• Explore the concept of DevOps, including DevOps practices and
• principles that can help eliminate the problems of traditional
• software development approaches. Examine different approaches for
• embracing the DevOps mindset, key elements of the DevOps mindset,
• and the roles of design thinking, Lean, and Agile in enabling and
• facilitating the DevOps mindset in the enterprises. In addition,
• discover the role of the cloud in realizing the benefits of DevOps,
• the criteria for selecting on-premise, cloud, hybrid or multi-cloud
• architectures, and how to enable code collaboration and
• configuration management.

• Explore the common application management roadblocks and the

• solutions provided by adopting DevOps practices and principles.
• Examine the concept of Disciplined DevOps and its workflow,
• critical change management elements for achieving better outcomes
• with the right cultural shift, prominent deployment strategies, and
• tools and platforms that are used to set up DevOps deployment
• environments. Discover how to use DevOps to bring people, process
• and technology together for digital transformation and how to set
• up deployment environments and release management solutions using
• Atlassian tools and cloud containers.

• Explore Kanban strategies for meeting project timelines, core

• practices used in Kanban, terms and goals that are critical for
• successful rollout of Kanban for operations, and key elements of
• Kanban for project management. Discover how to track and forecast
• projects using Kanban and how Waterfall teams can transition to
• Kanban. Examine project management tools that can be used to
• implement Kanban and key Kanban board metrics for tracking and
• measuring project progress. In addition, how to create Kanban
• projects, create and configure Kanban boards to monitor and manage
• projects and DevOps practices, and set WIP limits are also
• covered.

• Explore the objectives of Agile, core principles of the Agile

• Manifesto, the similarities and differences between Agile and
• DevOps, and the combined benefits provided by DevOps and Agile.
• Examine the types of reports that can help track Work in Progress,
• the process of visual requirements gathering for Agile project
• management, and key performance indicators and metrics for
• evaluating the progress of Agile development projects. Discover how
• to create Scrum boards, manage Backlogs and Sprints, and set up and
• implement Agile product development projects and practices using
• Jira, Azure DevOps, and TFS.

• Explore the concepts of continuous delivery and continuous

• integration, key principles and tools for implementing them, and
• the differences between continuous integration, continuous
• delivery, and continuous deployment. Examine the Continuous
• Delivery Maturity Model, the use of Application Release Automation,
• and the criteria for selecting the right code repository solutions.
• Discover how to set up continuous delivery architectures, use
• Bitbucket to set up repositories, configure pipelines for
• continuous delivery, implement continuous integration workflows and
• continuous deployment pipelines, build continuous delivery
• workflows with Atlassian tools, and use GitLab as a complete DevOps
• platform.

• Explore the benefits of using AWS for implementing CloudOps, AWS

• services that can be used for end-to-end CloudOps lifecycle
• implementation, implementation approaches for continuous
• integration and continuous delivery in AWS, and deployment targets
• in AWS. Discover how to work with AWS CodePipeline, AWS CodeCommit,
• AWS CodeStar, and AWS X-Ray to implement continuous integration,
• manage code repositories, and build, deploy and manage
• applications.

• Explore the features of prominent Azure DevOps and CloudOps

• tools that can be used for software development, the mindset shift
• to DevSecOps, and how to transform monolithic solutions to cloud
• solutions. Discover how to install and configure Azure Boards for
• GitHub, create local Git repositories, and synchronize repositories
• with centralized Git repositories in Azure DevOps. Examine how to
• use Azure Boards to manage software projects, configure CI/CD for
• applications in Azure Pipelines, work with Azure Artifacts to
• publish various packages in Azure DevOps, monitor application
• performance using Application Insights, and use Azure DevOps to
• manage the software development project testing lifecycle.

