The principles and practices of DevOps help enterprises innovate with greater efficiency and agility. In this course, you'll explore these practices, identify the problems they eliminate, and recognize their application in DevOps environments and solutions. You'll also list the DevOps methods and toolchains to improve product development and release and outline how to achieve DevOps transformation to leverage continuous integration and continuous delivery. You'll list the DevOps and Cloud principles that help achieve continuous operations in public, private, and hybrid clouds and the steps involved in building cloud-ready application architectures. You'll identify the IT operational principles for moving to an automated self-service CloudOps model, define the concept of DevOps as a Service, outline the steps involved in modernizing applications, and recognize some DevOps documentation challenges.

To successfully implement DevOps, you need to devise strategies that combine DevOps principles and practices. In this course, you'll explore how to implement robust DevOps practices throughout the deployment process. You'll examine the different types of release management processes, outline automation approaches, and identify methods for solutioning complex applications. You'll recognize how to incorporate DevOps practices with traditional ones, the role of Agile and Lean principles in the DevOps lifecycle, prominent tools for automating DevOps software development, and how to set up Agile delivery practices using Atlassian tools. You'll then set up open source tools to enable continuous application delivery and use Cloud tools to establish continuous integration and deployment and monitor the implementation success of DevOps practices.

Hybrid cloud solutions offer many benefits to growing enterprises. As a CloudOps engineer, you will likely face the challenge of successfully deploying a hybrid cloud solution. In this course, you'll explore the core components of a hybrid cloud solution, the business challenges driving their adoption, and how to develop roadmaps to achieve them. You'll identify the main pillars of hybrid cloud applications and the differences between hybrid, on-premises, and single cloud deployment solutions. You'll also examine considerations when deploying middleware using hybrid cloud solutions. Next, you'll outline a hybrid cloud migration strategy and the hybrid integration reference architecture. You'll name the cloud vendors providing end-to-end or elements of hybrid cloud solutions. Lastly, you'll compare the capabilities of the hybrid cloud solutions offered by AWS, Azure, Intel, and IBM.

When managing a hybrid cloud environment, applying DevOps principles can aid with deployment complexity, legacy app modernization, and Agile and CI/CD process implementation. In this course, you'll learn how to enable DevOps in a hybrid cloud environment, recognizing the associated challenges, the role of containerization and DevOps deployment strategies, and the implementation process of CI/CD. You'll then examine the challenges, best practices, and tools for monitoring hybrid clouds. You'll also recognize the workload combination used to build hybrid architectures, the tools used to design conceptual architecture and set up CI/CD mechanisms, and the benefits of hybrid CI/CD. You'll set up and configure hybrid cloud connectivity between AWS and on-premises environments, CI/CD processes for hybrid environments using Jenkins with Docker, and monitoring tools to monitor solutions deployed in hybrid environments.

Aspiring cloud engineers need to move beyond working with single platform deployments, such as on-prem and cloud, to more complicated scenarios, such as hybrid and multi-cloud deployments. In this course, you'll explore the benefits of multi-cloud and hybrid cloud, common scenarios involving hybrid and multi-cloud deployment, and the multi-cloud DevOps framework for managing multi-cloud distributed environments. You'll examine best practices for achieving multi-platform deployment and the driving hybrid and multi-cloud design principles to set up multi-cloud environments. You'll also outline hybrid and multi-cloud deployment and architectural patterns, network topologies used to set up hybrid and multi-cloud environments, and approaches to adopting multi-cloud management. Lastly, you'll identify a multi-cloud operating model and outline techniques to transition to cloud and multi-cloud environments and troubleshoot application distribution issues in multi-cloud environments.

Aspiring cloud engineers need to know how to select and use hybrid and multi-cloud deployment management services. In this course, you'll explore the AWS services for implementing hybrid and multi-cloud solutions and other multi-cloud environment application deployment tools. You'll configure AWS Outpost to run AWS services on-premises, Azure Arc to build hybrid deployment environments, and AWS, Azure, and GCP to connect with other public cloud platforms. You'll use AWS and Azure to set up dual or multi-cloud deployment environments. You'll examine how to back up multi-cloud environments and overcome disaster recovery challenges. Next, you'll configure Aviatrix networking software for an AWS multi-cloud network and LiveData for multi-cloud environment backup. Lastly, you'll use Terraform with VPNs to create secure, private, site-to-site connections between Google Cloud Platform and AWS.

An aspiring cloud engineer needs to learn how to build upon DevOps architecture design fundamentals to formulate robust and sound container clustering strategies. In this course, you'll recall the concept of clustering and outline the different cluster architectures for failover and load balancing support. You'll outline what comprises a clustering topology, physical and virtual clusters, and enterprise application cluster management. You'll then name clustered environment resource managers, application containerization types, and containerized cluster implementation solutions. Next, you'll examine data center cluster virtualization and investigate hybrid cloud cluster architectures for multi and hybrid cloud solution delivery. You'll explore clustering in Docker, Kubernetes, and Docker Swarm. Lastly, you'll set up single control-plane Kubernetes clusters, Docker Swarm clusters for high availability, and high-performance compute node clusters in Amazon EC2.

Container orchestration is an essential DevOps practice for managing containers in diversified environments. It provides portability and scalability by orchestrating containerized application management in multi-cloud environments. In this course, you'll start by examining cloud application-level orchestration, the orchestration layer, and the container orchestration tools for virtual machine and container allocation. You'll then outline the architectures used in multi-cloud and multi-cluster environments and cloud orchestration reference systems used for TOSCA-complaint container cluster federation. Next, you'll explore orchestration in managing multi-cloud environments and container orchestration in implementing CI/CD pipelines. You'll implement a pool of Docker hosts into a single virtual server and set up container clusters using Amazon Elastic Container Service and Fargate. Lastly, you'll deploy Azure Kubernetes Service clusters, use Kubernetes Cluster Autoscaler, and create multi-cloud Docker clusters with Docker Swarm.

