Mastering Gitlab 12 Implement Devops Culture And Repository Management Solutions

Mastering GitLab 12

Mastering GitLab 12

An expert guide to helping you use DevOps techniques with the latest GitLab version to optimize and manage your software workflow Key FeaturesDelve into GitLab's architecture, and install and configure it to fit your environmentLearn about the underlying principles of Agile software development and DevOpsExplore Gitlab's features to manage enterprise cloud-native applications and servicesBook Description GitLab is an open source repository management and version control toolkit with functions for enterprises and personal software projects. It offers configurability options, extensions, and APIs that make it an ideal tool for enterprises to manage the software development life cycle. This book begins by explaining GitLab options and the components of the GitLab architecture. You will learn how to install and set up GitLab on-premises and in the cloud, along with understanding how to migrate code bases from different systems, such as GitHub, Concurrent Versions System, Team Foundation Version Control, and Subversion. Later chapters will help you implement DevOps culture by introducing the workflow management tools in GitLab and continuous integration/continuous deployment (CI/CD). In addition to this, the book will guide you through installing GitLab on a range of cloud platforms, monitoring with Prometheus, and deploying an environment with GitLab. You'll also focus on the GitLab CI component to assist you with creating development pipelines and jobs, along with helping you set up GitLab runners for your own project. Finally, you will be able to choose a high availability setup that fits your needs and helps you monitor and act on results obtained after testing. By the end of this book, you will have gained the expertise you need to use GitLab features effectively, and be able to integrate all phases in the development process. What you will learnInstall GitLab on premises and in the cloud using a variety of configurationsConduct data migration from the SVN, TFS, CVS, and GitHub platforms to GitLabUse GitLab runners to develop different types of configurations in software developmentPlan and perform CI/CD by using GitLab featuresMonitor and secure your software architecture using Prometheus and GrafanaImplement DevOps culture by introducing workflow management tools in GitLabWho this book is for If you are a software developer, DevOps professional, or any developer who wants to master GitLab for productive repository management in your day-to-day tasks, this book is for you. Basic understanding of the software development workflow is assumed.

Comet for Data Science

Gain the key knowledge and skills required to manage data science projects using Comet Key Features • Discover techniques to build, monitor, and optimize your data science projects • Move from prototyping to production using Comet and DevOps tools • Get to grips with the Comet experimentation platform Book Description This book provides concepts and practical use cases which can be used to quickly build, monitor, and optimize data science projects. Using Comet, you will learn how to manage almost every step of the data science process from data collection through to creating, deploying, and monitoring a machine learning model. The book starts by explaining the features of Comet, along with exploratory data analysis and model evaluation in Comet. You'll see how Comet gives you the freedom to choose from a selection of programming languages, depending on which is best suited to your needs. Next, you will focus on workspaces, projects, experiments, and models. You will also learn how to build a narrative from your data, using the features provided by Comet. Later, you will review the basic concepts behind DevOps and how to extend the GitLab DevOps platform with Comet, further enhancing your ability to deploy your data science projects. Finally, you will cover various use cases of Comet in machine learning, NLP, deep learning, and time series analysis, gaining hands-on experience with some of the most interesting and valuable data science techniques available. By the end of this book, you will be able to confidently build data science pipelines according to bespoke specifications and manage them through Comet. What you will learn • Prepare for your project with the right data • Understand the purposes of different machine learning algorithms • Get up and running with Comet to manage and monitor your pipelines • Understand how Comet works and how to get the most out of it • See how you can use Comet for machine learning • Discover how to integrate Comet with GitLab • Work with Comet for NLP, deep learning, and time series analysis Who this book is for This book is for anyone who has programming experience, and wants to learn how to manage and optimize a complete data science lifecycle using Comet and other DevOps platforms. Although an understanding of basic data science concepts and programming concepts is needed, no prior knowledge of Comet and DevOps is required.