• Explore the features, benefits, and solutions of Google Cloud

• Platform for end-to-end CloudOps implementation. Examine the Cloud
• Build features for continuous integration, GCP configuration
• management tools, the GCP reference pipeline for continuous
• integration, and the benefits of using GCP for continuous delivery.
• Discover how to work GCP tools like Cloud Build, Cloud Source
• Repository, and Google Kubernetes Engine to create and manage
• Source Code Repository, as well as how to build configuration
• management workflows, automate continuous integration workflows for
• serverless applications, automate App Engine deployments, and
• create continuous delivery pipelines.

• Examine the deficiencies associated with manual resource

• configuration and how Infrastructure as Code (IaC) can eliminate
• those deficiencies. Explore the benefits and best practices for
• implementing Infrastructure as Code, the prominent tools and
• services that can be used to implement Infrastructure as Code, and
• the concept and benefits of Policy as Code. Discover Continuous
• Configuration Automation and tools used to implement it, Chef
• features, components and tools for implementing Continuous
• Configuration Automation, how to install Chef and write cookbooks,
• and also how to implement Infrastructure as Code using
• CloudFormation.

Final Exam: DevOps Engineer will test your knowledge and application of the topics presented throughout the DevOps Engineer track of the Skillsoft Aspire DevOps Engineer to CloudOps Architect Journey.

• Explore potential applications that can be automated, along with

• the advantages, disadvantages, and best practices of automation.
• Examine approaches for developing enterprise automation
• capabilities, key processes for an effective IT automation
• strategy, and benefits of deployment automation. Discover
• approaches for implementing deployment automation, benefits of
• cloud automation, and the common cloud tasks that can be automated.
• Automating DevOps processes, the role of automation in DevOps,
• tools used to automate DevOps practices, the roles and
• responsibilities of a DevOps Automation Architect, how to install
• and configure SaltStack, and how to automate static site deployment
• with AWS CloudFormation are also covered.

• Discover how to implement and improve DevOps practices, tools
• that can be used across various development and operations
• processes, and how to set up DevOps architecture to improve the
• delivery of value. Explore essential DevOps and CloudOps design
• patterns used to enable DevOps and CloudOps in the enterprise, how
• to implement continuous deployment, and how to scale applications
• using cloud services. Examine the DevOps Operational Model,
• essential cloud design patterns that can be applied when building
• cloud-based applications to achieve continuous operations in public
• and private clouds, and critical patterns for implementing
• automation in DevOps and CloudOps workflows. How to build scalable
• architecture in AWS and how to design applications by applying the
• Runtime Reconfiguration pattern is also covered.

• In this course, you'll explore automation approaches, how to

• using AWS to implement DevOps and CloudOps in the enterprise,
• critical automation patterns for implementing AWS DevOps and
• CloudOps, effective approaches for automating IT processes using
• the AWS DevOps Reference Architecture, and the DevOps
• Transformation Assessment and Strategy. Additionally, you'll learn
• about the role of essential AWS Serverless Architecture patterns in
• automating IT processes and prominent containerization services
• provided by AWS for CI/CD. You'll examine how to use and work with
• serverless architecture, AWS Lambda, AWS OpsWorks, AWS Systems
• Manager, and AWS Config to automate CI/CD pipelines. Finally,
• you'll discover how to implement configuration management, manage
• EC2 Systems, enforce compliance for infrastructures, and deploy
• code into containers running on ECS.

• In this course, you'll examine essential features of AWS

• services like AWS CodePipeline, AWS CodeDeploy, and AWS CodeStar.
• You'll learn about Infrastructure as Code and some of the most
• prominent non-AWS tools for automating AWS DevOps and CloudOps
• tasks. You'll discover how to work with AWS CodePipeline, AWS
• CodeDeploy, AWS CloudFormation, AWS CodeStar, AWS CloudWatch, and
• AWS GuardDuty to create automated software release pipelines,
• invoke AWS Lambda functions, automate application deployment,
• implement Infrastructure as Code, manage applications, automate
• continuous monitoring of resource usage, and implement continuous
• security monitoring.

