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Learn how to prepare for--and pass--the KCNA (Kubernetes and Cloud Native Associate) certification exam. This practical guide serves as both a study guide and point of entry for practitioners looking to explore and adopt cloud native technologies. Adrian Gonzalez Sanchez teaches you not only the core technology fundamentals, but also the community and industry that KCNA serves. With the meteoric rise in cloud adoption, cloud native technologies such as Kubernetes have become the de facto industry standard. Other Kubernetes certifications--CKAD, CKA, and CKS--are all geared towards higher level technical proficiency. The KCNA certification exam covers the cloud native environment generally as well as the fundamental Kubernetes skills and knowledge. This guide helps you learn: How to best and most efficiently prepare for the KCNA exam The latest cloud native developments and their importance The fundamentals of Kubernetes, cloud native development, and related CNCF projects The core elements of Kubernetes applications The crucial elements of modern cloud native development How to differentiate and choose cloud native technologies The market value of passing the KCNA exam About the author: Adrian Gonzalez Sanchez is a cloud, data and AI specialist at Microsoft, and the Industrial AI Lead for the Spanish Observatory of Ethical AI (OdiseIA).

Great engineers don't necessarily make great leaders -- at least, not without a lot of work. Finding your path to becoming a strong leader is often fraught with challenges. It's not easy to figure out how to be successful, empathetic, and caring yet tough. Whether you're on the management or individual contributor track, you need to develop strong leadership skills. This practical book guides you on the path to becoming a well-rounded and resilient engineering leader."--

Deep learning is rapidly gaining momentum in the world of finance and trading. But for many professional traders, this sophisticated field has a reputation for being complex and difficult. This hands-on guide teaches you how to develop a deep learning trading model from scratch using Python, and it also helps you create and backtest trading algorithms based on machine learning and reinforcement learning. Sofien Kaabar--financial author, trading consultant, and institutional market strategist--introduces deep learning strategies that combine technical and quantitative analyses. By fusing deep learning concepts with technical analysis, this unique book presents outside-the-box ideas in the world of financial trading. This A-Z guide also includes a full introduction to technical analysis, evaluating machine learning algorithms, and algorithm optimization. Understand and create machine learning and deep learning models Explore the details behind reinforcement learning and see how it's used in time series Understand how to interpret performance evaluation metrics Examine technical analysis and learn how it works in financial markets Create technical indicators in Python and combine them with ML models for optimization Evaluate the models' profitability and predictability to understand their limitations and potential

Advance your Power BI skills by adding AI to your repertoire at a practice level. With this practical book, business-oriented software engineers and developers will learn the terminologies, practices, and strategy necessary to successfully incorporate AI into your business intelligence estate.

Filled with tips, tricks, and techniques, this easy-to-use book is the perfect resource for intermediate to advanced users of Excel. You'll find complete recipes for more than a dozen topics covering formulas, PivotTables, charts, Power Query, and more. Each recipe poses a particular problem and outlines a solution that you can put to use right away--without having to comb through tutorial pages. Whether you're a data analyst, project manager, or financial analyst, author Dawn Griffiths directs you straight to the answers you need. Ideal as a quick reference, Excel Cookbook is also perfect for learning how to work in a more efficient way, leading to greater productivity on the job. With this book, you'll jump in and get answers to your questions--fast. This cookbook shows you how to: Get the most out of Excel's features Address complex data problems in the best way possible Collect, manage, and analyze data from a variety of sources Use functions and formulas with ease--including dynamic array and lambda formulas Analyze data with PivotTables, Power Pivot, and more Import and transform data with Power Query Write custom functions and automate Excel with VBA

Do you wish the existing books on site reliability engineering started at the beginning? Do you wish someone would walk you through how to become an SRE, how to think like an SRE, or how to build and grow a successful SRE function in your organization? Becoming SRE addresses all of these needs and more with three interconnected sections: the essential groundwork for understanding SRE and SRE culture, advice for individuals on becoming an SRE, and guidance for organizations on creating and developing a thriving SRE practice. Acting as your personal and personable guide, author David Blank-Edelman takes you through subjects like: SRE mindset, SRE culture, and SRE advocacy What you need to get started and hired in SRE and what the job will be like when you get there What you need to bring SRE into an organization and what is required for a good organizational fit so it can thrive there How to work with your business folks and management around SRE How SRE can grow and mature in an organization over time Ready to become an SRE or introduce SRE into your organization? This book is here to help.

