Designing Distributed Systems - Labs
Labs for Designing Distributed Systems
The samples in this lab are written with the reader of this book in mind: https://azure.microsoft.com/en-us/resources/designing-distributed-systems/en-us/ and will guide you through the steps in designing and deploying distributed systems in Microsoft Azure.
1.1. Single Node Pattern: Ambassador
In this lab we'll guide you through the steps to implement the Ambassador pattern with NGINX in Kubernetes by deploying a request splitting service that will split 10% of the incoming HTTP requests to an experimental server. This request splitting service can then be used in a scenario where you want to test a new version of a back-end service with only a subset of the requests.
Go to lab: 1.1. Request Splitter
1.2. Single Node Pattern: Circuit Breaker Pattern
In this lab we'll guide you through the steps to implement the Ambassador pattern as a Circuit Breaker with NGINX Plus and Kubernetes. The Circuit Breaker patterns is extremely useful in scenarios where you want to help failing back-end servers to recover from failure, re-route traffic and perform rate limiting.
Go to lab: 1.2. Single Node Pattern
2.1. Serving Pattern: Load Balancing Server
In this lab we'll guide you through the steps to deploy a replicated load balancing service that will process requests for the definition of English words. The requests will be processed by a few small replicated NodeJS servers that you will deploy in Kubernetes using a pre-existing Docker image.
Go to lab: 2.1. Replicated Load Balanced Services
2.2. Serving Pattern: Decorator Function
In this lab you will apply the Decorator Pattern to implement a function in Kubeless that adds default values and performs transformations to the input of an HTTP RESTful API.
Go to lab: 2.2. Decorator Function
3. Batch Computation Pattern
In this lab you will apply the Copier, Filter, Splitter and Join patterns to implement a fully functional containerized and batch-processing thumbnail generator in Kubernetes that uses a pre-generated Docker image of the popular FFMPEG media conversion tool.
Go to lab: 3. Batch Computational Pattern
4. Contributors
| Roles | Author(s) |
|---|---|
| Project Lead / Architect / Lab Manuals | Manfred Wittenbols (Canviz) @mwittenbols |
| Sponsor / Support | Phil Evans (Microsoft) |
| Sponsor / Support | Anand Chandramohan (Microsoft) |
5. Version history
| Version | Date | Comments |
|---|---|---|
| 1.0 | April 23, 2018 | Initial release |
Disclaimer
THIS CODE IS PROVIDED AS IS WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESS OR IMPLIED, INCLUDING ANY IMPLIED WARRANTIES OF FITNESS FOR A PARTICULAR PURPOSE, MERCHANTABILITY, OR NON-INFRINGEMENT.
Azure Container Service (AKS)