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- Herausgeber: Packt Publishing
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
Explore powerful Azure DevOps solutions to develop and deploy your software faster and more efficiently.
Key Features
- Build modern microservice-based systems with Azure architecture
- Learn to deploy and manage cloud services and virtual machines
- Configure clusters with Azure Service Fabric for deployment
Book Description
This Learning Path helps you understand microservices architecture and leverage various services of Microsoft Azure Service Fabric to build, deploy, and maintain highly scalable enterprise-grade applications. You will learn to select an appropriate Azure backend structure for your solutions and work with its toolkit and managed apps to share your solutions with its service catalog. As you progress through the Learning Path, you will study Azure Cloud Services, Azure-managed Kubernetes, and Azure Container Services deployment techniques. To apply all that you’ve understood, you will build an end-to-end Azure system in scalable, decoupled tiers for an industrial bakery with three business domains. Toward the end of this Learning Path, you will build another scalable architecture using Azure Service Bus topics to send orders between decoupled business domains with scalable worker roles processing these orders.
By the end of this Learning Path, you will be comfortable in using development, deployment, and maintenance processes to build robust cloud solutions on Azure.
This Learning Path includes content from the following Packt products:
- Learn Microsoft Azure by Mohamed Wali
- Implementing Azure Solutions - Second Edition by Florian Klaffenbach, Oliver Michalski, Markus Klein
- Microservices with Azure by Namit Tanasseri and Rahul Rai
What you will learn
- Study various Azure Service Fabric application programming models
- Create and manage a Kubernetes cluster in Azure Kubernetes Service
- Use site-to-site VPN and ExpressRoute connections in your environment
- Design an Azure IoT app and learn to operate it in various scenarios
- Implement a hybrid Azure design using Azure Stack
- Build Azure SQL databases with Code First Migrations
- Integrate client applications with Web API and SignalR on Azure
- Implement the Azure Active Directory (Azure AD) across the entire system
Who this book is for
If you are an IT system architect, network admin, or a DevOps engineer who wants to implement Azure solutions for your organization, this Learning Path is for you. Basic knowledge of the Azure Cloud platform will be beneficial.
Florian Klaffenbach is working as a technology solutions professional at Microsoft. He is a well-known expert in hybrid cloud scenarios, cloud connectivity, and cloud environment optimization. Before he started working with Microsoft, he worked in several companies in different roles, such as the technical community manager and solution expert at Dell, and solutions architect at CGI Germany. Oliver Michalski started his IT career as a web developer in 1999. Currently, he is a senior software engineer for Microsoft .NET and is an SOA architect. He also works as an independent enterprise consultant in the field of Microsoft Azure. When he started in 2011 with Microsoft Azure, there was no Azure community in the German market. Therefore, Oliver founded the Azure community Germany (ACD). Oliver is chairman of ACD, and he has been a Microsoft Most Valuable Professional for Microsoft Azure. Markus Klein works as a technology solution specialist at Microsoft Germany, and specialize in Azure and Hybrid Azure scenarios. He is passionate about the Microsoft technology for more than 20 years, starting with System Center, Service Provider Foundation, KATAL, Azure Pack, Azure, and Azure Stack. Before joining Microsoft, he worked as an architect at Microsoft Cloud Partners. In 2007, he founded a cloud community and was the co-founder of some Azure meetups. Before he joined Microsoft, he was recognized as an MVP in cloud and datacenter management for seven years. He supports the community and is a regular blogger and speaker at conferences in Europe and abroad. Mohamed Wali is a cloud DevOps engineer based in Amsterdam who has been working with Microsoft technologies for around seven years. He has been working with Azure since 2013. In July 2014, Mohamed became recognized as the youngest Microsoft MVP in the world. He has already authored and co-authored multiple books about Microsoft Azure. He shares his knowledge and expertise through blogging, authoring books, and speaking at events. Namit Tanasseri is a certified Microsoft cloud solutions architect with an experience of more than 11 years. He started his career as a software development engineer with Microsoft Research and Development Center in 2005. During the first five years of his career, he had opportunities to work with major Microsoft product groups, such as Microsoft Office and Windows. During this time, he strengthened his knowledge of agile software development methodologies and processes. He also earned a patent during this tenure. As a technology consultant with Microsoft, Namit worked with Microsoft Azure Services for four years. Namit is a subject matter expert in Microsoft Azure and actively contributes to the Microsoft cloud community, while delivering top quality solutions for Microsoft customers. Namit also led the Windows Azure community in Microsoft Services India. Namit currently serves as a Microsoft cloud solutions architect from Sydney, Australia, and works on large and medium-sized enterprise engagements. Rahul Rai is a technology consultant based in Sydney, Australia with over nine years of professional experience. He has been at the forefront of cloud consulting for government organizations and businesses around the world. Rahul has been working on Microsoft Azure since the service was in its infancy, delivering an ITSM tool built for and on Azure in 2008. Since then, Rahul has played the roles of a developer, a consultant, and an architect for enterprises ranging from small start-ups to multinational corporations. He worked for over five years with Microsoft Services with diverse teams t.o deliver innovative solutions on Microsoft Azure. In Microsoft, Rahul was a subject matter expert in Microsoft cloud technologies. Rahul has also worked as a cloud solution architect for Microsoft, for which he worked closely with some established Microsoft partners to drive joint customer transformations to cloud-based architectures.Sie lesen das E-Book in den Legimi-Apps auf:
Seitenzahl: 559
Veröffentlichungsjahr: 2019
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Implementing Azure: Putting Modern DevOps to Use
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First published: January 2019
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Contributors
About the authors
Florian Klaffenbach is working as a technology solutions professional at Microsoft. He is a well-known expert in hybrid cloud scenarios, cloud connectivity, and cloud environment optimization. Before he started working with Microsoft, he worked in several companies in different roles, such as the technical community manager and solution expert at Dell, and solutions architect at CGI Germany.
