Practical Serverless Applications With Aws Harnessing The Power Of Serverless Cloud Applications Livre
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Practical Serverless Applications with AWS
This comprehensive guide is your gateway to unlocking the potential of serverless computing on the AWS platform. Whether you're a seasoned developer or just starting your cloud journey, this book is your essential companion. Dive into the world of serverless architecture as we demystify AWS services like AWS Lambda, API Gateway, DynamoDB, and more. From design principles to deployment strategies, we'll equip you with the knowledge and hands-on experience to build robust, scalable, and cost-effective serverless applications. Practical Serverless Applications with AWS is tailored for anyone eager to grasp the fundamentals of AWS services for constructing serverless applications. Whether you're a seasoned developer or just starting your cloud journey or a student delving into the world of cloud computing, or a freelance developer seeking to expand your skill set, this resource is your gateway to mastering serverless application development on AWS. With a practical approach and real-world examples, this book caters to a diverse audience keen on harnessing the power of serverless computing. From fledgling enthusiasts to seasoned practitioners, this book is your indispensable tool for embarking on a transformative journey into serverless architecture with AWS. Get ready to revolutionize your approach to app development in the cloud! You Will Learn: The fundamentals of AWS empowering you to navigate the AWS environment with confidence. Both frontend and backend development services in the context of building serverless applications, enabling you to create robust and scalable solutions. Many AWS services and how to use them for building serverless applications, ensuring efficient and effective implementation. data engineering and DevOps best practices within the AWS ecosystem, providing a well-rounded skillset for holistic app development. how to build a complex serverless application, allowing you to apply your knowledge in a practical, hands-on way. Who It's for: web developers, cloud and data engineering who are looking to improve their cloud-native app development skills
Serverless Programming Cookbook
Author: Heartin Kanikathottu
language: en
Publisher: Packt Publishing Ltd
Release Date: 2019-01-31
Build, secure, and deploy real-world serverless applications in AWS and peek into the serverless cloud offerings from Azure, Google Cloud, and IBM Cloud Key FeaturesBuild serverless applications with AWS Lambda, AWS CloudFormation and AWS CloudWatchPerform data analytics and natural language processing(NLP)on the AWS serverless platformExplore various design patterns and best practices involved in serverless computingBook Description Managing physical servers will be a thing of the past once you’re able to harness the power of serverless computing. If you’re already prepped with the basics of serverless computing, Serverless Programming Cookbook will help you take the next step ahead. This recipe-based guide provides solutions to problems you might face while building serverless applications. You'll begin by setting up Amazon Web Services (AWS), the primary cloud provider used for most recipes. The next set of recipes will cover various components to build a Serverless application including REST APIs, database, user management, authentication, web hosting, domain registration, DNS management, CDN, messaging, notifications and monitoring. The book also introduces you to the latest technology trends such as Data Streams, Machine Learning and NLP. You will also see patterns and practices for using various services in a real world application. Finally, to broaden your understanding of Serverless computing, you'll also cover getting started guides for other cloud providers such as Azure, Google Cloud Platform and IBM cloud. By the end of this book, you’ll have acquired the skills you need to build serverless applications efficiently using various cloud offerings. What you will learnServerless computing in AWS and explore services with other cloudsDevelop full-stack apps with API Gateway, Cognito, Lambda and DynamoDBWeb hosting with S3, CloudFront, Route 53 and AWS Certificate ManagerSQS and SNS for effective communication between microservices Monitoring and troubleshooting with CloudWatch logs and metrics Explore Kinesis Streams, Amazon ML models and Alexa Skills KitWho this book is for For developers looking for practical solutions to common problems while building a serverless application, this book provides helpful recipes. To get started with this intermediate-level book, knowledge of basic programming is a must.
AI as a Service
AI as a Service is a practical handbook to building and implementing serverless AI applications, without bogging you down with a lot of theory. Instead, you’ll find easy-to-digest instruction and two complete hands-on serverless AI builds in this must-have guide! Summary Companies everywhere are moving everyday business processes over to the cloud, and AI is increasingly being given the reins in these tasks. As this massive digital transformation continues, the combination of serverless computing and AI promises to become the de facto standard for business-to-consumer platform development—and developers who can design, develop, implement, and maintain these systems will be in high demand! AI as a Service is a practical handbook to building and implementing serverless AI applications, without bogging you down with a lot of theory. Instead, you’ll find easy-to-digest instruction and two complete hands-on serverless AI builds in this must-have guide! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Cloud-based AI services can automate a variety of labor intensive business tasks in areas such as customer service, data analysis, and financial reporting. The secret is taking advantage of pre-built tools like Amazon Rekognition for image analysis or AWS Comprehend for natural language processing. That way, there’s no need to build expensive custom software. Artificial Intelligence (AI), a machine’s ability to learn and make predictions based on patterns it identifies, is already being leveraged by businesses around the world in areas like targeted product recommendations, financial forecasting and resource planning, customer service chatbots, healthcare diagnostics, data security, and more. With the exciting combination of serverless computing and AI, software developers now have enormous power to improve their businesses’ existing systems and rapidly deploy new AI-enabled platforms. And to get on this fast-moving train, you don’t have to invest loads of time and effort in becoming a data scientist or AI expert, thanks to cloud platforms and the readily available off-the-shelf cloud-based AI services! About the book AI as a Service is a fast-paced guide to harnessing the power of cloud-based solutions. You’ll learn to build real-world apps—such as chatbots and text-to-speech services—by stitching together cloud components. Work your way from small projects to large data-intensive applications. What's inside - Apply cloud AI services to existing platforms - Design and build scalable data pipelines - Debug and troubleshoot AI services - Start fast with serverless templates About the reader For software developers familiar with cloud basics. About the author Peter Elger and Eóin Shanaghy are founders and CEO/CTO of fourTheorem, a software solutions company providing expertise on architecture, DevOps, and machine learning. Table of Contents PART 1 - FIRST STEPS 1 A tale of two technologies 2 Building a serverless image recognition system, part 1 3 Building a serverless image recognition system, part 2 PART 2 - TOOLS OF THE TRADE 4 Building and securing a web application the serverless way 5 Adding AI interfaces to a web application 6 How to be effective with AI as a Service 7 Applying AI to existing platforms PART 3 - BRINGING IT ALL TOGETHER 8 Gathering data at scale for real-world AI 9 Extracting value from large data sets with AI