Book Image

Implementing Azure: Putting Modern DevOps to Use

By : Florian Klaffenbach, Oliver Michalski, Markus Klein, Mohamed Waly, Namit Tanasseri, Rahul Rai
Book Image

Implementing Azure: Putting Modern DevOps to Use

By: Florian Klaffenbach, Oliver Michalski, Markus Klein, Mohamed Waly, Namit Tanasseri, Rahul Rai

Overview of this book

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
Table of Contents (29 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
Index

Rate Limiter


Problem

Individual services in Microservice architecture have different Quality of Service (QoS) guarantees. If the processing requirements of the system exceed the capacity of the resources that are available, it will suffer from poor performance and may even fail. The system may be obliged to meet an agreed level of service, and such failure could be unacceptable.

Using auto-scaling pattern helps provision more resources with an increase in demand. This pattern not only consistently meets user demand, but also optimizes running costs. However, auto-scaling is not the optimal solution in the following scenarios:

  • The backend service or data store has throttling limits which affect the limit of scale the application can achieve.
  • There might be resource deficit in the window of time when resource provisioning is still going on:

Rate Limiter (Problem)

Solution

A solution to overcome the above mentioned issues is to allow applications to use resources only up to a threshold limit and...