DevOps Concepts
In this Introduction to DevOps, you’ll master the DevOps basics and learn the key concepts, tools, and techniques to improve productivity.
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Course Description
Discover the Basics of DevOps
DevOps is all about driving high-quality software development productively and collaboratively. It is a mix of cultural philosophies, practices, and tools to deliver software in an overall better way. This introduction to DevOps course simplifies the complex modern software development environments and puts you in the driver's seat.
You will see a comprehensive overview of software development, and you will learn all of the essential concepts behind DevOps and apply them to real-life use cases.
Explore Key DevOps Concepts
As you work through the course, you’ll explore the differences between DevOps, DataOps, and MLOps. In addition, you’ll cover basic project management methodologies, as well as basic software architecture concepts.
Discover the Essential DevOps Tools
Once you’ve built your knowledge in these areas, you’ll move on to the main software infrastructure concepts and explore continuous integration and continuous delivery. You’ll also learn about some of the main DevOps tools and explore how we can ensure data quality and security.
After completing this introduction to DevOps course, you will be able to apply your knowledge to almost any software development project to increase the output's quality and improve your team's productivity. So let's start exploring modern software development and applying what we learn from day one!
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Get your team access to the full DataCamp platform, including all the features.In the following Tracks
Professional Data Engineer in Python
Go To Track- 1
Introduction to DevOps
FreeThis chapter will go through what DevOps is, discover its principles and see what benefits it brings. You will discover how it is applied to different kinds of software development. Lastly, you will look at the basics of project management to see different approaches and how they can power up DevOps to bring substantial advantages to organizations.
What is DevOps?50 xpBenefits of DevOps50 xpCharacteristics of DevOps100 xpUse Cases for DevOps50 xpWhich engineer?100 xpEmploying the correct model100 xpDevOps implementations50 xpProject Management Methodologies for DevOps50 xpProject management frameworks100 xpFactors to decide the best project management framework100 xpChoosing the best project management model50 xp - 2
DevOps Architecture
This chapter introduces the main components of IT infrastructure, change management, and software architecture. You will see how different parts come together to compose online products, how they interact with each other, and how teams collaborate on the DevOps Change Management Model. You’ll explore the main elements of DevOps in detail. At the end of this chapter, you will be empowered to tackle some of the complex software engineering problems, like architectural design, and improve online products safely and quickly.
The DevOps Change Management Model50 xpDevOps cycle components100 xpData Engineering in the DevOps cycle100 xpMain Software Architecture Systems50 xpData in motion50 xpMaking architectural decisions100 xpModern IT Infrastructure Concepts50 xpIT infrastructure components100 xpChange management components100 xpElements of DevOps50 xpCI/CD pipelines100 xpDevOps concepts vs. generic infra concepts100 xp - 3
Implementation of DevOps for Data Engineering
Here, you will embark on a journey to navigate DevOps through the lens of a data engineer. You will explore what the DevOps architecture means from a Data Engineering standpoınt. Further, you will look at the main concepts related to Data Pipelines and how they are used in a microservices architecture. After learning about data pipelines, you will put your Data Scientist hat on and look at DevOps from a reporting perspective. Lastly, you will look at the tooling environment of DevOps and discuss the main tools used for DevOps.
Data Engineering Implications of the DevOps Architecture50 xpMicroservices vs. monolithic architecture100 xpData Engineering for microservices100 xpData Pipelines50 xpMain data operations100 xpBatch vs. stream processing100 xpAnalytics & Reporting with DevOps50 xpChange management metrics100 xpReporting architecture for DevOps100 xpTools: Ecosystem50 xpArchitecture systems and tools50 xpTools in DevOps cycle100 xpAutomating data pipelines50 xp - 4
Accurate, Predictive, and Unbiased Data With DevOps
In this final chapter, you will examine how DevOps helps ensure high data quality. Furthermore, you will look into quality and reliability in software. Last but not least, you will look at the cultural concepts enabling DevOps. Then, you will revamp everything you have learned and be fully equipped with the power of DevOps.
Ensuring Data Quality Standards with DevOps50 xpData quality100 xpData quality elements100 xpObservability and Reliability50 xpObservability vs. testing100 xpIncreasing reliability100 xpDevOps Cultural Concepts50 xpCultural concepts100 xpReacting to an incident100 xpTying it all together50 xpBenefits of DevOps50 xpDevOps cycle100 xpCONGRATS!50 xp
Training 2 or more people?
Get your team access to the full DataCamp platform, including all the features.In the following Tracks
Professional Data Engineer in Python
Go To Trackcollaborators
Cem Sakarya
See MoreInstructor & DevOps Risk Advisor
Risk Advisor specializing in DevOps and Platform Engineering risks and Software Engineering health best practices. Data Scientist by heart.
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