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.

Data Wrangling on AWS. Clean and organize complex data for analysis

Navnit Shukla, Sankar M, Sampat Palani

Data wrangling is the process of cleaning, transforming, and organizing raw, messy, or unstructured data into a structured format. It involves processes such as data cleaning, data integration, data transformation, and data enrichment to ensure that the data is accurate, consistent, and suitable for analysis. Data Wrangling on AWS equips you with the knowledge to reap the full potential of AWS data wrangling tools.First, you’ll be introduced to data wrangling on AWS and will be familiarized with data wrangling services available in AWS. You’ll understand how to work with AWS Glue DataBrew, AWS data wrangler, and AWS Sagemaker. Next, you’ll discover other AWS services like Amazon S3, Redshift, Athena, and Quicksight. Additionally, you’ll explore advanced topics such as performing Pandas data operation with AWS data wrangler, optimizing ML data with AWS SageMaker, building the data warehouse with Glue DataBrew, along with security and monitoring aspects.By the end of this book, you’ll be well-equipped to perform data wrangling using AWS services.

Datadog Cloud Monitoring Quick Start Guide. Proactively create dashboards, write scripts, manage alerts, and monitor containers using Datadog

Thomas Kurian Theakanath

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.

Deploying Microsoft System Center Configuration Manager. Manage complex and heterogeneous workloads with ConfigMgr 1706

Jacek Doktór, Paweł Jarosz

It becomes important to plan, design, and deploy configurations when administrators know that Configuration Manager interacts with a number of infrastructure components such as Active Directory Domain Services, network protocols, Windows Server services, and so on.Via real-world-world deployment scenarios, this book will help you implement a single primary site or multiples sites. You will be able to efficiently plan and deploy a multiple-site hierarchy such as central administration site. Next, you will learn various methods to plan and deploy Configuration Manager clients, secure them and make the most of new features offered through ConfigMgr 1706 like compliance, deploying updates operating systems to the endpoints. Then, this book will show you how to install, configure, and run SQL reports to extract information. Lastly, you will also learn how to create and manage users access in an ConfigMgr environmentBy the end of this book, you will have learned to use the built-in mechanism to back up and restore data and also design maintenance plan.