Microservices Reference Implementation

Microsoft patterns & practices

This reference implementation shows a set of best practices for building and running a microservices architecture on Microsoft Azure, using Kubernetes.

❗ The previous advanced Microservices Reference Implementation is now known as the AKS Fabrikam Drone Delivery reference implementation. The AKS Frabrikam Drone Delivery reference implementation is built on top the guidance forming the AKS Baseline Cluster. This basic Microservices Reference Implementation will remain here for your reference but we recommend you to consider basing your work on the AKS Fabrikam Drone Delivery reference implementation.

Guidance

This project has a companion set of articles that describe challenges, design patterns, and best practices for building microservices architecture. You can find these articles on the Azure Architecture Center:

Designing, building, and operating microservices on Azure with Kubernetes

Scenario

Fabrikam, Inc. (a fictional company) is starting a drone delivery service. The company manages a fleet of drone aircraft. Businesses register with the service, and users can request a drone to pick up goods for delivery. When a customer schedules a pickup, a backend system assigns a drone and notifies the user with an estimated delivery time. While the delivery is in progress, the customer can track the location of the drone, with a continuously updated ETA.

The Drone Delivery app

The Drone Delivery application is a sample application that consists of several microservices. Because it's a sample, the functionality is simulated, but the APIs and microservices interactions are intended to reflect real-world design patterns.

Ingestion service. Receives client requests and buffers them.
Scheduler service. Dispatches client requests and manages the delivery workflow.
Supervisor service. Monitors the workflow for failures and applies compensating transactions.
Account service. Manages user accounts.
Third-party Transportation service. Manages third-party transportation options.
Drone service. Schedules drones and monitors drones in flight.
Package service. Manages packages.
Delivery service. Manages deliveries that are scheduled or in-transit.
Delivery History service. Stores the history of completed deliveries.

Test results and metrics

The Drone Delivery application has been tested up to 2000 messages/sec:

	Replicas	~Max CPU (mc)	~Max Mem (MB)	Avg. Throughput*	Max. Throughput*	Avg (ms)	50^th (ms)	95^th (ms)	99^th (ms)
Nginx	1	N/A	N/A	serve: 1595 reqs/sec	serve: 1923 reqs/sec	N/A	N/A	N/A	N/A
Ingestion	10	474	488	ingest: 1275 msgs/sec	ingest: 1710 msgs/sec	251	50.1	1560	2540
Workflow (receive messages)	35	1445	79	egress: 1275 msgs/sec	egress: 1710 msgs/sec	81.5	0	25.7	121
Workflow (call backend services + mark message as complete)	35	1445	79	complete: 1100 msgs/sec	complete: 1322 msgs/sec	561.8	447	1350	2540
Package	50	213	78	N/A	N/A	67.5	53.9	165	306
Delivery	50	328	334	N/A	N/A	93.8	82.4	200	304
Dronescheduler	50	402	301	N/A	N/A	85.9	72.6	203	308

*sources:

Serve: Visual Studio Load Test Throughout Request/Sec
Ingest: Azure Service Bus metrics Incoming Messages/Sec
Egress: Azure Service Bus metrics Outgoing Messages/Sec
Complete: AI Service Bus Complete dependencies
Avg/50^th/95^th/99^th: AI dependencies
CPU/Mem: Azure Monitor for Containers

Deployment

To deploy the solution, follow the steps listed here.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.

pmsousa / microservices-reference-implementation Goto Github PK