Lambda Update
Author:
Publisher:
Published: 1993
Total Pages: 28
ISBN-13:
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Programming AWS Lambda
Author: John Chapin
Publisher: "O'Reilly Media, Inc."
Published: 2020-03-18
Total Pages: 290
ISBN-13: 1492041009
DOWNLOAD EBOOKServerless revolutionizes the way organizations build and deploy software. With this hands-on guide, Java engineers will learn how to use their experience in the new world of serverless computing. You’ll discover how this cloud computing execution model can drastically decrease the complexity in developing and operating applications while reducing costs and time to market. Engineering leaders John Chapin and Mike Roberts guide you through the process of developing these applications using AWS Lambda, Amazon’s event-driven, serverless computing platform. You’ll learn how to prepare the development environment, program Lambda functions, and deploy and operate your serverless software. The chapters include exercises to help you through each aspect of the process. Get an introduction to serverless, functions as a service, and AWS Lambda Learn how to deploy working Lambda functions to the cloud Program Lambda functions and learn how the Lambda platform integrates with other AWS services Build and package Java-based Lambda code and dependencies Create serverless applications by building a serverless API and data pipeline Test your serverless applications using automated techniques Apply advanced techniques to build production-ready applications Understand both the gotchas and new opportunities of serverless architecture
Modelling and implementation of a microscopic traffic simulation system
Author: Johannes Brügmann
Publisher: Logos Verlag Berlin GmbH
Published: 2015-11-16
Total Pages: 242
ISBN-13: 3832541330
DOWNLOAD EBOOKThis thesis presents the foundations, the initial state, and the progress made in modelling and implementing a real-world and real-time online microscopic traffic simulation system for highway traffic. To successfully model and implement such a simulation system, this thesis recommends the use of a number of formal methods applied at the right places. As part of the recommendation, this thesis proposes a microscopic traffic simulation system. To explore the feasibility and the potential of the recommended methods, it observes and examines the proposed system from multiple views and under various different aspects. As part of the examination, this thesis provides a (semi-)formal specification, a model implementation, an implementation of a productive system, and the benefits that result from validating such a system. The results and any proper application of them have the potential to increase the reliability and the trustworthiness for any future implementation of the proposed simulation system. The presented results additionally motivate to apply the proposed approach to similar simulation systems. The thesis concludes the presentation of the results with some considerations for future implementations.
Pipeline as Code
Author: Mohamed Labouardy
Publisher: Simon and Schuster
Published: 2021-11-23
Total Pages: 750
ISBN-13: 163835037X
DOWNLOAD EBOOKStart thinking about your development pipeline as a mission-critical application. Discover techniques for implementing code-driven infrastructure and CI/CD workflows using Jenkins, Docker, Terraform, and cloud-native services. In Pipeline as Code, you will master: Building and deploying a Jenkins cluster from scratch Writing pipeline as code for cloud-native applications Automating the deployment of Dockerized and Serverless applications Containerizing applications with Docker and Kubernetes Deploying Jenkins on AWS, GCP and Azure Managing, securing and monitoring a Jenkins cluster in production Key principles for a successful DevOps culture Pipeline as Code is a practical guide to automating your development pipeline in a cloud-native, service-driven world. You’ll use the latest infrastructure-as-code tools like Packer and Terraform to develop reliable CI/CD pipelines for numerous cloud-native applications. Follow this book's insightful best practices, and you’ll soon be delivering software that’s quicker to market, faster to deploy, and with less last-minute production bugs. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Treat your CI/CD pipeline like the real application it is. With the Pipeline as Code approach, you create a collection of scripts that replace the tedious web UI wrapped around most CI/CD systems. Code-driven pipelines are easy to use, modify, and maintain, and your entire CI pipeline becomes more efficient because you directly interact with core components like Jenkins, Terraform, and Docker. About the book In Pipeline as Code you’ll learn to build reliable CI/CD pipelines for cloud-native applications. With Jenkins as the backbone, you’ll programmatically control all the pieces of your pipeline via modern APIs. Hands-on examples include building CI/CD workflows for distributed Kubernetes applications, and serverless functions. By the time you’re finished, you’ll be able to swap manual UI-based adjustments with a fully automated approach! What's inside Build and deploy a Jenkins cluster on scale Write pipeline as code for cloud-native applications Automate the deployment of Dockerized and serverless applications Deploy Jenkins on AWS, GCP, and Azure Grasp key principles of a successful DevOps culture About the reader For developers familiar with Jenkins and Docker. Examples in Go. About the author Mohamed Labouardy is the CTO and co-founder of Crew.work, a Jenkins contributor, and a DevSecOps evangelist. Table of Contents PART 1 GETTING STARTED WITH JENKINS 1 What’s CI/CD? 2 Pipeline as code with Jenkins PART 2 OPERATING A SELF-HEALING JENKINS CLUSTER 3 Defining Jenkins architecture 4 Baking machine images with Packer 5 Discovering Jenkins as code with Terraform 6 Deploying HA Jenkins on multiple cloud providers PART 3 HANDS-ON CI/CD PIPELINES 7 Defining a pipeline as code for microservices 8 Running automated tests with Jenkins 9 Building Docker images within a CI pipeline 10 Cloud-native applications on Docker Swarm 11 Dockerized microservices on K8s 12 Lambda-based serverless functions PART 4 MANAGING, SCALING, AND MONITORING JENKINS 13 Collecting continuous delivery metrics 14 Jenkins administration and best practices
AIDS and the Law
Author: Allan H. Terl
Publisher: Taylor & Francis
Published: 1992
Total Pages: 212
ISBN-13: 9781560322191
DOWNLOAD EBOOKIntended for those who have no legal training, but who are interested in the legal aspects of AIDS, this work relates how AIDS and the human immuno- deficiency virus HIV have affected some legal isues. Discrimination permeates the issue and specific cases are cited.