Oliver Michalski started in 1999 with his IT carrier as a Web Developer. Now, he is a Senior Software Engineer for Microsoft .NET and an SOA Architect. He also works as an Independent Enterprise Consultant in the field Microsoft Azure. When he started in 2011 with Microsoft Azure, there was no Azure Community on the German market. Therefore, Oliver founded the Azure Community Germany (ACD). Oliver is Chairman of the Azure Community Germany, and since April 2016 and July 2017, he has been a Microsoft Most Valuable Professional for Microsoft Azure. Oliver is author (co-author) of Implementing Azure Solutions and Implementing Azure Cloud Design Patterns, both available from Packt Publishing.
Markus Klein works as a technology solution specialist at Microsoft Germany, and specialize in Azure and Hybrid Azure scenarios. He is passionate about the Microsoft technology for more than 20 years, starting with System Center, Service Provider Foundation, KATAL, Azure Pack, Azure, and Azure Stack. Before joining Microsoft, he worked as an architect at Microsoft Cloud Partners. In 2007, he founded a cloud community and was the co-founder of some Azure meetups. Before he joined Microsoft, he was recognized as an MVP in cloud and datacenter management for seven years. He supports the community and is a regular blogger and speaker at conferences in Europe and abroad.
Mohamed Wali is a cloud DevOps engineer based in Amsterdam who has been working with Microsoft technologies for around seven years. He has been working with Azure since 2013. In July 2014, Mohamed became recognized as the youngest Microsoft MVP in the world. He has already authored and co-authored multiple books about Microsoft Azure. He shares his knowledge and expertise through blogging, authoring books, and speaking at events.
Namit Tanasseri is a certified Microsoft cloud solutions architect with an experience of more than 11 years. He started his career as a software development engineer with Microsoft Research and Development Center in 2005. During the first five years of his career, he had opportunities to work with major Microsoft product groups, such as Microsoft Office and Windows. During this time, he strengthened his knowledge of agile software development methodologies and processes. He also earned a patent during this tenure. As a technology consultant with Microsoft, Namit worked with Microsoft Azure Services for four years. Namit is a subject matter expert in Microsoft Azure and actively contributes to the Microsoft cloud community, while delivering top quality solutions for Microsoft customers. Namit also led the Windows Azure community in Microsoft Services India. Namit currently serves as a Microsoft cloud solutions architect from Sydney, Australia, and works on large and medium-sized enterprise engagements.
Rahul Rai is a technology consultant based in Sydney, Australia with over nine years of professional experience. He has been at the forefront of cloud consulting for government organizations and businesses around the world. Rahul has been working on Microsoft Azure since the service was in its infancy, delivering an ITSM tool built for and on Azure in 2008. Since then, Rahul has played the roles of a developer, a consultant, and an architect for enterprises ranging from small start-ups to multinational corporations. He worked for over five years with Microsoft Services with diverse teams to deliver innovative solutions on Microsoft Azure. In Microsoft, Rahul was a subject matter expert in Microsoft cloud technologies. Rahul has also worked as a cloud solution architect for Microsoft, for which he worked closely with some established Microsoft partners to drive joint customer transformations to cloud-based architectures.
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Table of Contents
Title Page
Copyright and Credits
Implementing Azure: Putting Modern DevOps to Use
About Packt
Why subscribe?
Packt.com
Contributors
About the authors
Packt is searching for authors like you
Preface
Who this book is for
What this book covers
To get the most out of this book
Download the example code files
Conventions used
Get in touch
Reviews
Getting Started with Azure Implementation
Technical requirements
Service models
Deployment models
Cloud characteristics
Multi-cloud characteristics and models
Cloud brokering
Best of breed
Microsoft Azure
Azure services overview
Azure basics
Azure Resource Manager (ARM)
Resources
Azure regions
Microsoft data center and backbone
Azure portal
Azure automation
Azure automation tools
REST APIs
Summary
Azure Resource Manager and Tools
Technical requirements
Understanding ARM
Functionalities provided by ARM
Working with ARM
Creating an Azure resource group
Adding a resource to a resource group
First approach – adding a storage account to your resource group
Second approach – adding a storage account to your resource group
Tagging in ARM
Locking Azure resources
Azure resource locks
Working with ARM templates
Exporting a deployment as an ARM template (for IT pros)
Example 1 – exporting a resource group to an ARM template
Example 2 – exporting a resource (classic) to an ARM template
Modifying an ARM template
Authoring an ARM template
Creating your own ARM template (for developers)
Summary
Deploying and Synchronizing Azure Active Directory
Azure AD
Azure AD options
Azure AD free
Azure AD basic
Azure AD premium P1
Deploying a custom Azure AD
Adding accounts and groups to Azure AD
Installing Azure AD Connect – prerequisites
Installing a basic Azure AD Connect environment
Azure AD Connect highly available infrastructure
Azure AD conditional access
Azure AD DS
Summary
Implementing Azure Networks
Azure networking limits
Azure networking components
Azure virtual networks (VNet)
VNet peering and global VNet peering
VNet service endpoints
Azure VPN gateways
Azure local gateway
Azure virtual WAN
Azure ExpressRoute
Route filter
ExpressRoute Direct 
ExpressRoute Global Reach
Azure connections
Azure route
Azure Firewall
Azure third-party network devices
Azure load balancer
Hash-based distribution
Port forwarding
Automatic reconfiguration
Service monitoring
Source NAT
Azure Application Gateways and Web Application Firewall
Web Application Firewall 
Azure Traffic Manager
Azure DNS
Azure DDoS
Setting up Azure networks
Setting up Azure VNet
Setting up Azure virtual network site-to-site VPN
Configuring local network gateway
Configuring Azure virtual network gateway
Configuring connection between local and virtual network gateways
Setting up Azure virtual network with MPLS and ExpressRoute
Configuring Azure virtual network gateway
Configuring Azure ExpressRoute circuit
Setting up Azure VNet peering
Preparing the deployment
Configuring VNet peering
Configuring custom routes
Common Azure network architectures
Summary
Implementing Azure Storage
Storage accounts
The Blob storage account
General-purpose storage v1 account
General-purpose storage v2 accounts
Azure File Sync/Storage Sync services
Azure Data Lake
Replication and redundancy
Locally redundant storage (LRS)
Zone-redundant storage (ZRS)
Geo-redundant storage (GRS)
Read-access geo-redundant storage (RA-GRS)
Azure Storage services
Blob storage services
Table storage services
Queue storage services
File storage services
Access keys
Exploring Azure Storage with Azure Storage Explorer
Premium storage accounts
Premium storage requirements
Pricing
How to deploy a storage account?
