Mastering Big Data Engineering Aws Gcp Azure Showdown
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Mastering Big Data Engineering Aws Gcp Azure Showdown
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Author : Muthuraman Saminathan
language : en
Publisher: Libertatem Media Private Limited
Release Date : 2024-02-16
Mastering Big Data Engineering Aws Gcp Azure Showdown written by Muthuraman Saminathan and has been published by Libertatem Media Private Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-16 with Business & Economics categories.
In the rapidly evolving field of AI, operationalizing large language models (LLMs) has become a defining challenge. The LLMOps Advantage: Navigating the Future of AI is your comprehensive guide to mastering the deployment, monitoring, and scaling of LLMs in real-world applications. This book bridges the gap between model development and production, introducing readers to the specialized domain of LLMOps—a subset of MLOps tailored to the unique demands of large language models. From building scalable pipelines and optimizing inference workflows to ensuring compliance and security, this guide covers every aspect of operationalizing LLMs. Explore deployment strategies across platforms like AWS, Azure, GCP, and Hugging Face, learn about containerization and serverless architectures, and dive into tools for monitoring and observability such as Prometheus and Grafana. Through practical frameworks and case studies, the book provides actionable insights into managing performance metrics, addressing model drift, and leveraging distributed systems for scalability. Designed for data scientists, LLM engineers, and AI practitioners, The LLMOps Advantage also delves into ethical considerations, emerging trends like multi-modal models, and best practices for integrating LLMs with existing workflows. Whether you ' re fine-tuning models for specific tasks or scaling solutions to meet enterprise needs, this book equips you with the expertise to harness the full potential of LLMs. Stay ahead in the AI revolution with The LLMOps Advantage—your essential roadmap to mastering the future of large language model operations.
Mastering Big Data Engineering Aws Gcp Azure Showdown
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Author : Muthuraman Saminathan
language : en
Publisher: Libertatem Media Private Limited
Release Date : 2024-02-16
Mastering Big Data Engineering Aws Gcp Azure Showdown written by Muthuraman Saminathan and has been published by Libertatem Media Private Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-16 with Business & Economics categories.
In the rapidly evolving field of AI, operationalizing large language models (LLMs) has become a defining challenge. The LLMOps Advantage: Navigating the Future of AI is your comprehensive guide to mastering the deployment, monitoring, and scaling of LLMs in real-world applications. This book bridges the gap between model development and production, introducing readers to the specialized domain of LLMOps—a subset of MLOps tailored to the unique demands of large language models. From building scalable pipelines and optimizing inference workflows to ensuring compliance and security, this guide covers every aspect of operationalizing LLMs. Explore deployment strategies across platforms like AWS, Azure, GCP, and Hugging Face, learn about containerization and serverless architectures, and dive into tools for monitoring and observability such as Prometheus and Grafana. Through practical frameworks and case studies, the book provides actionable insights into managing performance metrics, addressing model drift, and leveraging distributed systems for scalability. Designed for data scientists, LLM engineers, and AI practitioners, The LLMOps Advantage also delves into ethical considerations, emerging trends like multi-modal models, and best practices for integrating LLMs with existing workflows. Whether you ' re fine-tuning models for specific tasks or scaling solutions to meet enterprise needs, this book equips you with the expertise to harness the full potential of LLMs. Stay ahead in the AI revolution with The LLMOps Advantage—your essential roadmap to mastering the future of large language model operations.
Mastering Enterprise Performance Engineering From Monoliths To Microservices
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Author : Gaurav Rathor
language : en
Publisher: Xoffencer International Book Publication House
Release Date : 2025-06-28
Mastering Enterprise Performance Engineering From Monoliths To Microservices written by Gaurav Rathor and has been published by Xoffencer International Book Publication House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-28 with Computers categories.