In this course, you will learn about the DevOps workflow and Azure-specific patterns for automating DevOps workflows, as well as prominent Azure tools and technologies that can be used to implement DevOps and CloudOps practices. You'll learn about the different types of version control provided by Azure Repos, along with the key elements and artifacts used in Azure Repos to manage version control and workflows. You'll examine how to create and synchronize local Git repositories with centralized Git repositories in Azure DevOps, use Azure DevOps to create and manage branches, and manage technical debts. Finally, you'll discover how to create Azure CI/CD pipelines, use Azure Pipelines to implement CI/CD for Node.js applications, and automate and execute test cases for web applications.

In this course, you'll learn how to plan, track, and monitor Sprints with Azure Boards, as well as examine prominent features of Azure Artifacts and best practices for managing and sharing packages. You'll also learn about the configuration management and monitoring capabilities of Azure DevOps and how to use Azure Pipelines to set up continuous deployment for containerized applications to Azure Kubernetes Service. Next, you'll discover how to create various test artifacts, use Azure DevOps to discover, install, and publish NuGet, NPM, and Maven packages, and configure Ansible instances on VMs using Ansible Solution Template. Finally, you'll learn how to use Ansible to configure Azure Kubernetes Service clusters in Azure, create resource groups, create AKS clusters within resource groups, and use Azure Blueprint to create, deploy, and update compliant environments.

• Explore the features of Google Cloud Platform, Google Kubernetes

• Engine, best practices for operating containers, and how to build
• cloud-native applications using the CloudOps methodology. Examine
• how Google Cloud Source Repository compares to GitHub and how the
• automated deployment capabilities of Google Cloud Deployment
• Manager compare with Terraform. Delve into the machine learning,
• artificial intelligence, and analytical capabilities of Google
• Cloud Platform, along with the essential design patterns for
• connecting Google Cloud Platform with other cloud platforms.
• Discover how to create and configure Google Kubernetes Engine
• clusters, deploy applications across multiple Kubernetes clusters,
• create repositories and manage code with Google Cloud Source
• Repository, and deploy applications from Cloud Source Repository to
• App Engine. How to automate the configuration of Google Cloud
• Platform resources and application deployment with Google Cloud
• Deployment Manager, create virtual machine instances on Google
• Cloud Platform, build applications with Terraform, configure AutoML
• and BigQuery to manage large volume of data and build ML models,
• set up fully-managed real-time messaging environments, and transfer
• data between Google Cloud Platform and other Cloud service
• providers are also covered.

• In this course, you'll explore the concept of multi-cloud, the

• benefits of adopting the multi-cloud strategy, and the multi-cloud
• architecture design for application and cloud environment
• management. You'll discover the challenges of hybrid and
• multi-cloud deployments, how to use the right hybrid and
• multi-cloud architecture patterns, the common network topologies
• for hybrid and multi-cloud setup, the critical challenges
• associated with multi-cloud environments, and the frameworks for
• eliminating these challenges. In addition, you'll learn about
• CloudOps characteristics that are applied to build cloud management
• platforms, the tools provided by AWS, Azure, and GCP to implement
• multi-cloud environments, the critical patterns for building
• cloud-specific automations in DevOps pipelines, and with how to
• create multi-cloud environments with Azure and AWS.

• In this course, you'll learn about the DevOps tools that can be

• used for cross-cloud multi-cloud deployments, how to implement
• CI/CD DevOps pipelines that employ multiple cloud environments,
• prominent tools that can be used to monitor metrics across
• multi-cloud platforms and environments, challenges associated with
• multi-cloud disaster recovery configuration, and the patterns that
• can be used to eliminate those challenges. You'll also discover how
• to integrate Azure AD with multiple AWS accounts, set up and
• configure CloudOps CI/CD process using Spinnaker, install and
• configure Jenkins to provision multi-cloud environments and deploy
• code, connect GCP with AWS using VPNs, monitor multi-cloud
• architecture with New Relic, and set up cloud disaster recovery
• using GCP and AWS.