Summary
Implementing Azure-Managed Kubernetes and Azure Container Service
Technical requirements
Containers – the concept and basics
Microservices – the concept
Workloads to run in containers
Deploying container hosts in Azure
Docker on Linux
Windows Server Container VM
Azure Container Registry (ACR)
ACI
Creating a first container in Azure
Azure Marketplace containers
Creating custom containers
Container orchestration
The concept of container orchestration
Azure Kubernetes Service (AKS)
Summary
Azure Hybrid Data Center Services
Technical requirements
ASDK
Preparing the ASDK host
Identity management configuration
 Networking configuration
VM design of Azure Stack (ASDK)
Azure Stack configuration task
Operating Azure Stack
Working with the portals
Working with PowerShell
Working with the CLI
Hybrid cloud patterns
Configure hybrid cloud connectivity
Machine learning solution with Azure Stack
Azure stack staged data analysis
Azure Stack cloud burst scenario
Azure Stack geo-distributed Application
Monitoring Azure Stack
Summary
Azure Web Apps Basics
Introduction to Azure App Service
Azure Web Apps
App Service plans
Azure App Service Environments
App Service Environment types
Creating an App Service Environment
Creating an App Service plan
Creating an App Service
Summary
Managing Azure Web Apps
Deployment slots
Deployment slots key points
App Service application settings
Application settings key points
Azure App Service scalability
Scaling up
App Service plan scaleup key points
Scaling out
Scaling out the App Service plan manually
Scaling out the App Service plan automatically
Key points for autoscaling your App Service plan
Azure App Service backup
App Service backup key points
Summary
Basics of Azure SQL Database
Introduction to Azure SQL Database
Why Azure SQL Database?
SQL Database (IaaS/PaaS)
Azure SQL Database (PaaS)
Scenarios that would fit Azure SQL Database
SQL on Azure VMs (IaaS)
Scenarios that would suit SQL on Azure VMs
Azure SQL Database types
Elastic database pools
Single databases
SQL database managed instance
Service tier types
DTU service tiers
vCore service tiers
Creating an Azure SQL Database
Connecting to Azure SQL Database
Server-level firewall
Connecting to Azure SQL Database using SQL SSMS
Summary
Managing Azure SQL Database
Azure SQL elastic database pools
Benefits of using elastic database pools
Creating an elastic database pool
Adding a database to an elastic pool
Setting Azure Active Directory authentication
Azure SQL Database business continuity
How business continuity works in Azure SQL Database
Hardware failure
Point-in-time restore
Point-in-time restoration key points
Restoring a deleted database
Active geo-replication
Auto-failover groups
Azure SQL Managed Instances
Azure SQL Managed Instance types
Creating an Azure SQL Managed Instance
Connecting to an Azure SQL Managed Instance
Azure SQL Managed Instance key points
Summary
Microservices 2013; Getting to Know the Buzzword
What are Microservices?
Microservices hosting platform
The Microservice advantage
Fault tolerance
Technology-agnostic
Development agility
Heterogeneous deployment
Manageability
Reusability
The SOA principle
Issues with SOA
The Microservices solution
Inter-Microservice communication
Communication through user interface
Sharing common code
Composite user interface for the web
Thin backend for rich clients
Synchronous communication
Asynchronous communication
Orchestrated communication
Shared data
Architecture of Microservices-based systems
Conway's law
Summary
Understanding Azure Service Fabric
The Service Fabric advantage
Highly scalable
Support for partitioning
Rolling updates
State redundancy
High-density deployment
Automatic fault tolerance
Heterogeneous hosting platforms
Technology agnostic
Centralized management
Service Fabric as an orchestrator
Orchestration as a Service
Is a cluster resource manager similar to an Azure load balancer?
Architecture of cluster resource manager
Architecture of Service Fabric
Transport Subsystem
Federation Subsystem
Reliability Subsystem
Management Subsystem
Hosting subsystem
Communication subsystem
Testability Subsystem
Deconstructing Service Fabric
Infrastructure model
Cluster
Node
System services
Naming service
Image store service
Upgrade service
Failover manager service
Cluster manager service
Service placement
Application model
Programming model
Guest Executables
Reliable Services
Reliable Actors
Creating a cluster on Azure
Basics
Cluster configuration
Security
Summary
Viewing your cluster status
Service Fabric Explorer
Summary view
Cluster Map
Fault domains
Upgrade domains
Viewing applications and services
Cluster nodes
Actions
System
Preparing your system
Summary
Hands-on with Service Fabric – Guest Executables
Service Fabric discovery and communication
Service protocols
Service discovery
Connections from applications external to Service Fabric
Configuring ports and protocols
Configuring the service manifest
Configuring the custom endpoint
Configuring the Azure load balancer
Configuring the health check
Built-in communication API
Deploying a Guest Executable
Understanding the manifests
Package structure
Packaging Guest Executables using Visual Studio
Manually packaging a Guest Executable
Creating the directory structure
Adding code and configuration
Updating service manifest
Updating the application manifest
Deployment
Deploying a Guest Container
Deploying Windows Container
Container image deployment and activation
Resource governance
Container port to host port mapping
Container-to-container discovery and communication
Configuring and setting environment variables
Deploying a Linux container
Summary
Hands on with Service Fabric – Reliable Services
Exploring the Service Fabric Explorer
Application Type
Application instance
Service type
Partition
Replica
Stateless Reliable Services
Stateless service architecture
Stateless service lifecycle
Scaling stateless services
Stateless frontend and stateless middle-tier
Stateless frontend and stateful middle-tier
Reliable Services communication
Exploring the application model
Stateful service
Stateful service architecture
Reliable Collections
Up and down counter application
Stateful service lifecycle
Service partitioning
Service replicas
Summary
Reliable Actors
Actor model
What is an Actor?
