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Author: Eric Salituro
Publisher: Packt Publishing Ltd
ISBN: 1801814333
Category : Computers
Languages : en
Pages : 542
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Book Description
Get up and running with building data pipelines and creating interactive dashboards to visualize, monitor, and present a wide variety of time-series data with this comprehensive introductory guide Key Features Install, set up, and configure Grafana for real-time data analysis, visualization, and alerting Visualize and monitor data using data sources such as InfluxDB, Telegraf, Prometheus, and Elasticsearch Explore Grafana's cloud support with Microsoft Azure, Amazon CloudWatch, and Google Cloud Monitoring Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionGet ready to unlock the full potential of the open-source Grafana observability platform, ideal for analyzing and monitoring time-series data with this updated second edition. This beginners guide will help you get up to speed with Grafana’s latest features for querying, visualizing, and exploring logs and metrics, no matter where they are stored. Starting with the basics, this book demonstrates how to quickly install and set up a Grafana server using Docker. You’ll then be introduced to the main components of the Grafana interface before learning how to analyze and visualize data from sources such as InfluxDB, Telegraf, Prometheus, Logstash, and Elasticsearch. The book extensively covers key panel visualizations in Grafana, including Time Series, Stat, Table, Bar Gauge, and Text, and guides you in using Python to pipeline data, transformations to facilitate analytics, and templating to build dynamic dashboards. Exploring real-time data streaming with Telegraf, Promtail, and Loki, you’ll work with observability features like alerting rules and integration with PagerDuty and Slack. As you progress, the book addresses the administrative aspects of Grafana, from configuring users and organizations to implementing user authentication with Okta and LDAP, as well as organizing dashboards into folders, and more. By the end of this book, you’ll have gained all the knowledge you need to start building interactive dashboards.What you will learn Learn the techniques of data visualization using Grafana Get familiar with the major components of Time series visualization Explore data transformation operations, query inspector, and time interval settings Work with advanced dashboard features, such as annotations, variable-based templating, and dashboard linking and sharing Connect user authentication through Okta, Google, GitHub, and other external providers Discover Grafana’s monitoring support for cloud service infrastructures Who this book is for This book is for business intelligence developers, business analysts, data analysts, and anyone interested in performing time-series data analysis and monitoring using Grafana. You’ll also find this book useful if you’re looking to create and share interactive dashboards or get up to speed with the latest features of Grafana. Although no prior knowledge of Grafana is required, basic knowledge of data visualization and some Python programming experience will help you understand the concepts covered in the book.
Author: Eric Salituro
Publisher: Packt Publishing Ltd
ISBN: 1801814333
Category : Computers
Languages : en
Pages : 542
Get Book Here
Book Description
Get up and running with building data pipelines and creating interactive dashboards to visualize, monitor, and present a wide variety of time-series data with this comprehensive introductory guide Key Features Install, set up, and configure Grafana for real-time data analysis, visualization, and alerting Visualize and monitor data using data sources such as InfluxDB, Telegraf, Prometheus, and Elasticsearch Explore Grafana's cloud support with Microsoft Azure, Amazon CloudWatch, and Google Cloud Monitoring Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionGet ready to unlock the full potential of the open-source Grafana observability platform, ideal for analyzing and monitoring time-series data with this updated second edition. This beginners guide will help you get up to speed with Grafana’s latest features for querying, visualizing, and exploring logs and metrics, no matter where they are stored. Starting with the basics, this book demonstrates how to quickly install and set up a Grafana server using Docker. You’ll then be introduced to the main components of the Grafana interface before learning how to analyze and visualize data from sources such as InfluxDB, Telegraf, Prometheus, Logstash, and Elasticsearch. The book extensively covers key panel visualizations in Grafana, including Time Series, Stat, Table, Bar Gauge, and Text, and guides you in using Python to pipeline data, transformations to facilitate analytics, and templating to build dynamic dashboards. Exploring real-time data streaming with Telegraf, Promtail, and Loki, you’ll work with observability features like alerting rules and integration with PagerDuty and Slack. As you progress, the book addresses the administrative aspects of Grafana, from configuring users and organizations to implementing user authentication with Okta and LDAP, as well as organizing dashboards into folders, and more. By the end of this book, you’ll have gained all the knowledge you need to start building interactive dashboards.What you will learn Learn the techniques of data visualization using Grafana Get familiar with the major components of Time series visualization Explore data transformation operations, query inspector, and time interval settings Work with advanced dashboard features, such as annotations, variable-based templating, and dashboard linking and sharing Connect user authentication through Okta, Google, GitHub, and other external providers Discover Grafana’s monitoring support for cloud service infrastructures Who this book is for This book is for business intelligence developers, business analysts, data analysts, and anyone interested in performing time-series data analysis and monitoring using Grafana. You’ll also find this book useful if you’re looking to create and share interactive dashboards or get up to speed with the latest features of Grafana. Although no prior knowledge of Grafana is required, basic knowledge of data visualization and some Python programming experience will help you understand the concepts covered in the book.