Final Exam: DevOps Automation Architect will test your knowledge and application of the topics presented throughout the DevOps Automation Architect track of the Skillsoft Aspire DevOps Engineer to CloudOps Architect Journey.

• Explore the differences between DevOps and CloudOps, the

• challenges and best practices associated with the implementation of
• CloudOps, and the cloud capabilities that we needs to integrate in
• existing DevOps implementations to transform DevOps to CloudOps.
• Discover the prominent multi-cloud management tools that we can use
• to implement CloudOps, how to select the right multi-cloud
• management tool, the differences between Hybrid cloud and
• multi-cloud along with the architectural designs that can lead to
• effective multi-cloud strategy.
  
• We will also discuss how to implement and optimize multi-cloud
• strategy in the enterprise, the CloudOps design scenarios for
• managing critical architectural and operational requirement of
• multi-cloud strategy, how to build DevOps pipelines for multi-cloud
• application deployment, how to eliminate operational challenges of
• multi-cloud using the Cloud Service Brokerage platform and mitigate
• the challenges of designing CloudOps solution for multi-cloud.

• "Explore the concept of IaaS, the architecture of IaaS, the key

• benefits of IaaS with CloudOps; compare IaaS with SaaS, PaaS, and
• Bare Metal as a Service; the core components of IaaS platform and
• architecture, when to adopt declarative and imperative IaaS, the
• prominent IaaS providers, the role of orchestration in implementing
• CloudOps for heterogeneous deployments, the benefits of cloud
• orchestration along with the categories of cloud automation and
• orchestration tools.
  
• We will also discuss the multi-cloud strategies and tools for
• planning and architecting IaaS, the benefits of running containers
• in multi-cloud environments, the prominent APIs and tools that we
• can use to run containers in multi-cloud environments, the role of
• Kubernetes in container management for multi-cloud, the impact of
• containerization on multi-cloud and edge computing, learn to
• install and configure OpenStack and OpenNebula on Ubuntu LTS to
• create multi-cloud models."

• In this course, you'll explore the categories of cloud computing

• portability and interoperability, the interfaces of the Distributed
• Computing Reference Model, the standardization required for cloud
• computing portability and interoperability, and the application
• design principles that can provide better interoperability. You'll
• learn about the taxonomy of the Cloud Ecosystem Reference Model for
• designing interoperable cloud architectures, the Enterprise
• Architecture Principles of the cloud ecosystem that can help
• maintain consistency and integrity of enterprise architectures, and
• the prominent cloud deployment models and when to adopt which
• model. You'll also examine the benefits of achieving cloud
• interoperability and maximizing portability, the challenges of
• achieving interoperability between diversified cloud components,
• the key elements of Interoperability and portability for cloud
• services, what to consider when defining hybrid cloud strategy, the
• process-oriented classification of cloud migration, and features
• exhibited by public, private and hybrid cloud.

• In this course, you'll explore scenarios of adopting private and

• public cloud for application deployment, comparisons of prominent
• cloud offerings and cloud-based integration tools for deploying and
• managing varied cloud environments and increasing IT framework
• complexity, the prominent types of cloud integration, and the
• benefits of using Integration Platform as a Service. You'll learn
• about the features of the prominent types of inter-cloud
• implementations, the recommended architectural patterns for
• planning multi-cloud migration and deployments, and the multi-cloud
• implementation workflow for designing automated and portable
• architectures. You'll also discover how to install, configure, and
• set up CloudHub and Talend to build portable multi-cloud
• integration workflows and deploy applications. Finally, you'll
• examine how to work with Aviatrix to integrate AWS with Azure
• Active Directory and integrate Azure with AWS and GCP.

