Hands On Python For Devops

Unleash DevOps excellence with Python and its ecosystem of tools for seamless orchestration on both local and cloud platforms, such as GCP, AWS, and Azure Key Features Integrate Python into DevOps for streamlined workflows, task automation, and improved collaboration Combine the principles of Python and DevOps into a unified approach for problem solving Learn about Python’s role in Infrastructure as Code (IaC), MLOps, networking, and other domains Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionPython stands out as a powerhouse in DevOps, boasting unparalleled libraries and support, which makes it the preferred programming language for problem solvers worldwide. This book will help you understand the true flexibility of Python, demonstrating how it can be integrated into incredibly useful DevOps workflows and workloads, through practical examples. You'll start by understanding the symbiotic relation between Python and DevOps philosophies and then explore the applications of Python for provisioning and manipulating VMs and other cloud resources to facilitate DevOps activities. With illustrated examples, you’ll become familiar with automating DevOps tasks and learn where and how Python can be used to enhance CI/CD pipelines. Further, the book highlights Python’s role in the Infrastructure as Code (IaC) process development, including its connections with tools like Ansible, SaltStack, and Terraform. The concluding chapters cover advanced concepts such as MLOps, DataOps, and Python’s integration with generative AI, offering a glimpse into the areas of monitoring, logging, Kubernetes, and more. By the end of this book, you’ll know how to leverage Python in your DevOps-based workloads to make your life easier and save time.What you will learn Implement DevOps practices and principles using Python Enhance your DevOps workloads with Python Create Python-based DevOps solutions to improve your workload efficiency Understand DevOps objectives and the mindset needed to achieve them Use Python to automate DevOps tasks and increase productivity Explore the concepts of DevSecOps, MLOps, DataOps, and more Use Python for containerized workloads in Docker and Kubernetes Who this book is for This book is for IT professionals venturing into DevOps, particularly programmers seeking to apply their existing programming knowledge to excel in this field. For DevOps professionals without a coding background, this book serves as a resource to enhance their understanding of development practices and communicate more effectively with developers. Solutions architects, programmers, and anyone regularly working with DevOps solutions and Python will also benefit from this hands-on guide.

Much has changed in technology over the past decade. Data is hot, the cloud is ubiquitous, and many organizations need some form of automation. Throughout these transformations, Python has become one of the most popular languages in the world. This practical resource shows you how to use Python for everyday Linux systems administration tasks with today’s most useful DevOps tools, including Docker, Kubernetes, and Terraform. Learning how to interact and automate with Linux is essential for millions of professionals. Python makes it much easier. With this book, you’ll learn how to develop software and solve problems using containers, as well as how to monitor, instrument, load-test, and operationalize your software. Looking for effective ways to "get stuff done" in Python? This is your guide. Python foundations, including a brief introduction to the language How to automate text, write command-line tools, and automate the filesystem Linux utilities, package management, build systems, monitoring and instrumentation, and automated testing Cloud computing, infrastructure as code, Kubernetes, and serverless Machine learning operations and data engineering from a DevOps perspective Building, deploying, and operationalizing a machine learning project

Explore and apply best practices for efficient application deployment. This book draws upon author Moshe Zadka's years of Dev Ops experience and focuses on the parts of Python, and the Python ecosystem, that are relevant for DevOps engineers. You'll start by writing command-line scripts and automating simple DevOps-style tasks. You'll then move on to more advanced cases, like using Jupyter as an auditable remote-control panel, and writing Ansible and Salt extensions. This work also covers how to use the AWS API to manage cloud infrastructure, and how to manage Python programs and environments on remote machines. Python was invented as a systems management language for distributed operating systems, which makes it an ideal tool for DevOps. ​Assuming a basic understanding of Python concepts, this book is perfect for engineers who want to move from operations/system administration into coding. What You'll LearnUse third party packages and create new packages Create operating system management and automation code in Python Write testable code, and testing best practices Work with REST APIs for web clients Who This Book Is For Junior or intermediate sysadmin who has picked up some bash and Python basics.

A step-by-step guide to building microservices using Python and Docker, along with managing and orchestrating them with Kubernetes Key FeaturesLearn to use Docker containers to create, operate, and deploy your microservicesCreate workflows to manage independent deployments on coordinating services using CI and GitOps through GitHub, Travis CI, and FluxDevelop a REST microservice in Python using the Flask framework and Postgres databaseBook Description Microservices architecture helps create complex systems with multiple, interconnected services that can be maintained by independent teams working in parallel. This book guides you on how to develop these complex systems with the help of containers. You’ll start by learning to design an efficient strategy for migrating a legacy monolithic system to microservices. You’ll build a RESTful microservice with Python and learn how to encapsulate the code for the services into a container using Docker. While developing the services, you’ll understand how to use tools such as GitHub and Travis CI to ensure continuous delivery (CD) and continuous integration (CI). As the systems become complex and grow in size, you’ll be introduced to Kubernetes and explore how to orchestrate a system of containers while managing multiple services. Next, you’ll configure Kubernetes clusters for production-ready environments and secure them for reliable deployments. In the concluding chapters, you’ll learn how to detect and debug critical problems with the help of logs and metrics. Finally, you’ll discover a variety of strategies for working with multiple teams dealing with different microservices for effective collaboration. By the end of this book, you’ll be able to build production-grade microservices as well as orchestrate a complex system of services using containers. What you will learnDiscover how to design, test, and operate scalable microservicesCoordinate and deploy different services using KubernetesUse Docker to construct scalable and manageable applications with microservicesUnderstand how to monitor a complete system to ensure early detection of problemsBecome well versed with migrating from an existing monolithic system to a microservice oneUse load balancing to ensure seamless operation between the old monolith and the new serviceWho this book is for This book is for developers, engineers, or software architects who are trying to move away from traditional approaches for building complex multi-service systems by adopting microservices and containers. Although familiarity with Python programming is assumed, no prior knowledge of Docker is required.