Actors in Service Fabric
Actor lifetime
Saving state
Distribution and failover
Actor communication
The Actor proxy
Concurrency
Reentrancy
Asynchronous drivers
Timers
Actor reminders
Actor events
Your first Reliable Actors application
Summary
Microservices Architecture Patterns Motivation
Creating an architecture
Defining the solution boundaries
Creating the solution structure
Component design
Classification of architectural patterns
Optimization or non-functional patterns
Operational patterns
Implementation or functional patterns
Picking up the right architecture pattern
Context
Forces
Complementing patterns
Applying a pattern
Structural variation
Behavioral variation
Internal variation
Domain dependent variation
Summary
Microservices Architectural Patterns
Architectural patterns
Service proxy
Problem
Solution
Considerations
Related patterns
Use cases
Service Façade \ API Gateway
Problem
Solution
Considerations
Related patterns
Use cases
Reliable Data Store
Problem
Solution
Considerations
Related patterns
Use cases
Cluster Orchestrator
Problem
Solution
Considerations
Related patterns
Use cases
Auto-scaling
Problem
Solution
Considerations
Related patterns
Use cases
Partitioning
Problem
Solution
Considerations
Related patterns
Use cases
Centralized Diagnostics Service
Problem
Solution
Considerations
Related patterns
Use cases
High Density Deployment
Problem
Solution
Considerations
Related patterns
Use cases
API Gateway
Problem
Solution
Considerations
Related patterns
Use cases
Latency Optimized Load Balancing
Problem
Solution
Considerations
Related patterns
Use cases
Queue Driven Decomposing Strategy
Problem
Solution
Considerations
Related patterns
Use cases
Circuit Breaker
Problem
Solution
Considerations
Related patterns
Use cases
Message Broker for Communication
Problem
Solution
Considerations
Related patterns
Use cases
Compensating Transaction
Problem
Solution
Considerations
Related patterns
Use cases
Rate Limiter
Problem
Solution
Considerations
Related patterns
Use cases
Sagas
Problem
Solution
Considerations
Related patterns
Use cases
Master Data Management
Problem
Solution
Considerations
Related patterns
Use cases
CQRS – Command Query Responsibility Segregation
Problem
Solution
Microservices in CQRS
Advantages
Considerations
Related patterns
Use cases
Event Sourcing
Problem
Solution
Considerations
Related patterns
Use cases
Remindable Actors
Problem
Solution
Considerations
Related patterns
Use cases
Managed Actors
Problem
Solution
Considerations
Related patterns
Use cases
Summary
Securing and Managing Your Microservices
Securing the communication channels
Inter-node communication
Client to node security
Certificate security
Azure Active Directory security
Publishing an application to a secured cluster
Managing Service Fabric clusters with Windows PowerShell
Prerequisites
Deploying Service Fabric applications
Upgrading Service Fabric applications
Removing Service Fabric applications
Summary
Diagnostics and Monitoring
Health entities
Health state
Health policies
Cluster health policy
Application health policy
Service type health policy
Health evaluation
Health reporting
Centralized logging
Collecting logs
Diagnostic extension
Deploying the Diagnostics extension
Summary
Continuous Integration and Continuous Deployment
Continuous Integration
Continuous Delivery
Deploying Service Fabric application on a standalone cluster
Deploying the application
Summary
Serverless Microservices
Before committing to Nanoservices
Building Nanoservices with Azure Functions
Function app templates
Timer function apps
Data processing function apps
Webhook and API function apps
Summary
Other Books You May Enjoy
Leave a review - let other readers know what you think
Preface
This Learning Path helps you understand microservices architecture and leverage various services of Microsoft Azure Service Fabric to build, deploy, and maintain highly scalable enterprise-grade applications. You will learn to select an appropriate Azure backend structure for your solutions and work with its toolkit and managed apps to share your solutions with its service catalog. As you progress through the Learning Path, you will study Azure Cloud Services, Azure-managed Kubernetes, and Azure Container Services deployment techniques. To apply all that you’ve understood, you will build an end-to-end Azure system in scalable, decoupled tiers for an industrial bakery with three business domains. Toward the end of this Learning Path, you will build another scalable architecture using Azure Service Bus topics to send orders between decoupled business domains with scalable worker roles processing these orders.
By the end of this Learning Path, you will be comfortable in using development, deployment, and maintenance processes to build robust cloud solutions on Azure.
This Learning Path includes content from the following Packt products:
Implementing Azure Solutions - Second Edition by
Florian Klaffenbach, Oliver Michalski, Markus Klein
Learn Microsoft Azure by Mohamed Wali
Microservices with Azure by Namit Tanasseri and Rahul Rai
Who this book is for
If you are an IT system architect, network admin, or a DevOps engineer who wants to implement Azure solutions for your organization, this Learning Path is for you. Basic knowledge of the Azure Cloud platform will be beneficial.
What this book covers
Chapter 1, Getting Started with Azure Implementation, will help you understand how the basic services of Azure make up the core of an application running in Azure. We will also give the reader an idea as to how Azure influences Microsoft’s products and product strategy. We will explain the different Cloud Models and Multi Cloud strategies in conjunction with Microsoft Azure too.
Chapter 2, Azure Resource Manager and Tools, describes the Azure Resource Manager (ARM) concept, the ARM Tools Instrumentation and how it works. We show: Working with the Azure Portal and working with Azure PowerShell. Last, we will also describe the differences between classic deployment and ARM.
Chapter 3, Deploying and Synchronizing Azure Active Directory, will describe how to deploy Azure Active Directory, how to secure it for the next following steps and give some best practice advises when using Azure Active Directory together with other Microsoft Services like Office 365. Within the chapter we will describe how Azure Active Directory Synchronization could be implemented. We will give best practices which Synchronization method is the best for different environments. We will also explain how to secure and filter which accounts and attributes are synced.
Chapter 4, Implementing Azure Networks,in this chapter you will learn how to deploy and configure virtual networks in Azure and will get some best practice advises about working with subnets and network splitting. We will also provide an overview about routing in Azure and Network Devices in Azure.
Chapter 5, Implementing Azure Storage, in this chapter, you will get to know how to implement storage accounts in azure, the differences between accounts and give a brief overview about the different usage scenarios.
Chapter 6, Implementing Azure-Managed Kubernetes and Azure Container Service, will describe the general concept behind containers in Azure work, the need to have Kubernetes as an orchestrator, how AKS works and where Azure Managed Instances make sense, how they are created, deployed and managed.
