AWS Lambda Quick Start Guide PDF Download
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Author: Markus Klems
Publisher: Packt Publishing Ltd
ISBN: 1789340608
Category : Computers
Languages : en
Pages : 178
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Book Description
Discover techniques and tools for building serverless applications with AWS Lambda Key Features Learn to write, run, and deploy Lambda functions in the AWS cloud Make the most of AWS Lambda functions to build scalable and cost-efficient systems A practical guide to developing serverless services and applications in Node.js, Java, Python, and C# Book Description AWS Lambda is a part of AWS that lets you run your code without provisioning or managing servers. This enables you to deploy applications and backend services that operate with no upfront cost. This book gets you up to speed on how to build scalable systems and deploy serverless applications with AWS Lambda. The book starts with the fundamental concepts of AWS Lambda, and then teaches you how to combine your applications with other AWS services, such as AmazonAPI Gateway and DynamoDB. This book will also give a quick walk through on how to use the Serverless Framework to build larger applications that can structure code or autogenerate boilerplate code that can be used to get started quickly for increased productivity. Toward the end of the book, you will learn how to write, run, and test Lambda functions using Node.js, Java, Python, and C#. What you will learn Understand the fundamental concepts of AWS Lambda Get to grips with the Serverless Framework and how to create a serverless project Testing and debugging Lambda functions Create a stateful, serverless backend with DynamoDB Program AWS Lambda with Java, Python, and C# Program a lambda function with Node.js Who this book is for This book is primarily for IT architects and developers who want to build scalable systems and deploy serverless applications with AWS Lambda. No prior knowledge of AWS is necessary.
Author: Markus Klems
Publisher: Packt Publishing Ltd
ISBN: 1789340608
Category : Computers
Languages : en
Pages : 178
Get Book Here
Book Description
Discover techniques and tools for building serverless applications with AWS Lambda Key Features Learn to write, run, and deploy Lambda functions in the AWS cloud Make the most of AWS Lambda functions to build scalable and cost-efficient systems A practical guide to developing serverless services and applications in Node.js, Java, Python, and C# Book Description AWS Lambda is a part of AWS that lets you run your code without provisioning or managing servers. This enables you to deploy applications and backend services that operate with no upfront cost. This book gets you up to speed on how to build scalable systems and deploy serverless applications with AWS Lambda. The book starts with the fundamental concepts of AWS Lambda, and then teaches you how to combine your applications with other AWS services, such as AmazonAPI Gateway and DynamoDB. This book will also give a quick walk through on how to use the Serverless Framework to build larger applications that can structure code or autogenerate boilerplate code that can be used to get started quickly for increased productivity. Toward the end of the book, you will learn how to write, run, and test Lambda functions using Node.js, Java, Python, and C#. What you will learn Understand the fundamental concepts of AWS Lambda Get to grips with the Serverless Framework and how to create a serverless project Testing and debugging Lambda functions Create a stateful, serverless backend with DynamoDB Program AWS Lambda with Java, Python, and C# Program a lambda function with Node.js Who this book is for This book is primarily for IT architects and developers who want to build scalable systems and deploy serverless applications with AWS Lambda. No prior knowledge of AWS is necessary.
Author: Deepak Vohra
Publisher: Packt Publishing Ltd
ISBN: 1789340055
Category : Computers
Languages : en
Pages : 183
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Book Description
This book gets you started and gives you knowledge about AWS Fargate in order to successfully incorporate it in your ECS container application. Key Features Gives you a quick walk-through over the Amazon Elastic Container Services (ECS) Provides an in depth knowledge of the components that Amazon Fargate has to offer. Learn the practical aspects of Docker application development with a managed service Book Description Amazon Fargate is new launch type for the Amazon Elastic Container Service (ECS). ECS is an AWS service for Docker container orchestration. Docker is the de facto containerization framework and has revolutionized packaging and deployment of software. The introduction of Fargate has made the ECS platform serverless. The book takes you through how Amazon Fargate runs ECS services composed of tasks and Docker containers and exposes the containers to the user. Fargate has simplified the ECS platform. We will learn how Fargate creates an Elastic Network Interface (ENI) for each task and how auto scaling can be enabled for ECS tasks. You will also learn about using an IAM policy to download Docker images and send logs to CloudWatch. Finally, by the end of this book, you will have learned about how to use ECS CLI to create an ECS cluster and deploy tasks with Docker Compose. What you will learn Running Docker containers with a managed service Use Amazon ECS in Fargate launch mode Configure CloudWatch Logging with Fargate Use an IAM Role with Fargate Understand how ECS CLI is used with Fargate Learn how to use an Application Load Balancer with Fargate Learn about Auto Scaling with Fargate Who this book is for This book is for Docker users and developers who want to learn about the Fargate platform. Typical job roles for which the book is suitable are DevOps Architect, Docker Engineer, and AWS Cloud Engineer. Prior knowledge of AWS and ECS is helpful but not mandatory.
