Pitfalls Pipelines
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Advanced GitLab CI/CD Pipelines: An In-Depth Guide for Continuous Integration and Deployment
Unlock the full potential of GitLab CI/CD with "Advanced GitLab CI/CD Pipelines: An In-Depth Guide for Continuous Integration and Deployment," your ultimate resource for accelerating and optimizing software development. This expertly crafted guide delves into advanced strategies, empowering you to automate, secure, and scale your development workflows efficiently. Whether you're a novice eager to set up your first pipeline or a seasoned professional aiming to enhance your workflow, this book delivers actionable insights and best practices for leveraging GitLab's powerful CI/CD capabilities. Explore comprehensive topics such as managing artifacts, integrating external services, and deploying complex applications across multiple environments with ease. Each chapter, written in a straightforward and direct style, provides a deep dive into essential areas, from securing your pipelines to containerization and orchestration with Docker and Kubernetes. With real-world applications, troubleshooting tips, and performance optimization strategies, this guide ensures you're equipped to tackle any project with confidence. "Advanced GitLab CI/CD Pipelines" is not just a book; it's a roadmap to achieving CI/CD excellence in your projects, ensuring fast, reliable, and high-quality software delivery. Embrace the future of software development with this in-depth guide and transform your GitLab CI/CD journey today.
Cost-Effective Data Pipelines
Author: Sev Leonard
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2023-07-13
The low cost of getting started with cloud services can easily evolve into a significant expense down the road. That's challenging for teams developing data pipelines, particularly when rapid changes in technology and workload require a constant cycle of redesign. How do you deliver scalable, highly available products while keeping costs in check? With this practical guide, author Sev Leonard provides a holistic approach to designing scalable data pipelines in the cloud. Intermediate data engineers, software developers, and architects will learn how to navigate cost/performance trade-offs and how to choose and configure compute and storage. You'll also pick up best practices for code development, testing, and monitoring. By focusing on the entire design process, you'll be able to deliver cost-effective, high-quality products. This book helps you: Reduce cloud spend with lower cost cloud service offerings and smart design strategies Minimize waste without sacrificing performance by rightsizing compute resources Drive pipeline evolution, head off performance issues, and quickly debug with effective monitoring Set up development and test environments that minimize cloud service dependencies Create data pipeline code bases that are testable and extensible, fostering rapid development and evolution Improve data quality and pipeline operation through validation and testing
Building ETL Pipelines with Python
Author: Brij Kishore Pandey
language: en
Publisher: Packt Publishing Ltd
Release Date: 2023-09-29
Develop production-ready ETL pipelines by leveraging Python libraries and deploying them for suitable use cases Key Features Understand how to set up a Python virtual environment with PyCharm Learn functional and object-oriented approaches to create ETL pipelines Create robust CI/CD processes for ETL pipelines Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionModern extract, transform, and load (ETL) pipelines for data engineering have favored the Python language for its broad range of uses and a large assortment of tools, applications, and open source components. With its simplicity and extensive library support, Python has emerged as the undisputed choice for data processing. In this book, you’ll walk through the end-to-end process of ETL data pipeline development, starting with an introduction to the fundamentals of data pipelines and establishing a Python development environment to create pipelines. Once you've explored the ETL pipeline design principles and ET development process, you'll be equipped to design custom ETL pipelines. Next, you'll get to grips with the steps in the ETL process, which involves extracting valuable data; performing transformations, through cleaning, manipulation, and ensuring data integrity; and ultimately loading the processed data into storage systems. You’ll also review several ETL modules in Python, comparing their pros and cons when building data pipelines and leveraging cloud tools, such as AWS, to create scalable data pipelines. Lastly, you’ll learn about the concept of test-driven development for ETL pipelines to ensure safe deployments. By the end of this book, you’ll have worked on several hands-on examples to create high-performance ETL pipelines to develop robust, scalable, and resilient environments using Python.What you will learn Explore the available libraries and tools to create ETL pipelines using Python Write clean and resilient ETL code in Python that can be extended and easily scaled Understand the best practices and design principles for creating ETL pipelines Orchestrate the ETL process and scale the ETL pipeline effectively Discover tools and services available in AWS for ETL pipelines Understand different testing strategies and implement them with the ETL process Who this book is for If you are a data engineer or software professional looking to create enterprise-level ETL pipelines using Python, this book is for you. Fundamental knowledge of Python is a prerequisite.