A step-by-step guide to implementing Continuous Integration and Continuous Delivery for Mobile, Hybrid, and Web applications KEY FEATURES a- This book covers all these practices that can be utilized in real-life scenarios with sample applications written in Java, Android, iOS, Node.js, Angular, Ionic Cordova, Xamarin, Python, and PHP. a- This book provides detailed insight into Microsoft Azure Cloud, especially Platform as a Service Model - Azure App Services. a- This book utilizes the Multi-Stage Pipeline Feature of Azure DevOps. Step by Step implementation of Continuous Practices of DevOps makes it easy to understand even for beginners of DevOps practices. DESCRIPTION This book will cover an approach that includes the understanding of DevOps, Assessment of AS-IS state, DevOps Practices Implementation and measurement of success. The main objective is to demonstrate Continuous Practices of DevOps Culture using Microsoft Azure DevOps and Microsoft Azure Cloud across different types of applications such as Mobile apps, Hybrid Mobile App, and Web applications. The main idea is to have a uniform approach across different types of applications such as Mobile apps, Hybrid Mobile App, and Web applications. It is important to have a uniform approach of DevOps Practices implementation in an application written in different programming languages such as Java, Android, iOS, Node.js, Angular, Ionic Cordova, Xamarin, Python, and PHP. WHAT WILL YOU LEARN a- Learn to create a Multi-Stage (CICD) Pipeline for sample applications a- Configure Unit Test Execution and Code Coverage Reports in Azure DevOps for sample applications a- Create and configure Cloud resources using Platform as a Service Model - Azure App Services for Web Applications and deploy Web Applications to Azure App Services using Pipeline a- Understand how to distribute Mobile App Packages (APK and IPA) to App Center WHO THIS BOOK IS FOR This book is suitable for DevOps Consultants, DevOps Evangelists, DevOps Engineers, Technical Specialists, Technical Architects, Cloud Experts, and Beginners. TABLE OF CONTENTS 1. Overview of DevOps Practices 2. DevOps Assessment - Measure the "e;AS-IS"e; Maturity 3. DevOps Practices Implementation for Android App - Azure DevOps Pipelines 4. DevOps Practices Implementation for iOS App - Azure DevOps Pipelines 5. DevOps Practices Implementation for Native Apps using App Center 6. DevOps Practices Implementation for Java App - Azure DevOps Pipelines 7. DevOps Practices Implementation for Node.js Apps - Azure DevOps Pipelines 8. DevOps Practices Implementation for Angular App - Azure DevOps Pipelines 9. DevOps Practices Implementation for Python and, PHP - Azure DevOps Pipelines 10. DevOps Practices Implementation for Hybrid Mobile App (Ionic and Xamarin) - Azure DevOps Pipeline 11. Azure DevOps Best Practices 12. Measure Benefits of DevOps Practices Implementations AUTHOR BIO Mitesh is a DevOps engineer. He is in love with the DevOps culture and concept. Continuous improvement is his motto in life with existing imperfection. Mitesh has worked on multiple DevOps practices implementation initiatives. His primary focus is on the improvement of the existing culture of an organization or a project using Continuous Integration and Continuous Delivery. He believes that attitude and dedication are some of the biggest virtues that can improve professional as well as personal life! He has good experience in DevOps consulting, and he enjoys talking about DevOps and CULTURE transformation using existing practices and improving them with open source or commercial tools. Mitesh always believes that DevOps is a cultural transformation, and it is facilitated by People, Processes, and Tools. DevOps transformation is a tools agnostic approach. He loves to give training and share knowledge with the community. He has a keen knowledge of programming, and he is aware of different languages/frameworks/platforms such as Java, Android, iOS, NodeJS, Angular. His main objective is to get enough information related to the project in a way that it is helpful in creating an end to end automation pipeline. In his leisure time, he likes to walk in Garden, to click photographs, and to do cycling. He prefers to spend time in peaceful places. His favorite tool / services for DevOps Practices implementation is Azure DevOps and Jenkins in commercial and open sources categories respectively.