Mastering Enterprise Performance Engineering: From Monoliths to Microservices is a comprehensive guide that explores the strategic, architectural, and engineering principles needed to build and maintain high-performance enterprise systems in the modern software era. As organizations evolve from legacy monolithic architectures to distributed microservices, the complexity of ensuring consistent performance, scalability, and reliability increases exponentially. This book provides an end-to-end performance engineering framework that integrates best practices across development, deployment, and operations. Beginning with foundational concepts of performance metrics, system bottlenecks, and load modeling, the book transitions into advanced topics such as distributed tracing, service mesh optimization, autoscaling policies, and performance-aware CI/CD pipelines. Readers will gain deep insights into capacity planning, cloud-native profiling, caching strategies, asynchronous processing, and real-time monitoring across microservices ecosystems. Case studies and real-world scenarios illustrate how to proactively diagnose and resolve performance degradation, even in highly dynamic environments. Designed for software architects, DevOps engineers, SREs, and technical leads, this book empowers professionals to shift performance left in the software lifecycle, adopt proactive observability, and ensure that systems not only function—but thrive— under demanding enterprise workloads. With a blend of theory, tooling, and actionable guidance, this book is essential reading for anyone navigating the shift from monoliths to microservices in pursuit of performance excellence.
Data Engineering With Apache Spark Delta Lake And Lakehouse
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Author : Manoj Kukreja
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-10-22
Data Engineering With Apache Spark Delta Lake And Lakehouse written by Manoj Kukreja and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-22 with Computers categories.
Understand the complexities of modern-day data engineering platforms and explore strategies to deal with them with the help of use case scenarios led by an industry expert in big data Key FeaturesBecome well-versed with the core concepts of Apache Spark and Delta Lake for building data platformsLearn how to ingest, process, and analyze data that can be later used for training machine learning modelsUnderstand how to operationalize data models in production using curated dataBook Description In the world of ever-changing data and schemas, it is important to build data pipelines that can auto-adjust to changes. This book will help you build scalable data platforms that managers, data scientists, and data analysts can rely on. Starting with an introduction to data engineering, along with its key concepts and architectures, this book will show you how to use Microsoft Azure Cloud services effectively for data engineering. You'll cover data lake design patterns and the different stages through which the data needs to flow in a typical data lake. Once you've explored the main features of Delta Lake to build data lakes with fast performance and governance in mind, you'll advance to implementing the lambda architecture using Delta Lake. Packed with practical examples and code snippets, this book takes you through real-world examples based on production scenarios faced by the author in his 10 years of experience working with big data. Finally, you'll cover data lake deployment strategies that play an important role in provisioning the cloud resources and deploying the data pipelines in a repeatable and continuous way. By the end of this data engineering book, you'll know how to effectively deal with ever-changing data and create scalable data pipelines to streamline data science, ML, and artificial intelligence (AI) tasks. What you will learnDiscover the challenges you may face in the data engineering worldAdd ACID transactions to Apache Spark using Delta LakeUnderstand effective design strategies to build enterprise-grade data lakesExplore architectural and design patterns for building efficient data ingestion pipelinesOrchestrate a data pipeline for preprocessing data using Apache Spark and Delta Lake APIsAutomate deployment and monitoring of data pipelines in productionGet to grips with securing, monitoring, and managing data pipelines models efficientlyWho this book is for This book is for aspiring data engineers and data analysts who are new to the world of data engineering and are looking for a practical guide to building scalable data platforms. If you already work with PySpark and want to use Delta Lake for data engineering, you'll find this book useful. Basic knowledge of Python, Spark, and SQL is expected.
The Self Taught Cloud Computing Engineer
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Author : Dr. Logan Song
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-09-22
The Self Taught Cloud Computing Engineer written by Dr. Logan Song and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-22 with Computers categories.
