Automation in microservices environment

Most of the microservices implementations are automated to a maximum, ranging from development to production.

Since microservices break monolithic applications into a number of smaller services, large enterprises may see a proliferation of microservices. Large numbers of microservices are hard to manage until and unless automation is in place. The smaller footprint of microservices also helps us automate the microservices development to deployment life cycle. In general, microservices are automated end to end, for example, automated builds, automated testing, automated deployment, and elastic scaling:

As indicated in the diagram, automations are typically applied during the development, test, release, and deployment phases.

Different blocks in the preceding diagram are explained as follows:

• The development phase will be automated using version control tools, such as Git, together with continuous integration (CI) tools, such as Jenkins, Travis CI, and more. This may also include code quality checks and automation of unit testing. Automation of a full build on every code check-in is also achievable with microservices.
• The testing phase will be automated using testing tools such as Selenium, Cucumber, and other AB testing strategies. Since microservices are aligned to business capabilities, the number of test cases to automate will be fewer compared to the monolithic applications; hence, regression testing on every build also becomes possible.
• Infrastructure provisioning will be done through container technologies, such as Docker, together with release management tools, such as Chef or Puppet, and configuration management tools, such as Ansible. Automated deployments are handled using tools such as Spring Cloud, Kubernetes, Mesos, and Marathon.