• In this course, learners will examine the architecture of Docker

• along with features afforded by Docker to enable and manage
• multicloud containers, environments, and services. The 12-video
• course opens with an overview of Docker and the prominent
• open-source tools that can be used by architects for productive
• container implementations. You will learn about the role of Docker
• Container Management in implementing multicloud containerization
• and the critical Docker services that you need to manage while
• setting up multicloud containerization. Along the way, explore the
• features of Docker Cloud and Docker Hub along with the benefits of
• combining Docker and multicloud computer technologies. You will
• also learn how to link multiple containers, the steps involved in
• integrating Docker Cloud with AWS (Amazon Web Services), and how to
• set up nodes on Docker Cloud and deploy services on the nodes. You
• will conclude the course by learning how to create multicloud
• clusters by using Docker Swarm, Docker Machine, and popular cloud
• platforms.

• Explore the federated application management process, the

• benefits of adopting the federated application pattern, the
• components, and features provided by Docker Enterprise. Compare the
• capabilities of Docker and Kubernetes and understand the objective
• of Cloud Native Computing Foundation.
  
• We will also learn to set up overlay network driver to create
• distributed networks among multiple Docker daemon hosts, connect
• Docker local client with remote AWS Docker, implement Multi-host
• Overlay Networking using Etcd, create AWS and Azure clusters using
• Containership.io and set up federated application management with
• Docker Enterprise and Amazon EKS.

• Explore prominent tools that can be used to manage the

• deployment and life cycle of Kubernetes. In this 15-video course,
• learn about essential patterns used with Kubernetes to create
• production level and heterogeneous deployments, as well as how to
• reduce complexity and risks of multicloud strategy with Kubernetes.
• Key concepts covered here include the architecture and components
• of Kubernetes and different types of pods to host
• vertically-integrated applications; comparing features of
• Kubernetes and Docker and the solution architectures that can be
• built; and essential Kubernetes deployment patterns that can be
• used to deploy application stacks with the Declarative deployment
• method. Other issues include Fixed and Recreate deployment
• strategies using Kubernetes; Zero Downtime and No Concurrent
• Versions deployment, applying the Blue/Green deployment strategy
• using Kubernetes; and implement Canary testing with Kubernetes
• Deployments and Services. You will examine Kubernetes Cluster
• Federation, and how to install and configure multicloud single node
• Kubernetes clusters on Ubuntu; install and configure multicloud
• Kubernetes to manage multicloud orchestration; and Extension and
• Operator patterns used in Kubernetes to improve Kubernetes cluster
• management capabilities.

• In this course, you'll explore the essential components of

• OpenStack that are used for accessing infrastructure resources.
• You'll examine topologies of multi-cloud orchestration involving
• Azure, AWS and OpenStack, as well as the differences between
• OpenStack and Kubernetes. Next, you'll look at the benefits of
• using OpenStack and Kubernetes together, the tools that can be used
• to manage OpenStack deployments, and the critical roles of
• OpenStack shared services. You'll move on to explore prominent
• features provided by Heat, the different approaches of deploying
• OpenStack, and how to get started with the most commonly used
• OpenStack services. Finally, you'll learn to install OpenStack,
• create and launch virtual machine instances, and install and
• configure storage nodes and Heat on OpenStack nodes.

• In this course, you'll explore the enterprise and operational

• factors and SLA considerations that can impact the design of
• OpenStack cloud. You'll examine open source projects that can be
• used to implement OpenStack container integration points, prominent
• containers and Platform as a Service tools that can be deployed on
• OpenStack Cloud, and the objectives of Magnum. Next, you'll learn
• about the challenges and associated solutions for implementing
• OpenStack multi-cloud, how to launch OpenStack instances using
• Docker Machine, and how to install and configure Docker on
• OpenStack instances. Finally, you'll discover how to run Kubernetes
• clusters in the OpenStack ecosystem to deploy application servers,
• install and configure Jenkins Automation Server, and install
• OpenStack-Ansible in test environments using general workflows.