Chapter 7, Azure Hybrid Data Center Services, will give the reader an overview how to implement Azure Hybrid Data Center Services using Azure Stack.
Chapter 8, Azure Web Apps Basics, covers one of Azure App Service, its different types, and how to work with them.
Chapter 9, Managing Azure Web Apps, covers some of the highly available solutions for Azure Web Apps in this chapter.
Chapter 10, Basics of Azure SQL Database, explores the Azure SQL Database, its types, and how to deploy it in Azure.
Chapter 11, Managing Azure SQL Database, covers other Azure SQL Database types and explains how to provide a highly available solution for them.
Chapter 12, Microservices 2013– Getting to Know the Buzzword, lays the foundation of concepts of Microservices and explores the scenarios, where Microservices are best suited for your application.
Chapter 13, Understanding Azure Service Fabric, explains the basic concepts and architecture of Azure Service Fabric.
Chapter 14, Hands-on with Service Fabric – Guest Executables, talks about building and deploying applications as Guest Executables on a Service Fabric cluster.
Chapter 15, Hands on with Service Fabric – Reliable Services, explains the concept of Reliable Services programming model for building Microservices hosted on Service Fabric.
Chapter 16, Reliable Actors, introduces Actor programming model on Service Fabric and the ways to build and deploy actors on a Service Fabric cluster.
Chapter 17, Microservices Architecture Patterns Motivation, provides an overview of the motivation behind driving Microservices architectural patterns. The chapter also talks about the classification of the patterns that are discussed in this book.
Chapter 18, Microservices Architectural Patterns, introduces a catalog of design patterns categorized by its application. Each design pattern explains the problem and the proven solution for that problem. The pattern concludes with considerations that should be taken while applying the pattern and the use cases where the pattern can be applied.
Chapter 19, Securing and Managing Your Microservices, will guide you on securing your Microservices deployment on a Service Fabric cluster.
Chapter 20, Diagnostics and Monitoring, covers how to set up diagnostics and monitoring in your Service Fabric application. You will also learn how to use Service Fabric Explorer to monitor the cluster.
Chapter 21, Continuous Integration and Continuous Deployment, takes you through the process of deploying your Microservices application on a Service Fabric cluster using Visual Studio Team Services.
Chapter 22, Serverless Microservices, helps you understand the concept of Serverless Computing and building Microservices using Azure functions.
To get the most out of this book
A basic knowledge of virtualization, networks, web development, databases, and active directory is required to get the most out of this book.
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Getting Started with Azure Implementation
Cloud services have come a long way in the last 5 to 10 years. Cloud was and still is one of the biggest trends in Information Technology (IT), with new topics still to be discovered.
In the early 2000s, cloud computing wasn't a widely phrase, but the concept, as well as data centers with massive computing power, already existed. Later in that decade, the word cloud became a buzzword for nearly anything that was not tangible or online. But the real rise of cloud computing with all its different service models happened before, when big IT companies started their cloud offerings. That was Amazon, Google, and Microsoft in particular. As these cloud offerings developed, they enabled companies from start ups to Fortune 500s to use cloud services, from web services to virtual machines, with billing exact to the minute.
In this chapter, we'll explore the following topics:
Cloud service models
Cloud deployment models
Cloud characteristics
Multi-cloud characteristics and models
An overview of Azure services
Technical requirements
To start with Microsoft Azure and cloud services, you need an active Azure subscription and an Azure tenant, which will be obtained with the subscription. There are different ways to order such an subscription.
The following list provides a few options:
Microsoft MSDN subscription
Microsoft Azure free trial
Microsoft Azure pass
Microsoft
Enterprise Agreement
(
EA
) with Azure commitment
Microsoft Azure cloud solution provider
Microsoft Azure in open licensing
Microsoft BizSpark program
Service models
Cloud computing is a new trend model for enabling workloads that use resources from a normally huge resource pool that is operated by a cloud service provider. These resources include servers, storage, network resources, applications, services, or even functions. These can be rapidly deployed, operated, and automated with little effort and the prices are calculated on a per-minute basis. This cloud model is composed of five essential characteristics, three service models, and four deployment models.
Cloud offerings are mainly categorized into the following service models:
Infrastructure as a Service
(
IaaS
): This describes a model where the cloud provider enables the consumer to create and configure resources from the computing layer upwards, without any need to care or know about the hardware layer. That includes virtual machines, networks, appliances, and lots of other infrastructure-related resources and services. The most popular IaaS resources in Azure contain virtual machines, virtual networks (internal and external), container services, and storage.
Platform as a Service
(
PaaS
): This gives the consumer an environment from the operating system upwards. So, the consumer is not responsible for the underlying IaaS infrastructure. Examples are operating systems, databases, or development frameworks. Microsoft Azure contains many PaaS resources such as SQL databases, Azure app services, or cloud services.
Software as a Service
(
SaaS
): This is the model with the lowest level of control and required management. A SaaS application is reachable from multiple clients and consumers, and the owning consumer doesn't have any control over the backend, except for some application-related management tasks. Examples of SaaS applications are Office 365, Visual Studio Online, the Outlook website, OneDrive, and even the Amazon website itself is a SaaS application with Amazon as its own consumer.
A comparison of service model responsibilities is shown in the following diagram:
Deployment models
There are also a number of deployment models for cloud computing that need to be discussed. These deployment models cover nearly all common cloud computing provider scenarios. They describe the group of consumers that are able to use the services of the cloud service, rather than the institution or the underlying infrastructure:
Public cloud
: A public cloud describes a cloud computing offer that can be accessed by the public. This includes individuals as well as companies. Examples of a public cloud are Microsoft Azure and Amazon AWS.
Community cloud
: A community cloud is only accessible by a specified group. These are, for example, connected by location, an organization membership, or by reasons of compliance. Examples of a community cloud are Microsoft Azure Germany (location) or Microsoft Azure Government (organization and compliance) for US government authorities.
Private cloud
: A private cloud describes an environment/infrastructure built and operated by a single organization for internal use. These offers are specifically designed for the different units in the organization. Examples are Microsoft
Windows Azure Pack
(
WAP
) or Microsoft Azure Stack, as well as OpenStack, if they are used for internal deployments.