Transform into a cloud-savvy professional by mastering cloud technologies through hands-on projects and expert guidance, paving the way for a thriving cloud computing career Get With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader Free Key Features Gain a solid foundation in cloud computing with a structured, easy-to-follow guide Develop practical skills across AWS, Azure, and Google Cloud, covering compute, storage, networking, data, security, and AI Work on real life industrial projects, business use cases, and personal cloud career development Book DescriptionAs cloud computing continues to revolutionize IT, professionals face the challenge of keeping up with rapidly evolving technologies. This book provides a clear roadmap for mastering cloud concepts, developing hands-on expertise, and obtaining professional certifications, making it an essential resource for those looking to advance their careers in cloud computing. Starting with a focus on the Amazon cloud, you’ll be introduced to fundamental AWS cloud services, followed by advanced AWS cloud services in the domains of data, machine learning, and security. Next, you’ll build proficiency in Microsoft Azure cloud and Google Cloud Platform (GCP) by examining the common attributes of the three clouds, differentiating their unique features, along with leveraging real-life cloud project implementations on these cloud platforms. Through hands-on projects and real-world applications, you’ll gain the skills needed to work confidently across different cloud platforms. The book concludes with career development guidance, including certification paths and industry insights to help you succeed in the cloud computing landscape. Walking through this cloud computing book, you’ll systematically establish a robust footing in AWS, Azure, and GCP, and emerge as a cloud-savvy professional, equipped with cloud certificates to validate your skills.What you will learn Develop core skills needed to work with AWS, Azure, and GCP Gain proficiency in compute, storage, and networking services across multi-cloud and hybrid-cloud environments Integrate cloud databases, big data, and machine learning services in multi-cloud environments Design and develop data pipelines, encompassing data ingestion, storage, processing, and visualization in the clouds Implement machine learning pipelines in multi-cloud environment Secure cloud infrastructure ecosystems with advanced cloud security services Who this book is for This book is ideal for IT professionals looking to transition into cloud computing, as well as experienced cloud practitioners seeking to deepen their knowledge. Whether you're a beginner with basic computing experience or an industry professional aiming to expand your expertise, this comprehensive guide provides the skills and insights needed to excel in the cloud domain.
Mastering Multi Cloud Paradigm For Enterprises
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Author : Barjender Paul
language : en
Publisher: Orange Education Pvt Ltd
Release Date : 2024-08-16
Mastering Multi Cloud Paradigm For Enterprises written by Barjender Paul and has been published by Orange Education Pvt Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-16 with Computers categories.
TAGLINE Building Tomorrow's Enterprise: Embracing the Multi-Cloud Era with AWS, Azure, and GCP. KEY FEATURES ● Comprehensive guide to multi-cloud architecture designs and best practices. ● Expert insights on networking strategies and efficient DNS design for multi-cloud. ● Emphasis on security, performance, cost-efficiency, and robust disaster recovery. DESCRIPTION This book is a comprehensive guide designed for IT professionals and enterprise architects, providing step-by-step instructions for creating and implementing tailored multi-cloud strategies. Covering key areas such as security, performance, cost management, and disaster recovery, it ensures robust and efficient cloud deployments. This book will help you learn to develop custom multi-cloud solutions that align with the organization's specific needs and goals. It includes in-depth discussions on cloud design patterns, architecture designs, and industry best practices. The book offers advanced networking strategies and DNS design insights to optimize system reliability, scalability, and performance. Practical tips help readers navigate the complexities of multi-cloud environments, ensuring seamless integration and management across different cloud platforms. Whether new to cloud concepts or an experienced practitioner looking to enhance your skills, this book equips you with the knowledge and tools needed to excel in your role. By following expert guidance and best practices, you can confidently design and implement multi-cloud strategies that foster innovation and operational excellence in your organization. WHAT WILL YOU LEARN ● Understand the fundamentals and benefits of multi-cloud environments. ● Gain a solid grasp of essential cloud computing concepts and terminologies. ● Learn how to establish a robust foundation for multi-cloud deployments. ● Implement best practices for securing and governing multi-cloud architectures. ● Design effective network solutions tailored for multi-cloud environments. ● Optimize DNS design and management across multiple cloud platforms. ● Apply architecture design patterns to enhance system reliability and scalability. ● Manage costs effectively and implement financial operations in a multi-cloud setting. ● Leverage automation and orchestration to streamline multi-cloud operations. ● Monitor and manage performance and health across various cloud services. ● Ensure robust disaster recovery and build resilient systems for multi-cloud. WHO IS THIS BOOK FOR? This book is for IT professionals, cloud architects, enterprise architects, and cloud engineers with a basic understanding of cloud computing concepts. It is ideal for those looking to deepen their knowledge of multi-cloud strategies and best practices to enhance their organization's cloud infrastructure. TABLE OF CONTENTS 1. Getting Started with Multi-Cloud 2. Cloud Computing Concepts 3. Building a Solid Foundation 4. Security and Governance in Multi-Cloud 5. Designing Network Solution 6. DNS in a Multi-Cloud Landscape 7. Architecture Design Pattern in Multi-Cloud 8. FinOps in Multi-Cloud 9. The Role of Automation and Orchestration 10. Multi-Cloud Monitoring 11. Resilience and Disaster Recovery Index
Mastering Machine Learning On Aws
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Author : Dr. Saket S.R. Mengle
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-05-20
Mastering Machine Learning On Aws written by Dr. Saket S.R. Mengle and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-20 with Computers categories.
