Implementing Azure Cloud Design Patterns
Oliver Michalski, Stefano Demiliani
- 300 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Implementing Azure Cloud Design Patterns
Oliver Michalski, Stefano Demiliani
About This Book
A hands-on guide to mastering Azure cloud design patterns and best practices.
Key Features
- Master architectural design patterns in Azure.
- Get hands-on with implementing design patterns.
- Implement best practices for improving efficiency and security
Book Description
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.
What you will learn
- Learn to organize Azure access
- Design the core areas of the Azure Execution Model
- Work with storage and data management
- Create a health endpoint monitoring pattern
- Automate early detection of anomalies
- Identify and secure Azure features
Who this book is for
This book is targeted at cloud architects and cloud solution providers who are looking for an extensive guide to implementing different patterns for the deployment and maintenance of services in Microsoft Azure. Prior experience with Azure is required as the book is completely focused on design patterns.
Frequently asked questions
Information
Monitoring and Telemetry
- Telemetry data
- An overview of monitoring
- Azure management portal
- System specific tools
- Microsoft System Center
- Microsoft Operations Management Suite (OMS)
- Azure Monitor
- Azure Application Insights
- Grafana
- Azure Log Analytics
- Azure Network Watcher
About telemetry data
What is a metric?
- Pre-defined or common metrics
- Custom metrics
- Client metrics: Client metrics are concerned with measuring the perception of the end user, for example, how long does it take for a client application to process and render results? Other areas covered by client metrics are the responsiveness of local and remote operations, the memory footprint, and the CPU usage.
- Business metrics: Business metrics provide a viewpoint to the logical operations (all end user activities) that define the business process. In terms of best practice, business metrics should cover all business transactions that the system performs.
- Application metrics: Application metrics include all measurements of the activity and performance of the application layer (that is, the application code, all application frameworks, and runtime execution environments used by the application). The purpose of these metrics is to help you synchronize the flow through the application with a potentially large number of concurrent user requests, analyze the resources that are consumed, and evaluate the likelihood and causes of performance issues.
- System metrics: System metrics capture information about the performance of the underlying infrastructure. These metrics are typically focused on Key Performance Indicators (KPIs) associated with memory occupancy, network utilization, disk activity, and CPU use.
- Service metrics: Service metrics cover the performance of dependent services, such as Azure Storage, messaging, cache, database, and any other external services your application may use. However, these types of metrics do not measure the performance of these services themselves, but capture information about the performance of the queries your system sends to them.