Hybrid cloud
: The hybrid cloud combines the private and public clouds. It is defined as a private cloud environment at the consumer's premises, as well as the public cloud infrastructure that the consumer uses. These structures are generally connected by site-to-site VPNs or
Multiprotocol Label Switching
(
MPLS
). A hybrid cloud could also exist as a combination of any other models, such as community and public clouds. Examples are Azure VMs connected to an on-premises infrastructure through Microsoft Azure ExpressRoute or site-to-site VPN.
The following diagram depicts a comparison between Azure (public cloud) and Azure Pack (private cloud):
Cloud characteristics
Microsoft Azure is one of the biggest cloud service providers worldwide, offering a wide range of services from IaaS to PaaS to SaaS. It fulfills all of the characteristics that the National Institute of Standards and Technology (NIST) describes for cloud computing. These are as follows:
On-demand self-service
: This means an automated deployment of resources that a consumer orders through an interface such as a consumer portal.
Broad network access
: Providing availability of cloud services through a standardized network interface that is, at best, accessible by several endpoint devices.
Resource pooling
: This means that the automated assignment and reassignment of diverse resources from various resource pools for individual customers is possible.
Rapid elasticity
: It is also known as rapid scaling and describes the ability to scale resources in a massive way. The automatic and fast assignment and reassignment of resources, and rapid up and down scaling of single instances, are keywords when talking about rapid elasticity. The adjustment of web server resources depending on the demand is an example of rapid elasticity.
Measured service
: All data usage for consumer resources is monitored and reported, to be available for consumers and the cloud provider. This is one of the requirements for minute-based billing.
Multi-cloud characteristics and models
When defining multi-cloud, you need first to be aware of what a cloud service is. At this stage of this book, you already had some insight into cloud computing and cloud models and characteristics. Now, you should be able to identify the cloud services you already use in your company and that you might use in the future.
Multi-cloud means you or your company are using not only the services of one cloud provider, but different solutions from different cloud providers. That could be an example of using Microsoft Office 365 for business collaboration, Salesforce for CRM, and AWS Area 52 for GeoDNS and GeoIP, or even OpenStack or Azure Stack as your private cloud solution within your data center or co-location.
The following diagram shows a schematic definition of a person or company between multiple cloud providers:
Why use multiple cloud providers and not only one that fits all? There are different reasons why someone chooses a multi-cloud solution. Let me explain the most common reasons in the field:
Redundancy
: You don't want to build up your environment on only one cloud provider because one can fail, as happened with AWS in the past. So, you want to keep the business running with the services of another cloud provider. That's mostly a reason when using IaaS or PaaS. Redundancy is mostly not possible with SaaS if the cloud provider does not support hybrid environments.
The solution does not fit my needs
: Mostly when choosing a cloud solution, you see whether it fits your need. You mostly look to features such as data center location or performance. Sometimes, a cloud solution from my preferred provider does not fit those needs, so I need to choose another cloud provider with its solution. Often, you see that in Microsoft Dynamics CRM Online versus Salesforce, or your preferred provider does not offer a data center in South Africa. So, you may switch from AWS to Microsoft Azure for that reason.
The cloud provider does not offer the service I need
: Often, cloud providers are strong in one field and less so in others. This means they don't offer the services you may want; for example, you use Salesforce and want to have a unified single sign-on solution with Facebook, Twitter, or Instagram for your marketing teams. That's a service Salesforce does not offer at the moment, which means you may want to include Microsoft Azure
Active Directory
(
AD
) in your environment to achieve your goal.
Your departments use a cloud service as shadow IT
: I have seen
shadow IT in
nearly every company in the last 12 years of my work experience. It means a department uses a solution outside of the IT controlled area or solution field, managing the application itself without IT knowing of it. Often, it happens that those solutions become business critical and C-level management forces IT to take over the solution and support it. In times of easily accessible cloud solutions, this issue increased dramatically. Their are mostly two reasons for shadow IT:
IT departments aren't fast enough to deploy an appropriate on-premises solution
The user thinks,
Okay I only need a credit card? Let's try
.
The key elements to building and performing a successful multi-cloud solution is to build a uniform solution between all of the cloud providers. Those solutions are based on a uniform Identity and Access Management (IAM), network, and application infrastructure.
Within this field, you might see two flavors of multi-cloud.
Cloud brokering
With cloud brokering, you migrate your workload depending on the price and needs from one cloud provider to another. That can be on a day-to-day or more frequent basis.
This brokering was the first intention of businesses to save money with the cloud, but in practice, brokering only works with very simple IaaS or very standardized PaaS solutions. Most of the more complex workloads, such as Microsoft Exchange, SAP, and Oracle depend on drivers and you always have different hypervisor solutions between your cloud providers. In addition to that, IaaS workloads are very costly compared with solutions built on PaaS. So, looking down and ahead the timeline, the second multi-cloud model has become more common—best of breed.
Best of breed
Best of breed means you choose your cloud provider and a solution that fits for your needs and business requirements, or that is the market leader in a special area, for example, artificial intelligence, Network as a Service (NaaS), collaboration software, or data center distribution. Mostly, that means you will always end up with three or more cloud providers integrated with each other.
Microsoft Azure
When Windows Azure came online for the general public in February 2010, there were only database services, websites, and virtual machine hosting available. Over time, Microsoft constantly added features and new services to Azure, and, as there were more and more offerings for Linux and other non-Windows services, Microsoft decided in April 2014 to rename Windows Azure to Microsoft Azure. This supported Microsoft's commitment to transform itself into a services company, which means that, in order to be successful, you have to offer as many services as possible to as many clients as possible. Since then, Microsoft has constantly improved and released new services. Additionally, it constantly builds and expands data centers all over the world.
Azure services overview
Azure offers many services in its cloud computing platform. These services include the following:
The service categories, differentiated between platform services and infrastructure services.
The platform services are as follows:
Management
: These services include the management portal, the marketplace with the services gallery, and the components to automate things in Azure.
Compute services
: Compute services are Azure cloud services that are basically PaaS offerings for developers to quickly build and deploy highly scalable applications. The service fabric and Azure RemoteApp are also in this category.
Security
: This contains all of the services that provide identity in Azure, such as Azure AD, multi-factor authentication, and the key vault, which is a safe place for your certificates.