Protect your organization's security at all levels by introducing the latest strategies for securing DevOps Key Features Integrate security at each layer of the DevOps pipeline Discover security practices to protect your cloud services by detecting fraud and intrusion Explore solutions to infrastructure security using DevOps principles Book Description DevOps has provided speed and quality benefits with continuous development and deployment methods, but it does not guarantee the security of an entire organization. Hands-On Security in DevOps shows you how to adopt DevOps techniques to continuously improve your organization’s security at every level, rather than just focusing on protecting your infrastructure. This guide combines DevOps and security to help you to protect cloud services, and teaches you how to use techniques to integrate security directly in your product. You will learn how to implement security at every layer, such as for the web application, cloud infrastructure, communication, and the delivery pipeline layers. With the help of practical examples, you’ll explore the core security aspects, such as blocking attacks, fraud detection, cloud forensics, and incident response. In the concluding chapters, you will cover topics on extending DevOps security, such as risk assessment, threat modeling, and continuous security. By the end of this book, you will be well-versed in implementing security in all layers of your organization and be confident in monitoring and blocking attacks throughout your cloud services. What you will learn Understand DevSecOps culture and organization Learn security requirements, management, and metrics Secure your architecture design by looking at threat modeling, coding tools and practices Handle most common security issues and explore black and white-box testing tools and practices Work with security monitoring toolkits and online fraud detection rules Explore GDPR and PII handling case studies to understand the DevSecOps lifecycle Who this book is for Hands-On Security in DevOps is for system administrators, security consultants, and DevOps engineers who want to secure their entire organization. Basic understanding of Cloud computing, automation frameworks, and programming is necessary.

Programming With Python - 8 BOOK BUNDLE!! Deep Learning With Keras Here Is A Preview Of What You’ll Learn Here… The difference between deep learning and machine learning Deep neural networks Convolutional neural networks Building deep learning models with Keras Multi-layer perceptron network models And much more... Convolutional Neural Networks In Python Here Is A Preview Of What You’ll Learn Here… Convolutional neural networks structure How convolutional neural networks actually work Convolutional neural networks applications The importance of convolution operator How to build a simple image classification CNN And much, much more! Python Machine Learning Here Is A Preview Of What You’ll Learn Here… Basics behind machine learning techniques Most commonly used machine learning algorithms, linear and logistic regression, decision trees support vector machines, k-nearest neighbors, random forests Solving multi-clasisfication problems Data visualization with Matplotlib and data transformation with Pandas and Scikit-learn Solving multi-label classification problems And much, much more... Machine Learning With TensorFlow Here Is A Preview Of What You’ll Learn Here… What is machine learning Main uses and benefits of machine learning How to get started with TensorFlow, installing and loading data Data flow graphs and basic TensorFlow expressions Creating MNIST classifiers with one-hot transformation And much, much more... Data Analytics With Python Here Is A Preview Of What You’ll Learn Here… What is Data Analytics? Difference between data science, big data and data analytics Installing python Python data structures Pandas series and data frames And much, much more... Natural Language Processing With Python Here Is A Preview Of What You’ll Learn Here… Challenges of natural language processing How natural language processing works? Part of speech tagging N-grams Running natural language processing script And much, much more... DevOps Handbook Here Is A Preview Of What You’ll Learn Here… Issues and mistakes plaguing software development What is software development life cycle? How software development life cycle works? The origins of devops Testing and building systems tools And much, much more... DevOps Adoption Here Is A Preview Of What You’ll Learn Here… Devops definition Overcoming traditional dev and ops Devops and security integration Devops success factors Is devops right for you? And much, much more... Get this book bundle NOW and SAVE money!

Become an expert in implementing advanced, network-related tasks with Python. Key Features Build the skills to perform all networking tasks using Python with ease Use Python for network device automation, DevOps, and software-defined networking Get practical guidance to networking with Python Book DescriptionThis book begins with a review of the TCP/ IP protocol suite and a refresher of the core elements of the Python language. Next, you will start using Python and supported libraries to automate network tasks from the current major network vendors. We will look at automating traditional network devices based on the command-line interface, as well as newer devices with API support, with hands-on labs. We will then learn the concepts and practical use cases of the Ansible framework in order to achieve your network goals. We will then move on to using Python for DevOps, starting with using open source tools to test, secure, and analyze your network. Then, we will focus on network monitoring and visualization. We will learn how to retrieve network information using a polling mechanism, ?ow-based monitoring, and visualizing the data programmatically. Next, we will learn how to use the Python framework to build your own customized network web services. In the last module, you will use Python for SDN, where you will use a Python-based controller with OpenFlow in a hands-on lab to learn its concepts and applications. We will compare and contrast OpenFlow, OpenStack, OpenDaylight, and NFV. Finally, you will use everything you’ve learned in the book to construct a migration plan to go from a legacy to a scalable SDN-based network.What you will learn Review all the fundamentals of Python and the TCP/IP suite Use Python to execute commands when the device does not support the API or programmatic interaction with the device Implement automation techniques by integrating Python with Cisco, Juniper, and Arista eAPI Integrate Ansible using Python to control Cisco, Juniper, and Arista networks Achieve network security with Python Build Flask-based web-service APIs with Python Construct a Python-based migration plan from a legacy to scalable SDN-based network Who this book is for If you are a network engineer or a programmer who wants to use Python for networking, then this book is for you. A basic familiarity with networking-related concepts such as TCP/IP and a familiarity with Python programming will be useful.