Author: Thomas Kurian Theakanath
Publisher: Packt Publishing Ltd
ISBN: 1800563574
Category : Computers
Languages : en
Pages : 318
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Book Description
A comprehensive guide to rolling out Datadog to monitor infrastructure and applications running in both cloud and datacenter environments Key FeaturesLearn Datadog to proactively monitor your infrastructure and cloud servicesUse Datadog as a platform for aggregating monitoring efforts in your organizationLeverage Datadog's alerting service to implement on-call and site reliability engineering (SRE) processesBook Description Datadog is an essential cloud monitoring and operational analytics tool which enables the monitoring of servers, virtual machines, containers, databases, third-party tools, and application services. IT and DevOps teams can easily leverage Datadog to monitor infrastructure and cloud services, and this book will show you how. The book starts by describing basic monitoring concepts and types of monitoring that are rolled out in a large-scale IT production engineering environment. Moving on, the book covers how standard monitoring features are implemented on the Datadog platform and how they can be rolled out in a real-world production environment. As you advance, you'll discover how Datadog is integrated with popular software components that are used to build cloud platforms. The book also provides details on how to use monitoring standards such as Java Management Extensions (JMX) and StatsD to extend the Datadog platform. Finally, you'll get to grips with monitoring fundamentals, learn how monitoring can be rolled out using Datadog proactively, and find out how to extend and customize the Datadog platform. By the end of this Datadog book, you will have gained the skills needed to monitor your cloud infrastructure and the software applications running on it using Datadog. What you will learnUnderstand monitoring fundamentals, including metrics, monitors, alerts, and thresholdsImplement core monitoring requirements using Datadog featuresExplore Datadog's integration with cloud platforms and toolsExtend Datadog using custom scripting and standards such as JMX and StatsDDiscover how proactive monitoring can be rolled out using various Datadog featuresUnderstand how Datadog can be used to monitor microservices in both Docker and Kubernetes environmentsGet to grips with advanced Datadog features such as APM and Security MonitoringWho this book is for This book is for DevOps engineers, site reliability engineers (SREs), IT Production engineers, software developers and architects, cloud engineers, system administrators, and anyone looking to monitor and visualize their infrastructure and applications with Datadog. Basic working knowledge of cloud and infrastructure is useful. Working experience of Linux distribution and some scripting knowledge is required to fully take advantage of the material provided in the book.
Author: Michael Bironneau
Publisher: Packt Publishing Ltd
ISBN: 1838551654
Category : Computers
Languages : en
Pages : 159
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Book Description
This quick start guide will bring the readers to a basic level of understanding when it comes to the Machine Learning (ML) development lifecycle, will introduce Go ML libraries and then will exemplify common ML methods such as Classification, Regression, and Clustering Key FeaturesYour handy guide to building machine learning workflows in Go for real-world scenariosBuild predictive models using the popular supervised and unsupervised machine learning techniquesLearn all about deployment strategies and take your ML application from prototype to production readyBook Description Machine learning is an essential part of today's data-driven world and is extensively used across industries, including financial forecasting, robotics, and web technology. This book will teach you how to efficiently develop machine learning applications in Go. The book starts with an introduction to machine learning and its development process, explaining the types of problems that it aims to solve and the solutions it offers. It then covers setting up a frictionless Go development environment, including running Go interactively with Jupyter notebooks. Finally, common data processing techniques are introduced. The book then teaches the reader about supervised and unsupervised learning techniques through worked examples that include the implementation of evaluation metrics. These worked examples make use of the prominent open-source libraries GoML and Gonum. The book also teaches readers how to load a pre-trained model and use it to make predictions. It then moves on to the operational side of running machine learning applications: deployment, Continuous Integration, and helpful advice for effective logging and monitoring. At the end of the book, readers will learn how to set up a machine learning project for success, formulating realistic success criteria and accurately translating business requirements into technical ones. What you will learnUnderstand the types of problem that machine learning solves, and the various approachesImport, pre-process, and explore data with Go to make it ready for machine learning algorithmsVisualize data with gonum/plot and GophernotesDiagnose common machine learning problems, such as overfitting and underfittingImplement supervised and unsupervised learning algorithms using Go librariesBuild a simple web service around a model and use it to make predictionsWho this book is for This book is for developers and data scientists with at least beginner-level knowledge of Go, and a vague idea of what types of problem Machine Learning aims to tackle. No advanced knowledge of Go (and no theoretical understanding of the math that underpins Machine Learning) is required.