Compiler Construction
Author: Görel Hedin
Publisher: Springer
Published: 2003-07-01
Total Pages: 347
ISBN-13: 3540365796
DOWNLOAD EBOOKThis book constitutes the refereed proceedings of the 12th International Conference on Compiler Construction, CC 2003, held in Warsaw, Poland, in April 2003. The 20 revised full regular papers and one tool demonstration paper presented together with two invited papers were carefully reviewed and selected from 83 submissions. The papers are organized in topical sections on register allocation, language constructs and their implementation, type analysis, Java, pot pourri, and optimization.
A Concise Introduction to Machine Learning
Author: A.C. Faul
Publisher: CRC Press
Published: 2019-08-01
Total Pages: 335
ISBN-13: 1351204742
DOWNLOAD EBOOKThe emphasis of the book is on the question of Why – only if why an algorithm is successful is understood, can it be properly applied, and the results trusted. Algorithms are often taught side by side without showing the similarities and differences between them. This book addresses the commonalities, and aims to give a thorough and in-depth treatment and develop intuition, while remaining concise. This useful reference should be an essential on the bookshelves of anyone employing machine learning techniques. The author's webpage for the book can be accessed here.
Scala for Machine Learning
Author: Patrick R. Nicolas
Publisher: Packt Publishing Ltd
Published: 2017-09-26
Total Pages: 740
ISBN-13: 178712620X
DOWNLOAD EBOOKLeverage Scala and Machine Learning to study and construct systems that can learn from data About This Book Explore a broad variety of data processing, machine learning, and genetic algorithms through diagrams, mathematical formulation, and updated source code in Scala Take your expertise in Scala programming to the next level by creating and customizing AI applications Experiment with different techniques and evaluate their benefits and limitations using real-world applications in a tutorial style Who This Book Is For If you're a data scientist or a data analyst with a fundamental knowledge of Scala who wants to learn and implement various Machine learning techniques, this book is for you. All you need is a good understanding of the Scala programming language, a basic knowledge of statistics, a keen interest in Big Data processing, and this book! What You Will Learn Build dynamic workflows for scientific computing Leverage open source libraries to extract patterns from time series Write your own classification, clustering, or evolutionary algorithm Perform relative performance tuning and evaluation of Spark Master probabilistic models for sequential data Experiment with advanced techniques such as regularization and kernelization Dive into neural networks and some deep learning architecture Apply some basic multiarm-bandit algorithms Solve big data problems with Scala parallel collections, Akka actors, and Apache Spark clusters Apply key learning strategies to a technical analysis of financial markets In Detail The discovery of information through data clustering and classification is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, engineering design, logistics, manufacturing, and trading strategies, to detection of genetic anomalies. The book is your one stop guide that introduces you to the functional capabilities of the Scala programming language that are critical to the creation of machine learning algorithms such as dependency injection and implicits. You start by learning data preprocessing and filtering techniques. Following this, you'll move on to unsupervised learning techniques such as clustering and dimension reduction, followed by probabilistic graphical models such as Naive Bayes, hidden Markov models and Monte Carlo inference. Further, it covers the discriminative algorithms such as linear, logistic regression with regularization, kernelization, support vector machines, neural networks, and deep learning. You'll move on to evolutionary computing, multibandit algorithms, and reinforcement learning. Finally, the book includes a comprehensive overview of parallel computing in Scala and Akka followed by a description of Apache Spark and its ML library. With updated codes based on the latest version of Scala and comprehensive examples, this book will ensure that you have more than just a solid fundamental knowledge in machine learning with Scala. Style and approach This book is designed as a tutorial with hands-on exercises using technical analysis of financial markets and corporate data. The approach of each chapter is such that it allows you to understand key concepts easily.