Gain expertise in ML techniques with AWS to create interactive apps using SageMaker, Apache Spark, and TensorFlow. Key FeaturesBuild machine learning apps on Amazon Web Services (AWS) using SageMaker, Apache Spark and TensorFlowLearn model optimization, and understand how to scale your models using simple and secure APIsDevelop, train, tune and deploy neural network models to accelerate model performance in the cloudBook Description AWS is constantly driving new innovations that empower data scientists to explore a variety of machine learning (ML) cloud services. This book is your comprehensive reference for learning and implementing advanced ML algorithms in AWS cloud. As you go through the chapters, you’ll gain insights into how these algorithms can be trained, tuned and deployed in AWS using Apache Spark on Elastic Map Reduce (EMR), SageMaker, and TensorFlow. While you focus on algorithms such as XGBoost, linear models, factorization machines, and deep nets, the book will also provide you with an overview of AWS as well as detailed practical applications that will help you solve real-world problems. Every practical application includes a series of companion notebooks with all the necessary code to run on AWS. In the next few chapters, you will learn to use SageMaker and EMR Notebooks to perform a range of tasks, right from smart analytics, and predictive modeling, through to sentiment analysis. By the end of this book, you will be equipped with the skills you need to effectively handle machine learning projects and implement and evaluate algorithms on AWS. What you will learnManage AI workflows by using AWS cloud to deploy services that feed smart data productsUse SageMaker services to create recommendation modelsScale model training and deployment using Apache Spark on EMRUnderstand how to cluster big data through EMR and seamlessly integrate it with SageMakerBuild deep learning models on AWS using TensorFlow and deploy them as servicesEnhance your apps by combining Apache Spark and Amazon SageMakerWho this book is for This book is for data scientists, machine learning developers, deep learning enthusiasts and AWS users who want to build advanced models and smart applications on the cloud using AWS and its integration services. Some understanding of machine learning concepts, Python programming and AWS will be beneficial.
Mastering Azure Analytics
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Author : Zoiner Tejada
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2017-04-06
Mastering Azure Analytics written by Zoiner Tejada and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-06 with Computers categories.
Helps users understand the breadth of Azure services by organizing them into a reference framework they can use when crafting their own big-data analytics solution.
Data Engineering With Google Cloud Platform
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Author : Adi Wijaya
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-03-31
Data Engineering With Google Cloud Platform written by Adi Wijaya and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-31 with Computers categories.
