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Pragmatic Microservices with C# and Azure

Pragmatic Microservices with C# and Azure

By : Nagel
4.2 (11)
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Pragmatic Microservices with C# and Azure

Pragmatic Microservices with C# and Azure

4.2 (11)
By: Nagel

Overview of this book

Pragmatic Microservices with C# and Azure introduces .NET Aspire for microservices, focusing on defining an app model, utilizing service discovery, and integrating with Azure's native cloud services. Written by a Microsoft MVP and seasoned software architect with over two decades of experience in .NET, this book will help you get to grips with robust service development using .NET features like minimal APIs, gRPC, and SignalR for real-time communication. Aside from covering essential aspects of DevOps, including testing methodologies such as unit, integration, and load testing, you’ll also explore logging and monitoring including OpenTelemetry using tools like Azure Log Analytics, Application Insights, Prometheus, and Grafana. You'll learn about asynchronous communication leveraging queues and events through Azure Event Hub and Apache. Throughout the book, theoretical aspects will be complemented by practical skills gained from building and deploying a fully functional microservices-based application. By the end, you’ll possess a deep understanding of microservices architecture, hands-on experience with various .NET technologies and Azure services, and the ability to design, build, deploy, and manage microservices applications effectively in both on-premises and cloud environments.
Table of Contents (23 chapters)
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1
Part 1: Creating Microservices with .NET
6
Part 2: Hosting and Deploying
12
Part 3: Troubleshooting and Scaling
16
Part 4: More communication options

Scaling Services

How fast is the service responding? Is the service limited to CPU cores or memory? Based on user load, when is it useful to start more server instances? If you run too many compute resources, or if they’re too big, you pay more than is necessary. If the resources you use are too small, the response time increases or the applications might not be available at all. With this, you lose customers, and your income is reduced. You should know how to find bottlenecks and know what good knobs to turn to scale the resources as needed.

In Chapter 10, we created load tests to see how the service behaves under load, while in Chapter 11, we extended the service by adding telemetry data. Now, we’ll use both load tests and telemetry data to find out what scaling option is best.

In this chapter, we’ll start reducing the response time with the help of telemetry data before analyzing the load, which can be run with one instance. Finally, we’ll define...

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