Core DevOps Skills

The modern software development landscape is filled with companies trying to find their space in the global market. To expedite the creation of the best software possible, many companies leverage DevOps tools to help ensure the best code is quickly in front of the customer. In this course, learn the differences between software development and software deployment management, in addition to several software deployment models, such as the waterfall, iterative, spiral, V, big bang, and Agile models. Next, examine DevOps, its benefits, and how it differs from previous methodologies. Finally, discover challenges when embracing a DevOps methodology. Upon completion, you'll be able to define the elements of software management and deployments with a focus on comparing and contrasting DevOps to other methodologies.

One of the most important aspects of DevOps is the way in which automation enables continuous processes so that the flow of software development can progress with as few interruptions as possible. In this course you will learn what aspects of automation are integrated into what will later be different stages of a development pipeline. After an overview of DevOps principles and practices, you will explore the concept of "continuous" as it applies to development, integration, testing, deployment, monitoring, and feedback. Then you will examine the idea of configuration management. Next, you will focus on many "as-code" concepts, such as Infrastructure-as-code, content-as-code, DevOps-as-code, and pipeline-as-code. Finally, you will examine the maturity process for an organization to transition from not utilizing DevOps to fully embracing DevOps to the degree that makes sense for the organization.

As with many things in all industries, software development does not exist in a vacuum. The important advances in DevOps software deployment management have been heavily influenced by the principles of the Agile framework. In this course, learn about Agile practices and compare and contrast various elements of Agile and DevOps. Examine Agile and DevOps similarities and differences in methodologies, processes, teams, testing principles, goals/key target areas, and requirements. Finally, investigate the synergy between efforts made in Agile development and the DevOps support of that development. Upon completion, you'll be able to recognize Agile development practices and outline how they compare, differ, or work with DevOps practices.

From the moment a developer has finished their keystrokes to the moment that an end user encounters that software, every piece of software has a journey it must go through. The DevOps pipeline is used to automate and facilitate the steps of that journey. In this course, learn what a DevOps pipeline is and how automation relates to it. Next, explore the source, build, test, deploy, validation, monitoring, and improvement stages of the CI/CD pipeline. Finally, examine the effects of modern computing on the principles of continuous delivery in the pipeline, such as containerization of software and site reliability engineering (SRE). Upon completion, you'll be able to outline how to apply continuous principles in the DevOps CI/CD pipeline.

Voltaire once said, "Is there anyone so wise as to learn by the experience of others?" We can learn a great deal from the successes and mistakes of others that have taken the journey of DevOps before us. In this course, you will learn about the journey to DevOps maturity taken by various private companies and government institutions. You will see how different organizations used the principles and practices of DevOps and the continuous integration and continuous deployment (CI/CD) pipeline to create an automated method of managing their software needs. In addition, you will see how some companies, such as Netflix, created innovations in the world of DevOps in order to meet the demands of their industry.

The more things stay the same, the more they also change, and when it comes to developing software, designers have always wanted more tools to make their work perform well and run with stability. Through this course, explore the evolution of classic server and virtual computing that has led to current container-related toolsets. Examine the pros and cons of different types of computing systems. Explore two major container-related toolsets, Docker and Kubernetes. Finally, discover some of the smaller container systems that can be selected for specific needs. After course completion, you'll be able to outline what containers are and differentiate between major container providers.

One of the most commonly recognized types of containers in the market today is the open platform called Docker. Becoming familiar with Docker is a critical step for any modern software developer. Begin this course by exploring the different services provided by Docker, including the details of how the infrastructure workflow of Docker interfaces with the software components being developed. Discover how to provision Docker resources and how Docker images and Dockerfiles are used to create consistent Docker-based container environments. Then, you will focus on managing Docker resources. Finally, you will investigate common use cases to determine how Docker can be used most effectively. When you have completed this course, you will be able to confidently describe Docker containers, the Docker workflow, and successfully manage Docker resources.

No matter what the infrastructure is that you are using to manage your applications, you are likely to find challenges trying to keep up when scaling out as demand for resources increases. The answer to this problem is automation and orchestration, and one of the most common tools for providing automation and orchestration for containers is called Kubernetes. Explore this open-source container orchestration system. You will gain insight into the various terms associated with this software and investigate the common workflow used to produce containers and deploy software to scale. Then, you will discover how to secure a Kubernetes Cluster. Finally, you will examine Kubernetes use cases and identify the differences between Kubernetes and Docker. After course completion, you will be able to work with Kubernetes containers, outline the Kubernetes workflow, and determine its situational usefulness.