Author: Mohamed Alibi
Publisher: Packt Publishing Ltd
ISBN: 1789538734
Category : Computers
Languages : en
Pages : 206
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Book Description
Configure Ansible and start coding YAML playbooks using the appropriate modules Key FeaturesCreate and use Ansible Playbook to script and organise management tasksBenefit from the Ansible community roles and modules to resolve complex and niche tasksWrite configuration management code to automate infrastructureBook Description Configuration Management (CM) tools help administrators reduce their workload. Ansible is one of the best Configuration Management tools, and can act as an orchestrator for managing other CMs. This book is the easiest way to learn how to use Ansible as an orchestrator and a Configuration Management tool. With this book, you will learn how to control and monitor computer and network infrastructures of any size,physical or virtual. You will begin by learning about the Ansible client-server architecture. To get started, you will set up and configure an Ansible server. You will then go through the major features of Ansible: Playbook and Inventory. Then, we will look at Ansible systems and network modules. You will then use Ansible to enable infrastructure automated configuration management, followed by best practices for using Ansible roles and community modules. Finally, you will explore Ansible features such as Ansible Vault, Ansible Containers, and Ansible plugins. What you will learnImplement Playbook YAML scripts and its capacities to simplify day-to-day tasksSetup Static and Dynamic InventoryUse Ansible predefined modules for Linux, Windows, networking, and virtualisation administrationOrganize and configure the host filesystem using storage and files modulesImplement Ansible to enable infrastructure automated configuration managementSimplify infrastructure administrationSearch and install new roles and enable them within AnsibleSecure your data using Ansible VaultWho this book is for This book is targeted at System Administrators and Network Administrators who want to use Ansible to automate an infrastructure. No knowledge of Ansible is required.
Author: Scalyr
Publisher: HitSubscribe
ISBN:
Category : Computers
Languages : en
Pages : 157
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Book Description
With the almost constant scaling of applications and environments, the need for good logging practices has likewise scaled exponentially. This book will help you understand the value of logging, the best practices for logs and introduce you to a number of tech stacks including languages and frameworks. It’s the ultimate resource for jumping into a new language or discovering new tricks in a familiar one. And you’ll learn the value that centralized logging brings on scale. All proceeds from this book will be donated by Scalyr to Girls Who Code
Author: Mario A. B. Capurso
Publisher: Mario Capurso
ISBN:
Category : Computers
Languages : en
Pages : 278
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Book Description
This work follows the 2021 curriculum of the Association for Computing Machinery for specialists in Data Sciences, with the aim of producing a manual that collects notions in a simplified form, facilitating a personal training path starting from specialized skills in Computer Science or Mathematics or Statistics. It has a bibliography with links to quality material but freely usable for your own training and contextual practical exercises. Part in a series of texts, it first summarizes the standard CRISP DM working methodology used in this work and in Data Science projects. As this text uses Orange for the application aspects, it describes its installation and widgets. The data modeling phase is considered from the perspective of machine learning by summarizing machine learning types, model types, problem types, and algorithm types. Advanced aspects associated with modeling are described such as loss and optimization functions such as gradient descent, techniques to analyze model performance such as Bootstrapping and Cross Validation. Deployment scenarios and the most common platforms are analyzed, with application examples. Mechanisms are proposed to automate machine learning and to support the interpretability of models and results such as Partial Dependence Plot, Permuted Feature Importance and others. The exercises are described with Orange and Python using the Keras/Tensorflow library. The text is accompanied by supporting material and it is possible to download the examples and the test data.
Author: Todd Montgomery
Publisher: John Wiley & Sons
ISBN: 1394171862
Category : Computers
Languages : en
Pages : 689
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Book Description
The latest edition of the official study guide for the AWS Advanced Networking certification specialty exam The newly revised second edition of the AWS Certified Advanced Networking Study Guide: Specialty (ANS-C01) Exam delivers an expert review of Amazon Web Services Networking fundamentals as they relate to the ANS-C01 exam. You’ll find detailed explanations of critical exam topics combined with real-world scenarios that will help you build the robust knowledge base you need for the test—and to succeed in the field as an AWS Certified Networking specialist. Learn about the design, implementation and deployment of AWS cloud-based Networking solutions, core services implementation, AWS service architecture design and maintenance (including architectural best practices), monitoring, Hybrid networks, security, compliance, governance, and network automation. The book also offers one year of free access to Sybex’s online interactive learning environment and expert study tools, featuring flashcards, a glossary of useful terms, chapter tests, practice exams, and a test bank to help you keep track of your progress and measure your exam readiness. The coveted AWS Advanced Networking credential proves your skills with Amazon Web Services and hybrid IT network architectures at scale. It assesses your ability to apply deep technical knowledge to the design and implementation of AWS Networking services. This book provides you with comprehensive review and practice opportunities so you can succeed on the challenging ANS-C01 exam the first time around. It also offers: Coverage of all relevant exam domains and competencies Explanations of how to apply the AWS skills discussed within to the real world in the context of an AWS Certified Networking-related career Complimentary access to the practical Sybex online learning environment, complete with practice exams, flashcards, a glossary, and test bank AWS certification proves to potential employers that you have the knowledge and practical skills you need to deliver forward-looking, resilient, cloud-based solutions. The AWS Certified Advanced Networking Study Guide: Specialty (ANS-C01) Exam, 2nd Edition, is your ticket to the next big step in your career.
