Top Microservices Trends of 2018

Posted by Lesa Moné

Top Microservices Trends 2018To meet the increasing expectations of business, today’s CIOs must make strategic decisions about their company’s IT architecture, and use the best-fit tools available to ensure innovation.

This blog post will outline the top supporting tools, infrastructure layers, and architectures for Microservices in 2018.

Increase in API-driven architectures

More companies will be inspired to move to a hybrid-cloud environment with a combination of the speed offered by APIs and microservices. API-driven development essentially makes the life of a developer easier and simplifies the process of app development. 

API-driven architectures take away some of the complexity of implementation, and bring in modularity which enables independent decoupled services to be integrated, implemented, and tested.  API-driven architectures are gaining popularity among IT teams in various enterprises because they enable faster app development, better documentation, and ease of interoperability.

Containers

Containers go hand in hand with microservices. They are both set to experience a higher level of adoption than in previous years. Scott Coulton, principal software engineer at Puppet predicts, "In 2018, I think we are going to see more distributed systems and applications, leading us to smaller units of applications. Container workloads will be the norm in production with Kubernetes reaching the masses, especially with the upcoming Windows support. The big technology to break through this year will be serverless, whether it is hosted by a cloud provider or on top a container orchestrator like OpenFaaS. This will allow business to be more agile now that consumers are expecting features faster." 

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Service meshes

service mesh is a dedicated infrastructure layer for making service-to-service communication safe, fast, and reliable. If you’re building a cloud-native application, you need a service mesh. Integrating with containers, service meshes help manage traffic through service discovery, routing, load balancing, checking health, and observability.

Service Meshes are not particularly exclusive to microservices or kubernetes environments. Service meshes can be applied to serverless as well.

 

Push and pull architectures.

Agile frameworks preempt the need for push and pull architectures. In a push architecture, the request for a given transaction is initiated by the publisher or central server. In a pull architecture,  the request for the transmission of information is initiated by the receiver or client.

In 2018, enterprises will utilize push/pull architectures at an increasing rate. Unlike traditional request-response architectures, in push and pull or event-driven systems, the functional process and transaction load in the establishing container does not rely on the availability and completion of isolated processes in subsequent containers. 

 

Microservice Management Platforms

The more microservices there are, the more convoluted the system becomes. Enterprises will use microservice management platforms to keep an overview of their microservice landscape. 

Consider using a professional Enterprise Architecture Management tool to visualize the relations between microservices.

Microservices — What an Enterprise Architect Needs to Know

 

Moving to GraphQL from REST

Created by Facebook in 2012 and open-sourced in 2015, GraphQL is an API specification that is a query language and a runtime for fulfilling queries. GraphQL allows developers to define data schemas, create new fields, and fields may be aged without affecting the existing queries or restructuring the client application.

 

Benefits of using GraphQL with microservices:

  • GraphQL allows you to clearly separate data owners because the request itself is pointed towards a single endpoint.  

  • GraphQL allows you to assert greater control over the data-loading process. Because the process for data loaders goes into its own endpoint, you can either honor the request partially, fully, or with caveats, and thereby control in an extremely granular way how data is transferred.

  • GraphQL can leverage powerful query planning. 

    By being able to send some queries to an endpoint, and have others execute in parallel at a later time per their weight and processor demand, you can effectively plan out queries over a relatively broad set of criteria and per the time allotted.

Choosing to make the change from monolithic code base to microservices is easy. Subsequently, operating a microservice architecture may present challenges. As microservice trend evolves, stay abreast of the different tools, trends, and supporting technologies to help create your desired microservice architecture. 

 

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