Network Programming with Go
Author: Adam Woodbeck
Publisher: No Starch Press
Published: 2021-03-25
Total Pages: 392
ISBN-13: 1718500882
DOWNLOAD EBOOKNetwork Programming with Go teaches you how to write clean, secure network software with the programming language designed to make it seem easy. Build simple, reliable, network software Combining the best parts of many other programming languages, Go is fast, scalable, and designed for high-performance networking and multiprocessing. In other words, it’s perfect for network programming. Network Programming with Go will help you leverage Go to write secure, readable, production-ready network code. In the early chapters, you’ll learn the basics of networking and traffic routing. Then you’ll put that knowledge to use as the book guides you through writing programs that communicate using TCP, UDP, and Unix sockets to ensure reliable data transmission. As you progress, you’ll explore higher-level network protocols like HTTP and HTTP/2 and build applications that securely interact with servers, clients, and APIs over a network using TLS. You'll also learn: Internet Protocol basics, such as the structure of IPv4 and IPv6, multicasting, DNS, and network address translation Methods of ensuring reliability in socket-level communications Ways to use handlers, middleware, and multiplexers to build capable HTTP applications with minimal code Tools for incorporating authentication and encryption into your applications using TLS Methods to serialize data for storage or transmission in Go-friendly formats like JSON, Gob, XML, and protocol buffers Ways of instrumenting your code to provide metrics about requests, errors, and more Approaches for setting up your application to run in the cloud (and reasons why you might want to) Network Programming with Go is all you’ll need to take advantage of Go’s built-in concurrency, rapid compiling, and rich standard library. Covers Go 1.15 (Backward compatible with Go 1.12 and higher)
Mastering AWS Serverless
Author: Miguel A. Calles
Publisher: BPB Publications
Published: 2024-04-29
Total Pages: 532
ISBN-13: 9355516118
DOWNLOAD EBOOKMaster the art of designing and creating serverless architectures and applications KEY FEATURES ● Learn to create serverless applications that leverage serverless functions, databases, data stores, and application programming interfaces. ● Learn the serverless concepts needed to provide serverless solutions for websites, mobile apps, APIs, backends, notifications, Artificial Intelligence, and Machine Learning. ● Create serverless, event-driven architectures and designs through hands-on exercises throughout the book. DESCRIPTION Serverless computing is relatively new compared to server-based designs. Amazon Web Services launched its serverless computing offering by introducing AWS Lambda. Lambda has introduced a revolution in cloud computing, where servers could be excluded from architectures, and events could be used to trigger other resources. The AWS serverless services have allowed developers, startups, and large enterprises to focus more on developing and creating features and spend less time managing and securing servers. It covers key concepts like serverless architecture and AWS services. You will learn to create event-driven apps, launch websites, and build APIs with hands-on exercises. The book will explore storage options and data processing, including serverless Machine Learning. Discover best practices for architecture, security, and cost optimization. The book will cover advanced topics like AWS SAM and Lambda layers for complex workflows. Finally, get guidance on creating new serverless apps and migrating existing ones. The knowledge gained from this book will help you create a serverless website, application programming interface, and backend. In addition, the information covered in the book will help you process and analyze data using a serverless design. WHAT YOU WILL LEARN ● Creating a serverless website using Amazon S3 and CloudFront. ● Creating a serverless API using Amazon API Gateway. ● Create serverless functions with AWS Lambda. ● Save data using Amazon DynamoDB and Amazon S3. ● Perform authentication and authorization with Amazon Cognito. WHO THIS BOOK IS FOR The book targets professionals and students who want to gain experience in software development, cloud computing, web development, data processing, or Amazon Web Services. It is ideal for cloud architects, developers, and backend engineers seeking to leverage serverless services for scalable and cost-effective applications. TABLE OF CONTENTS 1. Introduction to AWS Serverless 2. Overview of Serverless Applications 3. Designing Serverless Architectures 4. Launching a Website 5. Creating an API 6. Saving and Using Data 7. Adding Authentication and Authorization 8. Processing Data using Automation and Machine Learning 9. Sending Notifications 10. Additional Automation Topics 11. Architecture Best Practices 12. Next Steps