Author: Bernardo Ronquillo Japón
Publisher: BPB Publications
ISBN: 9391392385
Category : Antiques & Collectibles
Languages : en
Pages : 253
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Book Description
Program edge devices by learning low-code programming and essentials of IoT systems. KEY FEATURES ● In-depth practical demonstration of the IoT architecture with numerous examples. ● Includes graphical illustrations and uses of popular full-stack tools. ● Access to hardware components and software packages to build powerful IoT systems. DESCRIPTION Learn IoT Programming with Node-RED is an excellent source of practical knowledge for developing a successful Internet of Things system, starting with the very first step of programming a Raspberry Pi, and using numerous open-source software development tools. To begin, the book will provide you with a practical experience of visual programming, fundamentals of Node-RED, and the architecture of an Internet of Things system. The book covers data collecting capabilities and the development of real-time streaming functionalities. The book describes how to set up an Internet of Things infrastructure, manage software development, and integrate physical devices. The book provides IoT projects based on temperature and humidity data recorded as time series. It teaches you how to design the software using a simulated model of the hardware and use the same code to execute it in the actual hardware. Node-RED, Pusher, InfluxDB, and Grafana are some of the professional tools you will learn in this book. After reading the book, you will gain the knowledge to create your own applications that will be connected to the physical environment by means of a range of sensors. WHAT YOU WILL LEARN ● Create IoT systems with NodeRED visual programming. ● Learn to transfer data from IoT devices to machines for analysis using Pusher, a free platform. ● Store time-series data streams to InfluxDB. ● Use NodeRED to process data and execute statistical calculations on the remote machine. ● Create user-friendly Grafana dashboards for environmental monitoring. WHO THIS BOOK IS FOR IoT engineers, roboticists, and embedded system programmers who are interested in learning low-code development and programming hardware devices may benefit from this book. Prior knowledge of Linux and Raspberry Pi may be helpful. TABLE OF CONTENTS 1. Introduction to IoT Applications and Their Software Architecture 2. Getting Started with NodeRED 3. Data Acquisition and Real-time Streaming 4. Real-time Data Processing with NodeRED 5. Storing and Graphing Data Streams with InfluxDB and Grafana 6. The IoT Hardware Package 7. The IoT Software Package
Author: Eric Salituro
Publisher: Packt Publishing Ltd
ISBN: 1838828311
Category : Computers
Languages : en
Pages : 401
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Book Description
A comprehensive introduction to help you get up and running with creating interactive dashboards to visualize and monitor time-series data in no time Key Features Install, set up, and configure Grafana for real-time data analysis and visualization Visualize and monitor data using data sources such as InfluxDB, Prometheus, and Elasticsearch Explore Grafana's multi-cloud support with Microsoft Azure, Amazon CloudWatch, and Google Stackdriver Book DescriptionGrafana is an open-source analytical platform used to analyze and monitoring time-series data. This beginner's guide will help you get to grips with Grafana's new features for querying, visualizing, and exploring metrics and logs no matter where they are stored. The book begins by showing you how to install and set up the Grafana server. You'll explore the working mechanism of various components of the Grafana interface along with its security features, and learn how to visualize and monitor data using, InfluxDB, Prometheus, Logstash, and Elasticsearch. This Grafana book covers the advanced features of the Graph panel and shows you how Stat, Table, Bar Gauge, and Text are used. You'll build dynamic dashboards to perform end-to-end analytics and label and organize dashboards into folders to make them easier to find. As you progress, the book delves into the administrative aspects of Grafana by creating alerts, setting permissions for teams, and implementing user authentication. Along with exploring Grafana's