Build and deploy your own data pipelines on GCP, make key architectural decisions, and gain the confidence to boost your career as a data engineer Key Features Understand data engineering concepts, the role of a data engineer, and the benefits of using GCP for building your solution Learn how to use the various GCP products to ingest, consume, and transform data and orchestrate pipelines Discover tips to prepare for and pass the Professional Data Engineer exam Book DescriptionWith this book, you'll understand how the highly scalable Google Cloud Platform (GCP) enables data engineers to create end-to-end data pipelines right from storing and processing data and workflow orchestration to presenting data through visualization dashboards. Starting with a quick overview of the fundamental concepts of data engineering, you'll learn the various responsibilities of a data engineer and how GCP plays a vital role in fulfilling those responsibilities. As you progress through the chapters, you'll be able to leverage GCP products to build a sample data warehouse using Cloud Storage and BigQuery and a data lake using Dataproc. The book gradually takes you through operations such as data ingestion, data cleansing, transformation, and integrating data with other sources. You'll learn how to design IAM for data governance, deploy ML pipelines with the Vertex AI, leverage pre-built GCP models as a service, and visualize data with Google Data Studio to build compelling reports. Finally, you'll find tips on how to boost your career as a data engineer, take the Professional Data Engineer certification exam, and get ready to become an expert in data engineering with GCP. By the end of this data engineering book, you'll have developed the skills to perform core data engineering tasks and build efficient ETL data pipelines with GCP.What you will learn Load data into BigQuery and materialize its output for downstream consumption Build data pipeline orchestration using Cloud Composer Develop Airflow jobs to orchestrate and automate a data warehouse Build a Hadoop data lake, create ephemeral clusters, and run jobs on the Dataproc cluster Leverage Pub/Sub for messaging and ingestion for event-driven systems Use Dataflow to perform ETL on streaming data Unlock the power of your data with Data Studio Calculate the GCP cost estimation for your end-to-end data solutions Who this book is for This book is for data engineers, data analysts, and anyone looking to design and manage data processing pipelines using GCP. You'll find this book useful if you are preparing to take Google's Professional Data Engineer exam. Beginner-level understanding of data science, the Python programming language, and Linux commands is necessary. A basic understanding of data processing and cloud computing, in general, will help you make the most out of this book.
Azure Data Engineer Associate Certification Guide
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Author : Newton Alex
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-02-28
Azure Data Engineer Associate Certification Guide written by Newton Alex and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-28 with Computers categories.
Become well-versed with data engineering concepts and exam objectives to achieve Azure Data Engineer Associate certification Key Features Understand and apply data engineering concepts to real-world problems and prepare for the DP-203 certification exam Explore the various Azure services for building end-to-end data solutions Gain a solid understanding of building secure and sustainable data solutions using Azure services Book DescriptionAzure is one of the leading cloud providers in the world, providing numerous services for data hosting and data processing. Most of the companies today are either cloud-native or are migrating to the cloud much faster than ever. This has led to an explosion of data engineering jobs, with aspiring and experienced data engineers trying to outshine each other. Gaining the DP-203: Azure Data Engineer Associate certification is a sure-fire way of showing future employers that you have what it takes to become an Azure Data Engineer. This book will help you prepare for the DP-203 examination in a structured way, covering all the topics specified in the syllabus with detailed explanations and exam tips. The book starts by covering the fundamentals of Azure, and then takes the example of a hypothetical company and walks you through the various stages of building data engineering solutions. Throughout the chapters, you'll learn about the various Azure components involved in building the data systems and will explore them using a wide range of real-world use cases. Finally, you’ll work on sample questions and answers to familiarize yourself with the pattern of the exam. By the end of this Azure book, you'll have gained the confidence you need to pass the DP-203 exam with ease and land your dream job in data engineering.What you will learn Gain intermediate-level knowledge of Azure the data infrastructure Design and implement data lake solutions with batch and stream pipelines Identify the partition strategies available in Azure storage technologies Implement different table geometries in Azure Synapse Analytics Use the transformations available in T-SQL, Spark, and Azure Data Factory Use Azure Databricks or Synapse Spark to process data using Notebooks Design security using RBAC, ACL, encryption, data masking, and more Monitor and optimize data pipelines with debugging tips Who this book is for This book is for data engineers who want to take the DP-203: Azure Data Engineer Associate exam and are looking to gain in-depth knowledge of the Azure cloud stack. The book will also help engineers and product managers who are new to Azure or interviewing with companies working on Azure technologies, to get hands-on experience of Azure data technologies. A basic understanding of cloud technologies, extract, transform, and load (ETL), and databases will help you get the most out of this book.