approach to crafting explainability for varying CloudOps users and stakeholders outline the reasons and methods for building explainability into a CloudOps workflow, with a focus on eliminating the negative impact of IT state the challenges and opportunities of explainable AI and describe its impact on DevOps principles integrated in CloudOps describe the explainability decision tree that can be used to derive the value stream of an existing CloudOps implementation describe the fundamental principles of explainability along with the categories of explanations that help build a CloudOps practice recall the different algorithms that can be used to explain CloudOps practices adopted in the enterprise recognize the benefits of using explainability and specify how it helps configure and implement continuous monitoring and feedback mechanisms recall the role of explainability in achieving continuous ops in public, private, and multi-cloud environments describe the governance strategy that needs to be considered when configuring and deploying explainable cloud applications in multi-cloud environments recognize the features of applied intelligence that help derive an AIOps solution for DevOps, site reliability engineers, and on-call teams to manage CloudOps implementation create a basic explainability workflow using New Relic by creating policies with their associated conditions summarize the key concepts covered in this course

Objectives

Explainability for Cloud Deployments: Applying Explainability in CloudOps

discover the key concepts covered in this course
define the concept of interpretability and explainability and outline how these can be applied to CloudOps
list the stages of the design thinking process involved in developing an empathic approach to crafting explainability for varying CloudOps users and stakeholders
outline the reasons and methods for building explainability into a CloudOps workflow, with a focus on eliminating the negative impact of IT
state the challenges and opportunities of explainable AI and describe its impact on DevOps principles integrated in CloudOps
describe the explainability decision tree that can be used to derive the value stream of an existing CloudOps implementation
describe the fundamental principles of explainability along with the categories of explanations that help build a CloudOps practice
recall the different algorithms that can be used to explain CloudOps practices adopted in the enterprise
recognize the benefits of using explainability and specify how it helps configure and implement continuous monitoring and feedback mechanisms
recall the role of explainability in achieving continuous ops in public, private, and multi-cloud environments
describe the governance strategy that needs to be considered when configuring and deploying explainable cloud applications in multi-cloud environments
recognize the features of applied intelligence that help derive an AIOps solution for DevOps, site reliability engineers, and on-call teams to manage CloudOps implementation
create a basic explainability workflow using New Relic by creating policies with their associated conditions
summarize the key concepts covered in this course