multi-cloud monitoring support, you'll also learn about Grafana Loki, which is a backend logger for users running Prometheus and Kubernetes. By the end of this book, you'll have gained all the knowledge you need to start building interactive dashboards.What you will learn Find out how to visualize data using Grafana Understand how to work with the major components of the Graph panel Explore mixed data sources, query inspector, and time interval settings Discover advanced dashboard features such as annotations, templating with variables, dashboard linking, and dashboard sharing techniques Connect user authentication to Google, GitHub, and a variety of external services Find out how Grafana can provide monitoring support for cloud service infrastructures Who this book is forThis book is for business intelligence developers, business analysts, data analysts, and anyone interested in performing time-series data analysis and monitoring using Grafana. Those looking to create and share interactive dashboards or looking to get up to speed with the latest features of Grafana will also find this book useful. Although no prior knowledge of Grafana is required, basic knowledge of data visualization and some experience in Python programming will help you understand the concepts covered in the book.
Author: Shivakumar Gopalakrishnan
Publisher: BPB Publications
ISBN: 936589431X
Category : Computers
Languages : en
Pages : 437
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Book Description
DESCRIPTION Modern Python Programming using ChatGPT is your essential guide to leveraging Artificial Intelligence to streamline and enhance your Python development workflow across the entire software development lifecycle (SDLC). This book covers every stage, from requirements gathering and design to implementation, testing, security, deployment, and observability, demonstrating how ChatGPT can be of invaluable assistance throughout. Learn how to use ChatGPT to break down features into stories, design, and architect software, implement AI-generated code snippets, write clean and maintainable code, test and secure applications, deploy efficiently, and monitor performance. This comprehensive guide shows you how to integrate ChatGPT seamlessly into every stage of your Python projects. Discover how ChatGPT can automate repetitive tasks, generate high-quality code snippets, provide instant debugging tips, and ensure your code adheres to industry standards and best practices. This book provides thorough coverage of the latest trends and best practices in Python development, equipping you with the tools to write clean, maintainable, and robust code. Through practical examples and hands-on exercises, you will learn how to apply ChatGPT in real-world scenarios, making your development process more efficient and productive. KEY FEATURES ● Supercharge the entire SDLC using ChatGPT's AI-driven insights. ● Seamlessly integrate ChatGPT into every stage of your Python projects. ● Practical, real-world examples and hands-on exercises. WHAT YOU WILL LEARN ● To seamlessly integrate ChatGPT from coding to deployment to monitoring. ● Use ChatGPT to gather and document software requirements. ● Break down features into stories with ChatGPT assistance. ● Design, architect, and implement clean, maintainable code using AI-generated snippets. ● Test, secure, and deploy applications with AI support. ● Optimize performance and monitor software using ChatGPT. WHO THIS BOOK IS FOR This book is for Python developers of all experience levels who want to enhance their entire software development process using AI. Basic knowledge of Python is assumed, but detailed instructions are provided to help you integrate ChatGPT into your projects effectively. TABLE OF CONTENTS 1. ChatGPT and Its Capabilities 2. Benefits of Using ChatGPT in Python Development 3. Setting up ChatGPT for Python Development 4. Requirements Gathering 5. Design and Architecture 6. Implementing a Software Product 7. Pull Review and Commit Messages 8. Using ChatGPT for Coding with SOLID Principles 9. Software Testing with ChatGPT in Python 10. Deployment with ChatGPT 11. Performance and Observability 12. Revolutionary Impact of ChatGPT 13. Limitations, Pitfalls and Dangers of ChatGPT 14. Preparing for the Future with ChatGPT
Author: Laine Campbell
Publisher: "O'Reilly Media, Inc."