Final Exam: Core DevOps Skills will test your knowledge and application of the topics presented throughout the Core DevOps Skills track of the Core DevOps Skills Aspire Journey.

Chef offers a suite of software automation solutions to help with the top to bottom management of deployments, primarily revolving around bringing infrastructure and applications from development to delivery into production systems and beyond. Through this course, learn about the key concepts and features of Chef. Discover the prerequisites for installing Chef, its use cases, and the required syntax for using Ruby with Chef. Next, learn about the key components and features of the different products and solutions Chef offers. Finally, recognize the differences between Chef and Ansible and examine how they can work together. Upon completion, you'll be able to use the basic Chef platform offerings.

When software developers use a DevOps model based on Agile framework management, they need infrastructure to continuously integrate and deploy their software throughout their product's lifecycle. Jenkins software is one of the most commonly used tools to provide this deployment infrastructure. Through this course, learn the role of Jenkins in continuous integration and continuous development (CI/CD) and how it intersects with the needs of a DevOps environment. Discover how Jenkins supports CI/CD. Next, explore how Jenkins integrates with other software used in the DevOps process, including Docker, Ansible, AWS, Azure, Git, email, and Maven. Finally, examine the Jenkins job-building process. Upon completion, you'll be able to recognize the role of Jenkins in DevOps and integrate Jenkins with other software.

Becoming proficient in using any piece of software requires practice and exposure to key terms, concepts, and workflows associated with using that tool. Jenkins is no different in this regard. Through this course, learn key Jenkins concepts and how to use it for DevOps. Discover how to install the Jenkins platform using a variety of technologies and create a Jenkins build. Next, learn how to secure the Jenkins infrastructure and distribute Jenkins builds. Finally, examine how fingerprints and artifacts are used in a Jenkins infrastructure and the steps required to manage them. Upon completion, you'll be able to use Jenkins for DevOps.

In this course, you will discover practical uses of Ansible, including how to install, configure, and upgrade Ansible. You will learn how to create inventories, how to execute common commands, tasks, and playbooks, and how to troubleshoot possible playbook issues. Next, you will explore the command line interface to execute common options and use the debugger to resolve errors. Then, you will work with various Ansible plugins and determine when to use them. And finally, you will learn the best practices associated with using the Ansible Automation Platform. Upon course completion, you will be able to install and configure Ansible, work with playbooks, and define best practices.

Ansible allows you to add easy to understand automation to your DevOps environment. No special coding skills are needed to use this tool so your teams can quickly improve productivity. In this course, you will learn about Ansible's key components, the different applications of automation, and the features available within the Ansible platform. You will learn about Ansible's key tools and commands, orchestration, and how to use patterns as well as their limitations. You'll also identify how to use playbooks, and learn how to use Ansible Vault for encryption. Finally, you'll learn about the possible use cases for the Ansible toolset in a modern DevOps practice. Upon completion, you'll be familiar with key concepts and be able to perform basic operations in Ansible.

Final Exam: Core DevOps Tools will test your knowledge and application of the topics presented throughout the Core DevOps Tools track of the Core DevOps Skills Aspire Journey.

DevOps is a combination of culture, practices, and tools and a blend of development and IT operations to deliver quality software continuously and at high velocity. Organizations using Amazon Web Services (AWS) can leverage the cloud service to implement DevOps capabilities for the rapid building and delivery of software products. Through this course, learn about AWS's DevOps capabilities. Examine AWS continuous integration/continuous development (CI/CD) developer tools and services, including CodePipeline, CodeBuild, CodeDeploy, and CodeStar. Next, explore AWS offerings for microservices and infrastructure as code (IaC). Finally, learn about AWS tools for monitoring and logging services, Platform as a Service (PaaS), and version control. Upon completion, you'll be able to outline AWS DevOps elements, principles, and practices.

Cultivating a more developer-like mindset is essential for modern operations personnel to keep up with innovative software solution deployments and practices. Organizations can use the comprehensive set of Amazon Web Services (AWS) to leverage DevOps practices. In this course, you will explore a practical approach to implementing DevOps practices using AWS. You will create and build a project with AWS CodeBuild, configure AWS CodeDeploy, and work with AWS CodePipeline and AWS CodeStar. Next, you will build a microservices architecture using various AWS tools. Then, focus on Infrastructure as a Code (IaC), cloud monitoring, web apps, and version control. Finally, you will discover how popular DevOps platforms Ansible, Jenkins, and Chef Automate can be integrated with AWS. Upon completion, you'll be able to outline key practices of a implementing a DevOps practice with AWS using AWS services and popular third-party DevOps platforms.