• Securing multi-cloud deployments and CloudOps platforms involves

• managing the security and privacy of your cloud services. In this
• course, you'll explore the key principles and strategies for
• securing the enterprise cloud, recommended practices and models for
• perimeter security, and how to choose appropriate security
• mechanisms. You'll examine the configurable options for security
• mechanisms on both service and client side, the prominent intrusion
• detection techniques for managing cloud computing and security
• challenges, and prominent cloud audit methods. Next, you'll learn
• approaches for overcoming the impacts of security challenges in
• multi-cloud environments, best practices for improving the security
• of multi-cloud deployments, and how to secure CloudOps platforms to
• build secure pipelines, middleware, and infrastructure for
• multi-cloud applications. Finally, you'll explore issues a cloud
• architect should consider when designing cloud solutions and cloud
• service consumers should evaluate and manage the security and
• privacy of cloud services.

• Azure, AWS, and Google Cloud Platform provide various security

• services to secure access, applications, data, infrastructures, and
• deployments in the cloud. In this course, you'll explore the
• security services provided by AWS Cloud Security for securing
• workloads and applications, as well as the Azure security products
• that can be used to protect data, applications, and
• infrastructures. You'll explore the Google Security Model, the
• security services provided by Google, why you need to secure
• containers, and recommended cloud container security best practices
• for securing container usage in the cloud. You'll move on to learn
• about how configure AWS Security Hub, create and configure
• symmetric and asymmetric keys using AWS KMS, and implement Azure
• Active Directory and Seamless Single Sign-On. Finally, you'll
• examine how to set up VPN between a Check Point Security Gateway
• and Cloud VPN on Google Cloud Platform, harden security and
• restrict network access to the control plane and nodes of Google
• Kubernetes Engine, and how to encrypt Kubernetes secrets at the
• application layer.

• Implementing the right software-defined wide area network

• (SD-WAN) framework for the organization can help improve network
• management, decrease hardware costs, increase efficiency, and even
• enhance security. In this course, you'll explore the differences
• between traditional, software-defined networking, and a
• software-defined wide area network (SD-WAN). You'll learn about the
• advantages, working mechanisms, solution architecture, and primary
• components of SD-WAN. Next, you'll examine the topologies and
• deployment models that can be used to design SD-WAN overlays, along
• with prominent tools and applications that can be used to build,
• deploy, and maintain SD-WAN. You'll learn how to apply CloudOps in
• networks to simplify configuring, managing, and delivering the
• SD-WAN. You'll examine security challenges and best practices for
• secure deployment of SD-WAN and prominent Cisco SD-WAN
• architectures that can be implemented in AWS. You'll see approaches
• that can be used in an SD-WAN to transform complex legacy networks
• into easy-to-manage and scalable networks. Finally, you'll learn to
• configure AWS Transit Gateway, AWS-provided Cisco Cloud Services
• Router 1000V - BYOL, and VMware SD-WAN.

Final Exam: CloudOps Engineer will test your knowledge and application of the topics presented throughout the CloudOps Engineer track of the Skillsoft Aspire DevOps Engineer to CloudOps Architect Journey.

• In this course, you'll explore the critical roles and

• responsibilities of a Cloud Architect, the differences between the
• roles played by Solution Architects and Cloud Architects, and the
• cloud challenges that a Cloud Architect needs to manage. You'll
• learn about the planning solutions Cloud Architects use to automate
• and orchestrate multi-cloud applications, along with the Cloud
• Computing Reference Model and Cloud Governance Lifecycle, which are
• used for building cloud frameworks. Next, you'll look at tools and
• frameworks that can be used to assess cloud operations and identify
• the current capabilities of multi-cloud environments, as well as
• success factors that need to be considered as benchmarks for
• identifying business values of cloud architectures. Finally, you'll
• learn about using the Target Operating Model to deliver value
• through appropriate cloud strategies and using the Multi-cloud
• Maturity Model and transformation workflows for building solutions
• for cloud delivery mechanisms.