ISBN: 149192621X
Category : Computers
Languages : en
Pages : 309
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Book Description
The infrastructure-as-code revolution in IT is also affecting database administration. With this practical book, developers, system administrators, and junior to mid-level DBAs will learn how the modern practice of site reliability engineering applies to the craft of database architecture and operations. Authors Laine Campbell and Charity Majors provide a framework for professionals looking to join the ranks of today’s database reliability engineers (DBRE). You’ll begin by exploring core operational concepts that DBREs need to master. Then you’ll examine a wide range of database persistence options, including how to implement key technologies to provide resilient, scalable, and performant data storage and retrieval. With a firm foundation in database reliability engineering, you’ll be ready to dive into the architecture and operations of any modern database. This book covers: Service-level requirements and risk management Building and evolving an architecture for operational visibility Infrastructure engineering and infrastructure management How to facilitate the release management process Data storage, indexing, and replication Identifying datastore characteristics and best use cases Datastore architectural components and data-driven architectures
Author: Anurag Srivastava
Publisher: Packt Publishing Ltd
ISBN: 1789801885
Category : Computers
Languages : en
Pages : 176
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Book Description
Get the most out of Elasticsearch 7’s new features to build, deploy, and manage efficient applications Key FeaturesDiscover the new features introduced in Elasticsearch 7Explore techniques for distributed search, indexing, and clusteringGain hands-on knowledge of implementing Elasticsearch for your enterpriseBook Description Elasticsearch is one of the most popular tools for distributed search and analytics. This Elasticsearch book highlights the latest features of Elasticsearch 7 and helps you understand how you can use them to build your own search applications with ease. Starting with an introduction to the Elastic Stack, this book will help you quickly get up to speed with using Elasticsearch. You'll learn how to install, configure, manage, secure, and deploy Elasticsearch clusters, as well as how to use your deployment to develop powerful search and analytics solutions. As you progress, you'll also understand how to troubleshoot any issues that you may encounter along the way. Finally, the book will help you explore the inner workings of Elasticsearch and gain insights into queries, analyzers, mappings, and aggregations as you learn to work with search results. By the end of this book, you'll have a basic understanding of how to build and deploy effective search and analytics solutions using Elasticsearch. What you will learnInstall Elasticsearch and use it to safely store data and retrieve it when neededWork with a variety of analyzers and filtersDiscover techniques to improve search results in ElasticsearchUnderstand how to perform metric and bucket aggregationsImplement best practices for moving clusters and applications to productionExplore various techniques to secure your Elasticsearch clustersWho this book is for This book is for software developers, engineers, data architects, system administrators, and anyone who wants to get up and running with Elasticsearch 7. No prior experience with Elasticsearch is required.
Author: Kellyn Gorman
Publisher: Packt Publishing Ltd
ISBN: 1838829822
Category : Computers
Languages : en
Pages : 489
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Book Description
Explore the impressive storage and analytic tools available with the in-cloud and on-premises versions of Microsoft SQL Server 2019. Key FeaturesGain insights into what’s new in SQL Server 2019Understand use cases and customer scenarios that can be implemented with SQL Server 2019Discover new cross-platform tools that simplify management and analysisBook Description Microsoft SQL Server comes equipped with industry-leading features and the best online transaction processing capabilities. If you are looking to work with data processing and management, getting up to speed with Microsoft Server 2019 is key. Introducing SQL Server 2019 takes you through the latest features in SQL Server 2019 and their importance. You will learn to unlock faster querying speeds and understand how to leverage the new and improved security features to build robust data management solutions. Further chapters will assist you with integrating, managing, and analyzing all data, including relational, NoSQL, and unstructured big data using SQL Server 2019. Dedicated sections in the book will also demonstrate how you can use SQL Server 2019 to leverage data processing platforms, such as Apache Hadoop and Spark, and containerization technologies like Docker and Kubernetes to control your data and efficiently monitor it. By the end of this book, you'll be well versed with all the features of Microsoft SQL Server 2019 and understand how to use them confidently to build robust data management solutions. What you will learnBuild a custom container image with a DockerfileDeploy and run the SQL Server 2019 container imageUnderstand how to use SQL server on LinuxMigrate existing paginated reports to Power BI Report ServerLearn to query Hadoop Distributed File System (HDFS) data using Azure Data StudioUnderstand the benefits of In-Memory OLTPWho this book is for This book is for database administrators, architects, big data engineers, or anyone who has experience with SQL Server and wants to explore and implement the new features in SQL Server 2019. Basic working knowledge of SQL Server and relational database management system (RDBMS) is required.