Modern operations personnel need to become more literate in more developer-like thinking and mindsets for the modern software solution deployments and practices. Organizations using Microsoft Azure can leverage DevOps practices using Azure's comprehensive set of services for implementing DevOps practices. In this course, you will explore a practical approach to implementing DevOps practices using Microsoft Azure, beginning with demonstrations on planning with Azure Boards, building a pipeline, connecting to a project, and working with pipelines. Then you will learn how to work with Repos, create and execute test plans, and use Azure Artifacts. Finally, you will discover how popular DevOps platforms Ansible, Jenkins, and Chef Automate can be integrated with Azure.

DevOps is a combination of culture, practices, and tools, merging development and IT operations to continuously deliver quality software at high velocity. Organizations using Microsoft Azure can leverage the popular cloud service to implement DevOps capabilities for the rapid building and delivering of software products. In this course, you will discover Azure and its DevOps capabilities, beginning with an introduction to DevOps and Azure, Azure DevOps Server. You will compare Azure-hosted DevOps to onsite DevOps. Then, you will explore essential Azure services like Boards, Pipelines, Repos, Test Plans, Artifacts, and the Azure extensions marketplace. Finally, you will examine Azure DevTest Labs, Azure Monitor, and DevOps tools integration in Azure. After course completion, you'll be able to define key components, practices, and principles of Azure DevOps services.

In order to be a competent practitioner of Google Cloud technologies, you will need to get up close and personal with the various tools used to create a DevOps infrastructure. In this course, you will discover the different components of the Google Cloud Platform (GCP). Begin by exploring the App Engine, Compute Engine, and Cloud VMware Engine. Then, learn how to enable and manage data storage such as Cloud Storage, Filestore, and databases such as Firebase, Bigtable, Datastore, and Firestore. You will delve into the mechanics of cloud networking using a content delivery network (CDN) and Cloud Router. Finally, investigate automation tools such as Cloud Build, as well as tools for monitoring and logging using Cloud Operations. After completing this course, you'll be able to implement the GCP elements that support a DevOps framework

You can't build a house without tools and materials. Similarly, you can't build a DevOps infrastructure without the tools and materials needed to support developer needs. In this course, learn about the basics of the Google Cloud Platform (GCP). Explore how GCP compares to other cloud platforms and learn about different elements of the platform, such as computing, storage, and networking. Next, investigate tools and services like identity management, databases, analytics, and artificial intelligence. Finally, examine the relationships between the GCP and container technologies such as Docker, clustering container technologies such as Kubernetes, and orchestration technologies such as Jenkins. Upon completion, you'll be able to identify how elements of Google Cloud Platform (GCP) support a DevOps framework.

DataOps processes help to manage data analytics and processing. It combines DevOps teams with other data roles to supply processes, tools, and organizational structures to support enterprises. Through this course, learn DataOps guiding principles and how to implement them properly in an organization. Explore DataOps platforms and tools, key DataOps principles, and best practices and challenges in implementing DataOps. Next, learn about the role of DataOps in automating data governance and compare DataOps to DevOps. Finally, discover how to establish a DataOps team and practice, the individual DataOps team roles and responsibilities, and the components of a DataOps architecture. After course completion, you'll be able to outline what DataOps is and how to properly implement it.

MLOps is used to scale and govern machine learning operations, while AIOps provides a way to solve business problems and reduce incident management overhead using AI. In this course, you'll begin with an introduction to what AIOps is and which common IT operations it can be applied to. Discover AIOps capabilities, main business areas which AIOps can be incorporated into, and the benefits to an organization considering adoption. Next, explore various business use cases suitable for AIOps and adoption from a business and technical perspective. Moving on, look at the capabilities provided by MLOps and the benefits of MLOps to a data scientist. Next, explore the steps involved in implementing MLOps including the tools, challenges, and best practices involved. Upon completion of this course, you'll be able to identify the differences between AIOps, MLOps, and DevOps.

Final Exam: DevOps Platforms and Operations will test your knowledge and application of the topics presented throughout the DevOps Platforms and Operations track of the Core DevOps Skills Aspire Journey.