NGINX is one of the most widely used web servers available today, in part because of its capabilities as a load balancer and reverse proxy server for HTTP and other network protocols. This cookbook provides easy-to-follow examples to real-world problems in application delivery. The practical recipes will help you set up and use either the open source or commercial offering to solve problems in various use cases.For professionals who understand modern web architectures, such as n-tier or microservice designs, and common web protocols including TCP and HTTP, these recipes provide proven solutions for security, software load balancing, and monitoring and maintaining NGINXs application delivery platform. Youll also explore advanced features of both NGINX and NGINX Plus, the free and licensed versions of this server.Youll find recipes for:High-performance load balancing with HTTP, TCP, and UDPSecuring access through encrypted traffic, secure links, HTTP authentication subrequests, and moreDeploying NGINX to Google Cloud, AWS, and Azure cloud computing servicesSetting up and configuring NGINX ControllerInstalling and configuring the NGINX Plus App Protect moduleEnabling WAF through Controller ADC

In the modern symphony of business, each section-from the technical to the managerial-must play in harmony. Authors Ron Itelman and Juan Cruz Viotti introduce a bold methodology to synchronize your business and technical teams, transforming them into a single, high-performing unit. Misalignment between business and technical teams halts innovation. You'll learn how to transcend the root causes of project failure-the ambiguity, knowledge gaps, and blind spots that lead to wasted efforts. The unifying methodology in this book will teach you these alignment tools and more: The four facets of data products: A simple blueprint that encapsulates data and business logic helps eliminate the most common causes of wasted time and misunderstanding The concept compass: An easy way to identify the biggest sources of misalignment Success spectrums: Define the required knowledge and road map your team needs to achieve success JSON Schema: Leverage JSON and JSON Schema to technically implement the strategy at scale, including extending JSON Schema with custom keywords, understanding JSON Schema annotations, and hosting your own schema registry Data hygiene: Learn how to design high-quality datasets aligned with creating real business value, and protect your organization from the most common sources of pain

An understanding of psychologyspecifically the psychology behind how users behave and interact with digital interfacesis perhaps the single most valuable nondesign skill a designer can have. The most elegant design can fail if it forces users to conform to the design rather than working within the blueprint of how humans perceive and process the world around them. This practical guide explains how you can apply key principles in psychology to build products and experiences that are more intuitive and human-centered. Author Jon Yablonski deconstructs familiar apps and experiences to provide clear examples of how UX designers can build experiences that adapt to how users perceive and process digital interfaces.Youll learn:How aesthetically pleasing design creates positive responsesThe principles from psychology most useful for designersHow these psychology principles relate to UX heuristicsPredictive models including Fittss law, Jakobs law, and Hicks lawEthical implications of using psychology in designA framework for applying these principles

Cloud native security isn't a game for individual players. It requires team collaboration with a platform that can help cloud security engineers, developers, and operations people do their best work. That's what the cloud native application protection platform (CNAPP) delivers. With this practical guide, you'll learn how CNAPP can help you consolidate security through DevSecOps across cloud native technologies, practices, and application lifecycles. Through real-life attack scenarios, authors Russ Miles, Steve Giguere, and Taylor Smith help you explore how CNAPP not only mitigates multidimensional threats, but also reduces complexity and helps your team stay one step ahead of attackers. CNAPP provides a holistic approach to your cloud native development across identities, workloads, networks, and infrastructure. With this book, you will: Examine threats to different parts of the cloud native stack, including pipelines, supply chains, infrastructure, workloads, and applications Learn what CNAPP is and how it enables the context-sharing and collaboration necessary to secure your applications from development to runtime Assess your own attack surface from a code and runtime standpoint Identify blind spots in your existing cloud native security coverage Leverage CNAPP to achieve a holistic, collaborative security environment