An obvious goal of any cloud engineer is to ensure as little loss of service and downtime as possible. In this course, you'll explore the concept of high availability and outline the most common IT considerations, necessary components, architectures, and recommended strategies for implementing high availability. You'll examine the different types of outages addressed using high-availability solutions and the implementation approaches for primary and secondary distribution servers in high-availability environments. You'll then classify the benefits and pitfalls of implementing high-availability deployments and compare traditional and virtualized high-availability and failover solutions. Furthermore, you'll investigate the system availability metrics, key cloud architecture patterns, and critical cloud service management guidelines for designing and architecting high-availability solutions. Lastly, you'll differentiate between traditional and cloud high-availability solutions and define the process of migrating from traditional to cloud high-availability deployments.

How high availability (HA) is implemented, managed, and deployed often comes down to how applications use HA in their given environments - traditional or cloud. In this course, you'll learn how to implement HA in the cloud. You'll start by examining three-layer classification and the role of availability frameworks in implementing high-availability cloud solutions. You'll then explore the design process for developing a highly available cloud, the concept of elasticity and scalability, and the HA services provided by various cloud providers. Next, you'll configure a template that defines EC2 instances and use it to create an EC2 Auto Scaling group. You'll use AWS CodePipeline to deploy applications to multiple high-availability environment regions and Azure to create highly available virtual machines. Lastly, you'll configure an instance for high availability in GCP.

When multi-cloud or hybrid deployment scenarios are at play in distributed environments, technical support engineers need to switch from a data center to a CloudOps mindset. In this course, you'll investigate several deployment strategies for setting up multi-cloud or hybrid infrastructures. You'll examine multi-cloud architecture patterns, use cases, and business continuity reference architecture, as well as how to approach secure multi-cloud peering. You'll also identify the services provided by multi-cloud management systems for simplifying next-gen firewall insertion and operations and the CI/CD processes for managing multi-cloud. You'll recognize the challenges of federated multi-cloud PaaS and hybrid and multi-cloud environment monitoring, design consideration for setting up multi-cloud disaster recovery processes, and the differences between cloud orchestration and automation. Finally, you'll create and configure a virtual network, gateway subnet, VPN gateway, and virtual private cloud Elastic IP VPN device in Azure and AWS.

A CloudOps engineer should be able to deploy into various multi-cloud environments confidently. In this course, you'll recognize the key benefits of multi-cloud deployments and recall the CAMP and TOSCA principles for flexible multi-cloud deployment. You'll examine the features of high-performance cloud routing, cloud network-as-code, and multi-cloud and multi-region transit routing. You'll also identify multi-cloud deployment, management, and cost control tools, the features of Cloudify and Kubernetes for managing multi-cloud deployment challenges, and the conceptual architecture and benefits of CI/CD pipelines for multi-cloud deployment. Next, you'll outline how to create multi-cloud applications and segregate services. Finally, you'll deploy the Node.js web server and application using Cloudify, setup and configure Spinnaker for multi-cloud deployments, configure Jenkins for multi-cloud pipeline management, and create and configure a simulated hybrid environment for deployment.

Splunk is a horizontal application with many possible use cases. In this course, you'll explore the core Splunk products, features, and pricing options that can help achieve CloudOps observability, discover problems, collect and index data, gain business-critical insights, and implement a visualization service for cloud operational intelligence. Additionally, you'll examine the benefits of using Splunk Cloud, the data ingestion concepts used by this product, and its approach to identifying, investigating, and resolving critical issues. You'll also recognize the infrastructure monitoring capabilities provided by Splunk App for Infrastructure. Moving on, you'll learn to use Splunk to explore, categorize, and analyze data and generate Sparklines. You'll navigate Splunk Cloud's primary interface. You'll ingest, organize, and mine data in Splunk to glean operational intelligence. And lastly, you'll integrate VictorOps with Splunk.

The components of Splunk provide CloudOps practitioners with reliable methods to give their data meaning and structure in efficient ways. In this course, you'll examine various Splunk components used to create reports, including datasets, data models, and inheritance. You'll also explore the primary components of Splunk's Search Processing Language, some best practices for designing data models with Splunk, and the different types of lookup configurations you can create in Splunk. You'll then use the Data Model Editor to design a data model and create charts, dashboards, and reports for visualizing ingested data. You'll use commands in Splunk to transform search results into data structures. You'll create pivot reports, lookup files, alerts, and search macros. Lastly, you'll learn how to run Splunk reports automatically.

You may know how to implement continuous integration (CI) and continuous delivery (CD) in a single cloud environment, but what about more advanced environments? In this course, you'll explore the challenges of applying CI/CD techniques to hybrid and multi-cloud environments and the benefits and use cases for doing so. You'll examine the 12-factor multi-cloud CI/CD process, the critical components of integrated solution design, the prominent hybrid and multi-cloud architecture patterns, and tools to manage CI/CD processes. You'll then outline how to set up multi-cloud environments geared for CI/CD implementation and how to transition from traditional multi-cloud to secure CI/CD deployment. Next, you'll investigate enterprise CI/CD patterns for diversified hybrid and multi-cloud environments and how to build pipelines for multi-cloud application deployment. Lastly, you'll identify the different hybrid environments that can simplify multi-cloud CI/CD processes.

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