Book Image

Implementing Azure Cloud Design Patterns

By : Oliver Michalski, Stefano Demiliani
Book Image

Implementing Azure Cloud Design Patterns

By: Oliver Michalski, Stefano Demiliani

Overview of this book

A well designed cloud infrastructure covers factors such as consistency, maintenance, simplified administration and development, and reusability. Hence it is important to choose the right architectural pattern as it has a huge impact on the quality of cloud-hosted services. This book covers all Azure design patterns and functionalities to help you build your cloud infrastructure so it fits your system requirements. This book initially covers design patterns that are focused on factors such as availability and data management/monitoring. Then the focus shifts to complex design patterns such as multitasking, improving scalability, valet keys, and so on, with practical use cases. The book also supplies best practices to improve the security and performance of your cloud. By the end of this book, you will thoroughly be familiar with the different design and architectural patterns available with Windows Azure and capable of choosing the best pattern for your system.
Table of Contents (16 chapters)
Title Page
Packt Upsell

Azure data services

Azure data services are managed services that extend the platform with so-called common capabilities (shared functionalities). Because of the special importance of data in today's digital world, they were separated from the Azure application building blocks and represent a separate kind of service.

In the following diagram, you will find an overview of the Azure data services. Because of the high number of individual components on offer, these are only represented in categories:

The service categories are as follows:

  • Storage: This category includes a total of five very different services: Blob Storage (storage of unstructured data), Table Storage (NoSQL storage based on key-value pairs), Queue Storage (for message processing), File Storage, and Disk Storage (Premium Storage).
  • SQL Database as a Service: This category includes three full managed Databases as a Service: SQL Server, MySQL and PostgreSQL. This category also includes some special offers: SQL Server DWH, SQL Server Stretch DB, SQL Server Elastic DB. All special offers are further developments of the SQL Server as a Service and cover specific cloud workloads.
  • NoSQL Database as a Service: This category includes a fully managed NoSQL Database as a Service: Azure CosmosDB. A NoSQL database is used to store semi-structured data. A NoSQL database distinguishes between storing key-values, graphs, and document data. You can specify what type of storage you want to use when creating the database.
  • Big Data: This category includes, along with Azure HDInsight, a fully managed implementation of Apache Hadoop. In addition, implementations (with varying levels of development) are available for Apache Storm, Apache Spark, Apache Kafka, and the Microsoft R Server.
  • Analytics: This category includes tools to analyze and process data, such as Azure Stream Analytics, Azure Data Lake Analytics, and the Azure Data Factory.
  • AI: This category includes a fully managed service, Azure Machine Learning (Azure ML), that enables you to easily build, deploy and share predictive analytics solutions, and also includes some prefabricated solutions for immediate use (Microsoft Cognitive Services).
  • Visualization: This category is a special case because the offered service (Microsoft PowerBI) is strictly an Azure service but is only offered by Microsoft as an SaaS solution.