With the massive adoption of microservices, operators and developers face far more complexity in their applications today. Service meshes can help you manage this problem by providing a unified control plane to secure, manage, and monitor your entire network. This practical guide shows you how the Linkerd service mesh enables cloud-native developers--including platform and site reliability engineers--to solve the thorny issue of running distributed applications in Kubernetes. Jason Morgan and Flynn draw on their years of experience at Buoyant--the creators of Linkerd--to demonstrate how this service mesh can help ensure that your applications are secure, observable, and reliable. You'll understand why Linkerd, the original service mesh, can still claim the lowest time to value of any mesh option available today. Learn how Linkerd works and which tasks it can help you accomplish Install and configure Linkerd in an imperative and declarative manner Secure interservice traffic and set up secure multicluster links Launch a zero trust authorization strategy in Kubernetes clusters Organize services in Linkerd to override error codes, set custom retries, and create timeouts Use Linkerd to manage progressive delivery and pair this service mesh with the ingress of your choice

Software as a service (SaaS) is on the path to becoming the de facto model for building, delivering, and operating software solutions. Adopting the multi-tenant model of SaaS requires builders to take on a broad range of new architecture, implementation, and operational challenges. How data is stored, how resources are isolated, how tenants are authenticated, how microservices are built--these are all examples of areas that builders must consider when designing and creating SaaS offerings. This practical book equips SaaS builders and architects with a collection of patterns, strategies, and insights to help you bridge these technical and business challenges. Tod Golding, a global SaaS lead at AWS, provides you with an end-to-end view of SaaS architecture and development techniques for addressing the unique blend of challenges associated with building a robust SaaS solution that realizes its full potential.

Decentralized finance (DeFi) is a rapidly growing field in fintech, having grown from $700 million to $100 billion over the past three years alone. But the lack of reliable information makes this area both risky and murky. In this practical book, experienced securities attorney Alexandra Damsker explains DeFi's role in both blockchain and finance. Ideal for developers looking to build decentralized applications (DApps), this book compares DeFi to traditional bank-led fintech and explains why DeFi is exploding in interest and popularity. You'll explore the growing array of DApps and platforms in various categories, including their benefits and drawbacks, and learn how DeFi tools work together from the perspective of both users and developers. With this book, you will: Learn how DeFi fits into the blockchain and fintech worlds Understand why it's important to move beyond the banking system Explore the tools for building a useful, functional DeFi application Learn the risks, benefits, regulatory concerns, and unresolved issues in this nascent and fast-growing industry See which technologies are well-positioned to be incorporated into DeFi blockchains in the near future Assess your own risk level to determine which strategies are most appropriate

Maverick Scientist is the memoir of Forrest Mims, who forged a distinguished scientific career despite having no academic training in science. Named one of the "50 Best Brains in Science" by Discover magazine, Forrest shares what sparked his childhood curiosity and relates a lifetime of improbable, dramatic, and occasionally outright dangerous experiences in the world of science. At thirteen he invented a new method of rocket control. At seventeen he designed and built an analog computer that could translate Russian into English and that the Smithsonian collected as an example of an early hobby computer. While majoring in government at Texas A&M University, Forrest created a hand-held, radar-like device to help guide the blind. And during his military service, he had to be given special clearance to do top secret laser research at the Air Force Weapons Lab. Why? Because while he lacked the required engineering degree, they wanted his outside-the-box thinking on the project. He went on to co-found MITS, Inc., producer of the first commercially successful personal computer, wrote a series of electronics books for Radio Shack that sold more than seven million copies, and designed the music synthesizer circuit that became known as the infamous Atari Punk Console. All this came before he started consulting for NASA's Goddard Space Flight Center, and NOAA's famous Mauna Loa Observatory, and earning the prestigious Rolex Award. This intimate portrait of a self-made scientist shares a revelatory look inside the scientific community, and tells the story of a lifelong learner who stood by his convictions even when pressured by the establishment to get in line with conventional wisdom. With dozens of personal photos and illustrations, Maverick Scientist serves as proof that to be a scientist, you simply need to do science.

