Learn to implement microservices across a range of common tech stacks.

Scalability & System Design for Developers

In this module, we’ll look at some fundamental concepts for implementing microservices. Within each concept, learn about the different technologies used to implement it. The technologies include front-end integration with Edge Side Includes (ESI), asynchronous microservices with Kafka and REST feeds, synchronous microservices with the Netflix stack, and Consul, Docker, Kubernetes, Cloud Foundry. Each technology is described and then demonstrated with real code.

Microservice Architecture: Practical Implementation

# REST

Microservices platforms appear to be particularly suitable for synchronous microservices and REST communication, as they offer particularly good support for this.

# Frontend integration
The platforms can be extended to allow other communication mechanisms and frontend integration can be implemented with these platforms.


Client frontend integration is completely independent of the platform used. Only with server-side frontend integration would the server have to be installed and operated on the platform.

# Operation

The platform can also cover the operational aspect for asynchronous microservices. Better support for the operation of the microservices alone is a good reason to use the platforms. Operation is one of the most important challenges with microservices. This aspect is independent of the communication mechanism used.

# Physical hardware

The question arises whether there are other environments for the operation of microservices. A theoretical alternative to the platforms is physical hardware, however, physical hardware is hardly used any more for cost reasons.

# Virtual hardware

Virtual hardware is inflexible and heavyweight, so the only alternative to a platform is “docker without scheduler”. In this scenario, Docker containers are installed on classic servers.

In this case, the macro architecture standardizes the operation to use **only one
technology for log analysis or monitoring** and thus to work efficiently.


Microservices platforms **already have such features**. You do not have to build support for **logging or monitoring** yourself, but you can use these parts of the platform. This can be a simpler solution because implementing log analysis for many microservices can be very costly.

**Resilience** and other features such as **load balancing have to be
implemented** at the virtual machine level since the Docker infrastructure does not offer these.

 At the end of the day, it can
happen that the **features of a microservices platform** like log analysis, monitoring, reliability, and load balancing are **recreated step by step** instead of installing and using a prepackaged microservices platform.

In this lesson, we'll discuss some variations in the microservices platform approach that we have looked at so far.

Variations

REST