Integration
: The integration services include interface services such as BizTalk and Azure Service Bus, but also message helpers such as storage queues.
Media and CDN
: These are basically two services. One is the CDN, which makes it possible to build your own content delivery network based on Azure. The other is media services that make it very easy to use and process different media with the help of Azure.
Web and mobile
: These include all of the services that assist in creating apps or backend services for the web and mobiles, for example, web apps and API apps.
Developer services
: These are cloud-based development tools for version control, collaboration, and other development-related tasks. The Azure SDK is a part of the developer services.
Data
: The data services contain all of the different database types that you can deploy in Azure (SQL, DocumentDB, MongoDB, Table storage, and so on) and diverse tools to configure them.
Analytics and IoT
: As the name suggests, analytics services are tools to analyze and process data. This offers a broad range of possibilities, from machine learning to stream analytics. These can, but don't have to, build on certain data services. The
Internet of Things
(
IoT
) services include the fundamental tools needed to work with devices used for the IoT, such as the Raspberry Pi 2.
Hybrid operations
: This category sums up all of the remaining services that could not clearly be categorized. These include backup, monitoring, and disaster recovery, as well as many others.
The infrastructure services are as follows:
Operating system and server compute
: This category consists of compute containers. It includes virtual machine containers and, additionally, container services, which are quite new to the product range.
Storage
: Storage services are the two main storage types—
BLOB
and
file storage
. They have different pricing tiers depending on the speed and latency of the storage ordered.
Networking
: This category consists of basic networking resources. Examples are load balancer, ExpressRoute, and VPN gateways.
The important thing is to remember that we are talking about a rapidly changing and very agile cloud computing platform. After this chapter, if you have not already done so, you should start using Azure by experimenting, exploring, and implementing your solutions while reading the correlating chapters.
For testing purposes, you should use the Azure FreeTrial (https://azure.microsoft.com/en-in/offers/ms-azr-0044p/), Visual Studio Dev Essentials (https://www.visualstudio.com/dev-essentials/), or the included Azure amount from an MSDN subscription.
Azure basics
In the following section, we will take a look at the basic Microsoft Azure key concepts. This should provide an overview and an idea of how to use Azure.
Azure Resource Manager (ARM)
In the previous major version of Azure, a deployment backend model called Azure Service Manager (ASM) was used. With higher demand on scaling, and being more flexible and standardized, a new model called ARM was introduced and is now the standard way of using Azure.
This includes a new portal, a new way of looking at things as resources, and a standardized API that every tool, including the Azure portal, that interacts with Azure uses.
With this API and architectural changes, it's possible to use such things as ARM templates for any size of deployment. ARM templates are written in JavaScript Object Notation (JSON) and are a convenient way to define one or more resources and their relationship to another programmatically. This structure is then deployed to a resource group. With this deployment model, it's possible to define dependencies between resources, as well as being able to deploy the exact same architecture again and again. The next section will dive a little deeper into resources.
Resources
Azure resources are the key to every service offering in Azure. Resources are the smallest building blocks and represent a single technical entity, such as a VM, a network interface card, a storage account, a database, or a website. When deploying a web app, a resource called app service will be deployed along with a service plan for billing.
When deploying a virtual machine from an Azure Marketplace template, a VM resource will be created as well as a storage account resource holding the virtual hard disks, a public IP Address resource for initial access to the VM, a network interface card, and a virtual network resource.
Every resource has to be deployed to one specific resource group. A resource group can hold multiple resources, while a single resource can only exist in one resource group. Resource groups also can't contain another resource group, which leads to a single layer of containers regarding resources.
One resource group can contain all resources of a deployment or multiple resources of different deployments. There are no strong recommendations on structuring resource groups, but it's recommended to organize either the resources of one project/enrollment/deployment in separate resource groups or distribute resources based on their purpose (networking, storage, and so on) to resource groups.
Azure regions
Azure as a global cloud platform provides multiple regions to deploy resources to. One region consists of at least one highly available data center or data center complex. At the time of writing, 54 regions are distributed all over the world and include community clouds, so-called sovereign regions.
Microsoft also divides its regions into geopolitical zones, which can be found at the following URL: https://azure.microsoft.com/en-us/global-infrastructure/regions/.
These sovereign clouds where built by Microsoft to fit customer or governmental needs, such as for special compliance and/or data privacy laws. At the moment, the following sovereign clouds are available:
Microsoft Azure US
Department of Defense
(
DoD
)
Microsoft Azure US Government
Microsoft Azure China
Microsoft Cloud Germany
Microsoft Cloud Germany is also special among the sovereign clouds. Because of customer demands, Microsoft built up Microsoft Cloud Germany differently. Microsoft does not operate the cloud in Germany itself; they use a data trustee to operate the cloud for them.
Microsoft Azure staff and all Microsoft employees are not allowed to enter the data centers or lay hands on the servers or framework. Everything is operated by the trustee, starting with hardware maintenance up to updates of the framework.
Regions can also have an impact on the performance and availability of some resources. Some services may not be, or are only partially, available in a specific region.
The costs of offered services also vary by region. For reduced latency, it's recommended to choose a region next to the physical location of the consumer. It might also be important to see which legal requirements must be met. This could, for example, result in a deployment only in EU regions, or even regions in specific countries:
A
vailable Azure regions
:
https://azure.microsoft.com/en-us/regions/
Lists all the services available in specific regions
:
https://azure.microsoft.com/en-us/regions/services/
Microsoft data center and backbone
Microsoft operates two types of following data centers:
The first type is the production data center, where Microsoft calculates all workloads of its customers and stores all the data.
The second type is the edge or delivery site. Those sites connect all Microsoft Cloud services to the internet and Microsoft's customers. Edge sites come in two stages of expansion. The smallest one allows Microsoft public direct peering through the internet. With the second stage of expansion, Microsoft allows customers and providers to establish a private connection to the Microsoft backbone using the Microsoft Azure ExpressRoute service.
The following diagram shows a schematic of the Microsoft data center structure:
Edge and production sites are connected through the Microsoft backbone. Currently Microsoft owns and operates the second largest and fastest full meshed provider backbone of the world.. Microsoft also owns and operates own see cables such as the MAREA cable from Bilbao (Spain) to Virginia (US).