With this book, Chris Fregly, Antje Barth, and Shelbee Eigenbrode from AWS help CTOs, ML practitioners, application developers, business analysts, data engineers, and data scientists find practical ways to use this exciting new technology.

乌龟提杰要跳。乌龟如何跳？。这个故事教我们 如何不停试验到成功。wū guī tí jié yào tiào 。 wū guī rú hé tiào ？ zhè ge gù shi jiào wǒ men rú hé bù tíng shì yàn dào chéng gōng 。 A Turtle named TJ wants to jump. How can a turtle jump? This story teaches us all how to keep trying until we succeed.

后记 "知更鸟的第一次飞行 "是要飞但怕飞的故事。 知更鸟克服恐惧并学会飞翔！这个寓言帮助我们每个人找到自己的翅膀。 "Robin's First Flight" is the story of wanting to fly but afraid to try. Robin overcomes fear and learns to soar! This fable helps each of us find our own wings.

Traditional data architecture patterns are severely limited. To use these patterns, you have to ETL data into each tool--a cost-prohibitive process for making warehouse features available to all of your data. The lack of flexibility with these patterns requires you to lock into a set of priority tools and formats, which creates data silos and data drift. This practical book shows you a better way. Apache Iceberg provides the capabilities, performance, scalability, and savings that fulfill the promise of an open data lakehouse. By following the lessons in this book, you'll be able to achieve interactive, batch, machine learning, and streaming analytics with this high-performance open source format. Authors Tomer Shiran, Jason Hughes, and Alex Merced from Dremio show you how to get started with Iceberg. With this book, you'll learn: The architecture of Apache Iceberg tables What happens under the hood when you perform operations on Iceberg tables How to further optimize Iceberg tables for maximum performance How to use Iceberg with popular data engines such as Apache Spark, Apache Flink, and Dremio Discover why Apache Iceberg is a foundational technology for implementing an open data lakehouse.

Gain the valuable skills and techniques you need to accelerate the delivery of machine learning solutions. With this practical guide, data scientists, ML engineers, and their leaders will learn how to bridge the gap between data science and Lean product delivery in a practical and simple way. David Tan, Ada Leung, and Dave Colls show you how to apply time-tested software engineering skills and Lean product delivery practices to reduce toil and waste, shorten feedback loops, and improve your team's flow when building ML systems and products. Based on the authors' experience across multiple real-world data and ML projects, the proven techniques in this book will help your team avoid common traps in the ML world, so you can iterate and scale more quickly and reliably. You'll learn how to overcome friction and experience flow when delivering ML solutions. You'll also learn how to: Write automated tests for ML systems, containerize development environments, and refactor problematic codebases Apply MLOps and CI/CD practices to accelerate experimentation cycles and improve reliability of ML solutions Apply Lean delivery and product practices to improve your odds of building the right product for your users Identify suitable team structures and intra- and inter-team collaboration techniques to enable fast flow, reduce cognitive load, and scale ML within your organization

If programming is magic then web scraping is surely a form of wizardry. By writing a simple automated program, you can query web servers, request data, and parse it to extract the information you need. The expanded edition of this practical book not only introduces you web scraping, but also serves as a comprehensive guide to scraping almost every type of data from the modern web.Part I focuses on web scraping mechanics: using Python to request information from a web server, performing basic handling of the servers response, and interacting with sites in an automated fashion. Part II explores a variety of more specific tools and applications to fit any web scraping scenario youre likely to encounter.Parse complicated HTML pagesDevelop crawlers with the Scrapy frameworkLearn methods to store data you scrapeRead and extract data from documentsClean and normalize badly formatted dataRead and write natural languagesCrawl through forms and loginsScrape JavaScript and crawl through APIsUse and write image-to-text softwareAvoid scraping traps and bot blockersUse scrapers to test your website