Author: Matheus Arrais
Publisher: John Wiley & Sons
ISBN: 1119778972
Category : Computers
Languages : en
Pages : 529
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Book Description
Validate your AWS Cloud database skills! AWS Certified Database Study Guide: Specialty (DBS-C01) Exam focuses on helping you to understand the basic job role of a database administrator / architect and to prepare for taking the certification exam. This is your opportunity to take the next step in your career by expanding and validating your skills on the AWS Cloud, and performing a database-focused role. AWS is the frontrunner in cloud computing products and services, and this study guide will help you to gain an understanding of core AWS services, uses, and basic AWS database design and deployment best practices. AWS offers more than relational and nonrelation databases, they offer purpose built databases, which allow you to utilize database services prebuilt to meet your business requirements. If you are looking to take the Specialty (DBS-C01) exam, this Study Guide is what you need for comprehensive content and robust study tools that will help you gain the edge on exam day and throughout your career. AWS Certified Database certification offers a great way for IT professionals to achieve industry recognition as cloud experts. This new study guide is perfect for you if you perform a database-focused role and want to pass the DBS-C01 exam to prove your knowledge of how to design and deploy secure and robust database applications on AWS technologies. IT cloud professionals who hold AWS certifications are in great demand, and this certification could take your career to the next level! Master all the key concepts you need to pass the AWS Certified Database Specialty (DBS-C01) Exam Further your career by demonstrating your cloud computing expertise and your knowledge of databases and database services Understand the concept of purpose built databases, allowing you to pick the right tool for the right job. Review deployment and migration, management and operations, monitoring and troubleshooting, database security, and more Access the Sybex online learning environment and test bank for interactive study aids and practice questions Readers will also get one year of FREE access after activation to Sybex’s superior online interactive learning environment and test bank, including hundreds of questions, a practice exam, electronic flashcards, and a glossary of key terms.
Author: Eyal Wirsansky
Publisher: Packt Publishing Ltd
ISBN: 180512157X
Category : Computers
Languages : en
Pages : 419
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Book Description
Explore the ever-growing world of genetic algorithms to build and enhance AI applications involving search, optimization, machine learning, deep learning, NLP, and XAI using Python libraries Key Features Learn how to implement genetic algorithms using Python libraries DEAP, scikit-learn, and NumPy Take advantage of cloud computing technology to increase the performance of your solutions Discover bio-inspired algorithms such as particle swarm optimization (PSO) and NEAT Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionWritten by Eyal Wirsansky, a senior data scientist and AI researcher with over 25 years of experience and a research background in genetic algorithms and neural networks, Hands-On Genetic Algorithms with Python offers expert insights and practical knowledge to master genetic algorithms. After an introduction to genetic algorithms and their principles of operation, you’ll find out how they differ from traditional algorithms and the types of problems they can solve, followed by applying them to search and optimization tasks such as planning, scheduling, gaming, and analytics. As you progress, you’ll delve into explainable AI and apply genetic algorithms to AI to improve machine learning and deep learning models, as well as tackle reinforcement learning and NLP tasks. This updated second edition further expands on applying genetic algorithms to NLP and XAI and speeding up genetic algorithms with concurrency and cloud computing. You’ll also get to grips with the NEAT algorithm. The book concludes with an image reconstruction project and other related technologies for future applications. By the end of this book, you’ll have gained hands-on experience in applying genetic algorithms across a variety of fields, with emphasis on artificial intelligence with Python.What you will learn Use genetic algorithms to solve planning, scheduling, gaming, and analytics problems Create reinforcement learning, NLP, and explainable AI applications Enhance the performance of ML models and optimize deep learning architecture Deploy genetic algorithms using client-server architectures, enhancing scalability and computational efficiency Explore how images can be reconstructed using a set of semi-transparent shapes Delve into topics like elitism, niching, and multiplicity in genetic solutions to enhance optimization strategies and solution diversity Who this book is for If you’re a data scientist, software developer, AI enthusiast who wants to break into the world of genetic algorithms and apply them to real-world, intelligent applications as quickly as possible, this book is for you. Working knowledge of the Python programming language is required to get started with this book.