Author: Parth Ghiya
Publisher: Packt Publishing Ltd
ISBN: 1788836855
Category : Computers
Languages : en
Pages : 399
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Book Description
Build robust microservice-based applications that are distributed, fault tolerant, and always available Key Features Learn to build message-driven services for effective communication Design microservices API using Reactive programming design patterns Deploy, scale and monitor microservices for consistent high performance Book Description In the last few years or so, microservices have achieved the rock star status and right now are one of the most tangible solutions in enterprises to make quick, effective, and scalable applications. The apparent rise of Typescript and long evolution from ES5 to ES6 has seen lots of big companies move to ES6 stack. If you want to learn how to leverage the power of microservices to build robust architecture using reactive programming and Typescript in Node.js, then this book is for you. Typescript Microservices is an end-to-end guide that shows you the implementation of microservices from scratch; right from starting the project to hardening and securing your services. We will begin with a brief introduction to microservices before learning to break your monolith applications into microservices. From here, you will learn reactive programming patterns and how to build APIs for microservices. The next set of topics will take you through the microservice architecture with TypeScript and communication between services. Further, you will learn to test and deploy your TypeScript microservices using the latest tools and implement continuous integration. Finally, you will learn to secure and harden your microservice. By the end of the book, you will be able to build production-ready, scalable, and maintainable microservices using Node.js and Typescript. What you will learn Get acquainted with the fundamentals behind microservices. Explore the behavioral changes needed for moving from monolithic to microservices. Dive into reactive programming, Typescript and Node.js to learn its fundamentals in microservices Understand and design a service gateway and service registry for your microservices. Maintain the state of microservice and handle dependencies. Perfect your microservice with unit testing and Integration testing Develop a microservice, secure it, deploy it, and then scale it Who this book is for This book is for JavaScript developers seeking to utilize their Node.js and Typescript skills to build microservices and move away from the monolithic architecture. Prior knowledge of TypeScript and Node.js is assumed.
Author: Caitlin Sadowski
Publisher: Apress
ISBN: 1484242211
Category : Computers
Languages : en
Pages : 275
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Book Description
Get the most out of this foundational reference and improve the productivity of your software teams. This open access book collects the wisdom of the 2017 "Dagstuhl" seminar on productivity in software engineering, a meeting of community leaders, who came together with the goal of rethinking traditional definitions and measures of productivity. The results of their work, Rethinking Productivity in Software Engineering, includes chapters covering definitions and core concepts related to productivity, guidelines for measuring productivity in specific contexts, best practices and pitfalls, and theories and open questions on productivity. You'll benefit from the many short chapters, each offering a focused discussion on one aspect of productivity in software engineering. Readers in many fields and industries will benefit from their collected work. Developers wanting to improve their personal productivity, will learn effective strategies for overcoming common issues that interfere with progress. Organizations thinking about building internal programs for measuring productivity of programmers and teams will learn best practices from industry and researchers in measuring productivity. And researchers can leverage the conceptual frameworks and rich body of literature in the book to effectively pursue new research directions. What You'll LearnReview the definitions and dimensions of software productivity See how time management is having the opposite of the intended effect Develop valuable dashboards Understand the impact of sensors on productivity Avoid software development waste Work with human-centered methods to measure productivity Look at the intersection of neuroscience and productivity Manage interruptions and context-switching Who Book Is For Industry developers and those responsible for seminar-style courses that include a segment on software developer productivity. Chapters are written for a generalist audience, without excessive use of technical terminology.
Author: Noah Gift
Publisher: O'Reilly Media
ISBN: 1492057665
Category : Computers
Languages : en
Pages : 506
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Book Description
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