How can you make sense of the complex IoT landscape? With dozens of components ranging from devices to metadata about the devices, it's easy to get lost among the possibilities. But it's not impossible if you have the right guide to help you navigate all the complexities. This practical book shows developers, architects, and IT managers how to build IoT solutions on Azure. Author Blaize Stewart presents a comprehensive view of the IoT landscape. You'll learn about devices, device management at scale, and the tools Azure provides for building globally distributed systems. You'll also explore ways to organize data by choosing the appropriate dataflow and data storage technologies. The final chapters examine data consumption and solutions for delivering data to consumers with Azure. Get the architectural guidance you need to create holistic solutions with devices, data, and everything in between. This book helps you: Meet the demands of an IoT solution with Azure-provided functionality Use Azure to create complete scalable and secure IoT systems Understand how to articulate IoT architecture and solutions Guide conversations around common problems that IoT applications solve Select the appropriate technologies in the Azure space to build IoT applications

If you were handed two different but related sets of data, what tools would you use to find the matches? What if all you had was SQL SELECT access to a database? In this practical book, author Jim Lehmer provides best practices, techniques, and tricks to help you import, clean, match, score, and think about heterogeneous data using SQL. DBAs, programmers, business analysts, and data scientists will learn how to identify and remove duplicates, parse strings, extract data from XML and JSON, generate SQL using SQL, regularize data and prepare datasets, and apply data quality and ETL approaches for finding the similarities and differences between various expressions of the same data. Full of real-world techniques, the examples in the book contain working code. You'll learn how to: Identity and remove duplicates in two different datasets using SQL Regularize data and achieve data quality using SQL Extract data from XML and JSON Generate SQL using SQL to increase your productivity Prepare datasets for import, merging, and better analysis using SQL Report results using SQL Apply data quality and ETL approaches to finding similarities and differences between various expressions of the same data

This practical guide provides a collection of techniques and best practices that are generally overlooked in most data engineering and data science pedagogy. A common misconception is that great data scientists are experts in the "big themes" of the discipline--machine learning and programming. But most of the time, these tools can only take us so far. In practice, the smaller tools and skills really separate a great data scientist from a not-so-great one. Taken as a whole, the lessons in this book make the difference between an average data scientist candidate and a qualified data scientist working in the field. Author Daniel Vaughan has collected, extended, and used these skills to create value and train data scientists from different companies and industries. With this book, you will: Understand how data science creates value Deliver compelling narratives to sell your data science project Build a business case using unit economics principles Create new features for a ML model using storytelling Learn how to decompose KPIs Perform growth decompositions to find root causes for changes in a metric Daniel Vaughan is head of data at Clip, the leading paytech company in Mexico. He's the author of Analytical Skills for AI and Data Science (O'Reilly).

Explore the theory and practice of designing and writing serverless applications using examples from the Knative project. With this practical guide, mid-level to senior application developers and team managers will learn when and why to target serverless platforms when developing microservices or applications. Along the way, you'll also discover warning signs that suggest why serverless might cause you more trouble than joy. Drawing on author Evan Anderson's 15 years of experience developing and maintaining applications in the cloud--and more than six years of experience with serverless platforms at scale--this book acts as your guide into the high-velocity world of serverless application development. You'll come to appreciate why Knative is the most widely adopted open source serverless platform available. With this book, you will: Learn what serverless is, how it works, and why teams are adopting it Understand the benefits of Knative for cloud native development teams Learn how to build a serverless application on Knative Explore the challenges serverless introduces for debugging and the tools that can help improve it Learn why event-driven architecture and serverless compute are complementary but distinct Understand when a serverless approach might not be the right system design

