Cloud Solution Architect's Career Master Plan. Proven techniques and effective tips to help you become a successful solution architect

Rick Weyenberg, Kyle Burns

In the fast-paced tech world where businesses rely ever more on cloud infrastructure, the role of a cloud solution architect serves as the backbone of operations. The Solution Architects Career Masterplan isn’t just informative; it’s an actionable roadmap to thriving in this role, providing the knowledge and strategies necessary to build a successful career in cloud computing.You’ll dive headfirst into mastering the role's core principles, strategically charting your career trajectory, and expanding your network within the cloud community. As you advance to the practical aspects, you’ll explore tailored education options, gain hands-on experience, and prepare to seize strategic opportunities. Finally, you’ll prepare for success by arming yourself with interview strategies, staying updated with evolving cloud technologies, and actively contributing to the cloud community.By the end of this book, you'll be on your path to a rewarding career in cloud architecture with this trusted companion.

Cloudera Administration Handbook. A complete, hands-on guide to building and maintaining large Apache Hadoop clusters using Cloudera Manager and CDH5

Rohit Menon

Cloud-Native Applications in Java. Build microservice-based cloud-native applications that dynamically scale

Ajay Mahajan, Munish Kumar Gupta, Shyam Sundar S

Businesses today are evolving so rapidly that they are resorting to the elasticity of the cloud to provide a platform to build and deploy their highly scalable applications. This means developers now are faced with the challenge of building build applications that are native to the cloud. For this, they need to be aware of the environment, tools, and resources they’re coding against. If you’re a Java developer who wants to build secure, resilient, robust, and scalable applications that are targeted for cloud-based deployment, this is the book for you. It will be your one stop guide to building cloud-native applications in Java Spring that are hosted in On-prem or cloud providers - AWS and AzureThe book begins by explaining the driving factors for cloud adoption and shows you how cloud deployment is different from regular application deployment on a standard data centre. You will learn about design patterns specific to applications running in the cloud and find out how you can build a microservice in Java Spring using REST APIsYou will then take a deep dive into the lifecycle of building, testing, and deploying applications with maximum automation to reduce the deployment cycle time. Gradually, you will move on to configuring the AWS and Azure platforms and working with their APIs to deploy your application. Finally, you’ll take a look at API design concerns and their best practices. You’ll also learn how to migrate an existing monolithic application into distributed cloud native applications.By the end, you will understand how to build and monitor a scalable, resilient, and robust cloud native application that is always available and fault tolerant.

Containers for Developers Handbook. A practical guide to developing and delivering applications using software containers

Francisco Javier Ramírez Urea

Developers are changing their deployment artifacts from application binaries to container images, giving rise to the need to build container-based apps as part of their new development workflow. Managing an app’s life cycle is complex and requires effort—this book will show you how to efficiently develop, share, and execute applications.You’ll learn how to automate the build and delivery process using CI/CD tools with containers as container orchestrators manage the complexity of running cluster-wide applications, creating infrastructure abstraction layers, while your applications run with high availability, resilience, and persistence. As you advance, you’ll develop, test, and debug applications on your desktop and get them ready to run in production with optimal security standards, using deployment patterns and monitoring tools to help identify common issues. You’ll also review deployment patterns that’ll enable you to solve common deployment problems, providing high availability, scalability, and security to your applications. Finally, you’ll explore different solutions to monitor, log, and instrument your applications as per open-source community standards.By the end of this book, you’ll be able to manage your app’s life cycle by implementing CI/CD workflows using containers to automate the building and delivery of its components.

Containers in OpenStack. Leverage OpenStack services to make the most of Docker, Kubernetes and Mesos

Madhuri Kumari, Pradeep Kumar Singh

Containers are one of the most talked about technologies of recent times. They have become increasingly popular as they are changing the way we develop, deploy, and run software applications. OpenStack gets tremendous traction as it is used by many organizations across the globe and as containers gain in popularity and become complex, it’s necessary for OpenStack to provide various infrastructure resources for containers, such as compute, network, and storage.Containers in OpenStack answers the question, how can OpenStack keep ahead of the increasing challenges of container technology? You will start by getting familiar with container and OpenStack basics, so that you understand how the container ecosystem and OpenStack work together. To understand networking, managing application services and deployment tools, the book has dedicated chapters for different OpenStack projects: Magnum, Zun, Kuryr, Murano, and Kolla. Towards the end, you will be introduced to some best practices to secure your containers and COE on OpenStack, with an overview of using each OpenStack projects for different use cases.

Data Engineering with AWS. Learn how to design and build cloud-based data transformation pipelines using AWS

Gareth Eagar

Written by a Senior Data Architect with over twenty-five years of experience in the business, Data Engineering for AWS is a book whose sole aim is to make you proficient in using the AWS ecosystem. Using a thorough and hands-on approach to data, this book will give aspiring and new data engineers a solid theoretical and practical foundation to succeed with AWS.As you progress, you’ll be taken through the services and the skills you need to architect and implement data pipelines on AWS. You'll begin by reviewing important data engineering concepts and some of the core AWS services that form a part of the data engineer's toolkit. You'll then architect a data pipeline, review raw data sources, transform the data, and learn how the transformed data is used by various data consumers. You’ll also learn about populating data marts and data warehouses along with how a data lakehouse fits into the picture. Later, you'll be introduced to AWS tools for analyzing data, including those for ad-hoc SQL queries and creating visualizations. In the final chapters, you'll understand how the power of machine learning and artificial intelligence can be used to draw new insights from data.By the end of this AWS book, you'll be able to carry out data engineering tasks and implement a data pipeline on AWS independently.

Data Engineering with Google Cloud Platform. A practical guide to operationalizing scalable data analytics systems on GCP

Adi Wijaya

With 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.

Data Modeling for Azure Data Services. Implement professional data design and structures in Azure

Peter ter Braake

Data is at the heart of all applications and forms the foundation of modern data-driven businesses. With the multitude of data-related use cases and the availability of different data services, choosing the right service and implementing the right design becomes paramount to successful implementation.Data Modeling for Azure Data Services starts with an introduction to databases, entity analysis, and normalizing data. The book then shows you how to design a NoSQL database for optimal performance and scalability and covers how to provision and implement Azure SQL DB, Azure Cosmos DB, and Azure Synapse SQL Pool. As you progress through the chapters, you'll learn about data analytics, Azure Data Lake, and Azure SQL Data Warehouse and explore dimensional modeling, data vault modeling, along with designing and implementing a Data Lake using Azure Storage. You'll also learn how to implement ETL with Azure Data Factory.By the end of this book, you'll have a solid understanding of which Azure data services are the best fit for your model and how to implement the best design for your solution.