This map shows the current Microsoft Azure backbone with the new MAREA cable:
While building its backbone, Microsoft acts differently to the other cloud providers. Microsoft builds its own dark fibre cables or leases dark fibre cables and operates the whole backbone itself. Microsoft runs a fully software-defined network and infrastructure for its backbone, using firewall appliances built for network function virtualization.
If you ever have the chance to see a server rack that connects the Microsoft backbone or represents a Microsoft Edge site, it will probably look like this:
If you want to know more about Microsoft regarding data center equipment and software defined, I highly recommend you consult open source and open compute projects. Microsoft is investing highly in these and is very open in the following projects:
Microsoft cloud servers:
Open cloud server platform
:
https://www.opencompute.org/projects/server
ARM-based cloud server project olympus
:
https://www.opencompute.org/wiki/Server/ProjectOlympus
Microsoft network cards for backbone and cloud services:
Smart NIC
:
https://www.opencompute.org/wiki/Server/Mezz
Microsoft networking and switch software
:
Project SONiC
:
https://azure.microsoft.com/de-de/blog/sonic-the-networking-switch-software-that-powers-the-microsoft-global-cloud/
Azure portal
The Azure portal is a web application and the most straightforward way to view and manage most Azure resources. The Azure portal can also be used for identity management, to view billing information, and to create custom dashboards for often used resources to get a quick overview of some deployments.
Although it's easy to start with using and deploying services and resources, it's highly recommended to use some Azure automation technologies for larger and production environments. The Azure portal is located at https://portal.azure.com.
Azure automation
Azure automation is a service and a resource, as well as an Azure concept in the context of cloud computing.
It's very important to see automation as an essential concept when it comes to cloud computing. Automation is one of the key technologies to reduce operational costs and will also provide a consistent and replicable state. It also lays the foundation of any rapid deployment plans.
As Azure uses a lot of automation internally, Microsoft decided to make some of that technology available as a resource called automation account.
Azure automation tools
Azure provides several ways of interacting and automating things. The two main ways to interact with Azure besides the portal are Azure PowerShell and the Azure Command-Line Interface (CLI).
Both are basically just wrappers around the Azure API to enable everyone not familiar with RESTful APIs, but familiar with their specific scripting language, to use and automate Azure. The Azure PowerShell module provides cmdlet for managing Azure services and resources through the Azure API. Azure PowerShell cmdlet are used to handle account management and environment management, including creating, updating, and deleting resources. These cmdlet work completely the same on Azure, Azure Pack, and the Azure Stack, Microsoft's private cloud offerings.
Azure PowerShell is open source and maintained by Microsoft. The project is available on GitHub at the following link: https://github.com/Azure/azure-powershell. The Azure CLI is a tool that you can use to create, manage, and remove Azure resources from the command-line. The Azure CLI was created for administrators and operators that are not that experienced with Microsoft technologies, but with other server technologies, such as Unix or Linux. The Azure CLI is an open source project as well, and is available for Linux, macOS, and Windows here: https://github.com/Azure/azure-cli.
REST APIs
All Azure services, including the Azure Management Portal, provide their own REST APIs for their functionality. They can, therefore, be accessed by any application that RESTful services can process.
In order for software developers to write applications in the programming language of their choice, Microsoft offers wrapper classes for the REST APIs.
These are available as an Azure SDK for numerous programming languages (for example, .NET, Java, and Node.js) here at https://github.com/Azure.
Summary
In this chapter, we learned about cloud models and what cloud in general means. We now know how Microsoft fits into that ecosystem with its cloud services and their strategy. We also gained some very important insights into Azure and Microsoft regarding their data centers and backbone.
Azure Resource Manager and Tools
The Azure platform consists primarily of three parts—Azure execution model, which denotes the areas where you can provide your services and applications in the cloud; Azure Building Blocks; and Azure Data Services, which refers to services that extend the platform to common capabilities and functionalities.
I could actually forgo the description of the platform, because most users only get to see these three parts, but there are still more. Many other services are working under the hood of the platform and ensure its ongoing operation. These services include, for example, Azure Traffic Manager, Azure Load Balancer, and Azure Resource Manager (ARM). All of these services can be customized using various interfaces for your personal needs.
In this chapter, I'll introduce you to ARM in detail, and we will explore the following topics:
ARM and Azure resource groups
Azure resource tags
Azure resource locks
Working with ARM templates
Creating your own ARM template
Technical requirements
For running containers in a cloud environment, no specific installations are required, as you only need the following:
A computer with an internet browser
An Azure subscription (if not available, a trial could work too, at
https://azure.microsoft.com/en-us/free/
)
The code in this chapter can be found here:
https://github.com/PacktPublishing/Implementing-Azure-Putting-Modern-DevOps-to-Use
Understanding ARM
With the classic Azure system management, you could previously manage only one resource on the Azure platform at the same time. But what about more complex applications, as are common today? The infrastructure of today's applications typically consists of several components—a virtual machine, a storage account, a virtual network, a web app, a database, a database server, or a third-party service. To manage such complex applications, with the first preview of the Azure Management Portal 3.0, the concept of resource groups was introduced.
You now no longer see your components as separate entities, but as related and interdependent parts of a single entity. So, you will be able to manage all the resources of your application simultaneously. As an instrument for this type of management, ARM (and ARM tools) was introduced.
Enough of the preliminary remarks. Let's take a look at ARM in detail with the following diagram:
As you can see in the preceding diagram, ARM can be accessed through a variety of different technologies and interfaces. These access options include the following:
The traditional way, through the Azure portal (version 3.0 and newer)
The script-based way, through Azure PowerShell (look for PowerShell modules with the
AzureRM
prefix) or through the Azure
C
ommand-Line Interface
(
CLI
) (cross-platform CLI)
For developers, through Visual Studio
For developers, there are also SDKs available (
.NET
and some other programming languages) and, as with all Azure services, an extensive RESTful API
Let's go through the preceding diagram:
It consists of one or more Azure resource groups and one or more Azure resources. An Azure resource group is a container (a management unit), that all of the resources of your Azure solution contain. The Azure resource is any form of manageable element available through Azure (for example, a virtual machine, a virtual network, and so on).