"The adoption of serverless is on the rise, but until now, little guidance has been available for development teams that want to apply this technology on AWS. This definitive guide is packed with architectural, security, and data best practices and patterns for architects and engineers who want to build reliable enterprise-scale serverless solutions. Sheen Brisals, an AWS Serverless Hero, and Luke Hedger, an AWS Community Builder, outline the serverless adoption requirements for an enterprise, examine the development tools your team needs, and explain in depth the nuances of testing event-driven and distributed serverless services. You'll gain practical guidance for keeping up with change and learn how to build serverless solutions with sustainability in mind. Examine the serverless technology ecosystem and AWS services needed to develop serverless applications; learn the approach and preparation required for a successful serverless adoption in an enterprise; learn serverless architectures and implementation patterns; design, develop, and test distributed serverless microservices on AWS cloud; apply security best practices while building serverless solutions; identify and adapt the implementation patterns for your particular use case; incorporate the necessary measures for observable serverless applications; implement sustainable serverless applications in the cloud "--

Trillions of lines of code help us in our lives, companies, and organizations. But just a single software cybersecurity vulnerability can stop entire companies from doing business and cause billions of dollars in revenue loss and business recovery. Securing the creation and deployment of software, also known as software supply chain security, goes well beyond the software development process. This practical book gives you a comprehensive look at security risks and identifies the practical controls you need to incorporate into your end-to-end software supply chain. Author Cassie Crossley demonstrates how and why everyone involved in the supply chain needs to participate if your organization is to improve the security posture of its software, firmware, and hardware. With this book, you'll learn how to: Pinpoint the cybersecurity risks in each part of your organization's software supply chain Find the cybersecurity frameworks and resources that can improve security Identify the roles that participate in the supply chain--including IT, development, operations, manufacturing, and procurement Design initiatives and controls for each part of the supply chain using existing frameworks and references Evaluate third-party risk in your supply chain

Microservices can be a very effective approach for delivering value to your organization and to your customers. If you get them right, microservices help you to move fast, making changes to small parts of your system hundreds of times a day. But get them wrong and microservices just make everything more complicated. In this book, technical strategist Sarah Wells provides practical, in-depth advice for moving to microservices. Having built her first microservices architecture in 2013 for the Financial Times, Sarah discusses the approaches you need to take from the start, and explains the potential traps most likely to trip you up. You'll also learn how to maintain the architecture as your systems mature while minimizing the time you spend on support and maintenance. With this book, you will: Learn the impact of microservices on software development patterns and practices Identify the organizational changes you need to make to successfully build and operate this architecture Determine the steps you must take before you move to microservices Understand the traps to avoid when you create a microservices architecture--and learn how to recover if you fall into one

Kubernetes is becoming the de-facto standard for container orchestration and distributed applications management across a microservices framework. With this practical cookbook, youll learn hands-on recipes for automating the deployment, scaling, and operations of application containers across clusters of hosts.The book's easy-lookup problem-solution-discussion format helps you find the detailed answers you needquickly. Kubernetes lets you deploy your applications quickly and predictably, so you can efficiently respond to customer demand. This cookbook, ideal for developers and system administers alike, provides the essential knowledge you need to get there.Youll find recipes for:Kubernetes installationKubernetes API, API groupsApplication primitivesMonitoringTroubleshooting

Implementing and designing systems that make suggestions to users are among the most popular and essential machine learning applications available. Whether you want customers to find the most appealing items at your online store, videos to enrich and entertain them, or news they need to know, recommendation systems (RecSys) provide the way. In this practical book, authors Bryan Bischof and Hector Yee illustrate the core concepts and examples to help you create a RecSys for any industry or scale. You'll learn the math, ideas, and implementation details you need to succeed. This book includes the RecSys platform components, relevant MLOps tools in your stack, plus code examples and helpful suggestions in PySpark, SparkSQL, FastAPI, Weights & Biases, and Kafka. You'll learn: The data essential for building a RecSys How to frame your data and business as a RecSys problem Ways to evaluate models appropriate for your system Methods to implement, train, test, and deploy the model you choose Metrics you need to track to ensure your system is working as planned How to improve your system as you learn more about your users, products, and business case