• In this course, you'll explore the role of a cloud architect in

• transitioning from DevOps to CloudOps. You'll examine the role of a
• Cloud Operating Model in defining operational processes, as well as
• the role of the people, organization and operations domain in
• determining the CloudOps transition process. Next, you'll look at
• the best practices for transforming enterprise capabilities, the
• benefits of multi-cloud transition, and the approaches of managing
• data and information to implement the right cloud transition
• mechanism. You'll move on to learn about prominent cloud transition
• strategies for building CloudOps transition roadmaps. You'll
• explore the systemic principles for planning multi-cloud
• transitions, tools for planning and deploying CloudOps solutions,
• and the processes, SLAs, and KPIs associated with running cloud
• operations that can be used to create operational baseline
• capabilities. Finally, you'll explore how to facilitate a smooth
• process, data, and platform transition in multi-cloud environments
• and the transition path for identifying and applying the right
• CloudOps Maturity Model.

• In this course, you'll learn about the essential components

• involved in solutioning CloudOps projects, the layered approach of
• managing enterprise CloudOps applications, and the role-based and
• layer-based CloudOps solutioning architectures. You'll examine the
• role of different types of cloud engineers in providing logical and
• physical architectures for the CloudOps solutioning process. You'll
• also learn about the role of the Cloud Governance Framework in
• providing comprehensive cloud-centric governance for each phase of
• the cloud transformation life cycle used in CloudOps. Next, you'll
• explore the RACI Matrix of Roles for each CloudOps solutioning
• stakeholder, the Measures and Metrics involved in solutioning
• CloudOps strategy, and the anatomy of Cloud Service Agreements.
• Finally, you'll learn about the logical CloudOps architecture and
• prominent CloudOps solutioning tools for designing, planning,
• architecting, and implementing CloudOps solutioning.

• In this course, you'll explore the concept of AI Explainability,

• the role of CloudOps Explainability in managing multi-cloud
• solutions, how to evaluate explanatory systems, and the properties
• used to define systems to accommodate explainability approaches.
• You'll look at how users interact with explainable systems and the
• effect of explainability on the robustness, security, and privacy
• aspects of predictive systems. Next, you'll learn about the use of
• qualitative and quantitative validation approaches and the
• explainability techniques for defining operational and functional
• derivatives of cloud operation. You'll examine how to apply
• explainability throughout the process of operating cloud
• environments and infrastructures, the methodologies involved in the
• three stages of AI Explainability in deriving the right CloudOps
• model for implementation guidance, and the role of explainability
• in defining AI-assisted Cloud Managed Services. Finally, you'll
• learn about the architectures that can be derived using Explainable
• Models, the role of Explainable AI reasoning paths in building
• trustable CloudOps workflows, and the need for management and
• governance of AI frameworks in CloudOps architectures.

• The impact of future trends allow you to recognize how to build

• cloud-based applications and architectures that can adopt and adapt
• to emerging trends, technologies, and processes. In this course,
• you'll explore future trends in cloud computing and emerging
• technologies that can help with analyzing their impact on existing
• cloud operations and practices. You'll learn about solutioning
• strategies and resource types that can help with adopting emerging
• technologies and trending features in existing CloudOps
• architectures. Next, you'll examine cloud application design
• considerations and the inside-out and outside-in development
• strategies that can help with adopting and adapting to any
• futuristic upgrades. You'll learn about how to handle states at the
• service level, system architecture design considerations, and the
• use of Adapter pattern to build architectures that adopt and adapt
• to futuristic innovations. You'll examine the Minimum Valuable
• Increment design approach, the Manifesto for Future Generation
• Cloud Computing, and the manifesto areas that are relevant for
• aligning with the future research directions.

Final Exam: CloudOps Architect will test your knowledge and application of the topics presented throughout the CloudOps Architect track of the Skillsoft Aspire DevOps Engineer to CloudOps Architect Journey.