Book Image

Distributed .NET with Microsoft Orleans

By : Bhupesh Guptha Muthiyalu, Suneel Kumar Kunani
Book Image

Distributed .NET with Microsoft Orleans

By: Bhupesh Guptha Muthiyalu, Suneel Kumar Kunani

Overview of this book

Building distributed applications in this modern era can be a tedious task as customers expect high availability, high performance, and improved resilience. With the help of this book, you'll discover how you can harness the power of Microsoft Orleans to build impressive distributed applications. Distributed .NET with Microsoft Orleans will demonstrate how to leverage Orleans to build highly scalable distributed applications step by step in the least possible time and with minimum effort. You'll explore some of the key concepts of Microsoft Orleans, including the Orleans programming model, runtime, virtual actors, hosting, and deployment. As you advance, you'll become well-versed with important Orleans assets such as grains, silos, timers, and persistence. Throughout the book, you'll create a distributed application by adding key components to the application as you progress through each chapter and explore them in detail. By the end of this book, you'll have developed the confidence and skills required to build distributed applications using Microsoft Orleans and deploy them in Microsoft Azure.
Table of Contents (17 chapters)
1
Section 1 - Distributed Applications Architecture
4
Section 2 - Working with Microsoft Orleans
10
Section 3 - Building Patterns in Orleans
13
Section 4 - Hosting and Deploying Orleans Applications to Azure

Monolithic applications versus distributed applications

In the following diagram, we have a classic monolithic hotel booking application with all the UX and business processing services deployed in a single application server tightly coupled together with the database on the left side. We have a basic N-tier distributed hotel booking application with UX, business processing services, and a database all decoupled and deployed in separate servers on the right side.

Figure 1.1 – Monolithic application (left) versus an N-tier distributed application (right)

Figure 1.1 – Monolithic application (left) versus an N-tier distributed application (right)

Monolithic architecture was widely adopted 15-20 years ago, but plenty of problems arose for software engineering teams when systems grew and business needs expanded with time. Let's see some of the common issues with this approach.

Common issues with monolithic apps

Let's have a look at the scaling issues:

  • In a monolithic app, there will be no option to scale up UX and services separately as they are tightly coupled. Sometimes scaling doesn't help due to conflicting needs of the resources.
  • As most components use a common backend storage, there will be a possibility of locks when everyone tries to access the data at the same time leading to high latency. You can scale up but there will be physical limits to what a single instance of storage can scale.

Here are some issues associated with availability, reliability, and performance SLAs:

  • Any changes in the system will need the deployment of all UX and business components, leading to downtime and low availability.
  • Any non-persistent state-like session stored in a web app will be lost after every deployment. This will lead to abandoning all the workflows that were triggered by the user.
  • Any bugs such as memory leaks or any security bugs in any module make all the modules vulnerable and have the potential to impact the whole system.
  • Due to the highly coupled nature and the sharing of resources within modules, there will always be resource starvation or unoptimized usage of resources, leading to high latency in the system.

Lastly, let's see what the impacts are on the business and engineering team:

  • The impact of a change is difficult to quantify and needs extensive testing. Hence, it slows down the rate of delivery to production. Even a small change would need the entire system to be deployed.
  • Given a single highly coupled system, there will always be physical limits on collaboration across teams to deliver a feature.
  • New scenarios such as mobile apps, chatbots, and analysis engines will take more effort as there are no independent reusable components and services.
  • Continuous deployment is almost impossible.

Let's see how these issues are addressed in a distributed application.

N-tier distributed applications

N-tier architecture divides the application into n tiers:

  • Presentation (known as the UX layer, UI layer, and the work surface)
  • Business (known as the business rules layer and services layer)
  • Data (known as the data storage and access layer)

Let's have a look at the advantages of a distributed application:

  • These tiers can be owned, managed, and deployed separately. For example, any bug fixes or changes in the UX or service will need regression testing and deployment of only that portion.
  • Multiple presentation layers, such as web, mobile, and bots, can leverage the same business and data tiers as they are decoupled.
  • Better scalability: I can scale up my UX, services, and database independently. For example, in the following diagram, I have horizontally scaled out each of the tiers independently.
Figure 1.2 – N-tier Distributed application scaled out

Figure 1.2 – N-tier Distributed application scaled out

  • The separation of concerns has been taken care of. The presentation tier containing the user interface is separated from the services tier containing business logic, which is again separated from the data access tier containing the data store. High-level components are unaware of the low-level components consuming them. The data access tier is unaware of the services consuming it, and the services are unaware of the UX consuming them. Each service is separated based on business logic and the functionality it is supposed to provide.
  • Encapsulation has been taken care of. Each component in the architecture will interact with other components through a well-defined interface and contracts. We should be able to replace any component in the diagram without worrying about its internal implementation if it adheres to the contract. The loosely coupled architecture here also helps in faster development and deployment to the market for customers. Multiple teams can work in parallel on each of their components independently. They share the contract and timelines for integration testing at the beginning of the project with each other and once internal implementation and unit tests are done, they can start with integration testing.

In this section, we discussed the advantages of distributed applications over monolithic applications and how easy it is to scale each of the tiers independently. In the next section, we will see challenges with distributed applications.