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DevOps class at INSA Rennes, CS dep

A team is composed of three students. Each team has to:

  • select a research paper to read and present;
  • build a DevOps toolchain for the app Spoon-web

Project

The given app Spoon-web is currently not built in a DevOps toolchain.

You have to select quality tools, improve the app, test its back and front, package, release, deploy, and monitor the app as automatically as possible.

Several points are mandatory.

Following the DevOps steps:

code

Mandatory:

  • put the project on the INSA gitlab instance
  • Add new features:
    • front-end: TODO

test

backend

Mandatory:

  • unit test
  • code convention (eg checkstyle)
  • linters (eg spotbugs, errorprone)
  • code coverage (fail if < x %)
  • mutation analysis (eg Descartes tool for extreme mutation)

To do so, complete the Maven configuration file.

Optional:

  • security analysis
  • performance testing
  • write new linters (eg using Spoon
  • or any relevant idea

frontend

Mandatory:

  • front-end unit test (need to mock the back-end and its REST API, HTTP interceptor)
  • system test (E2E testing) using Protractor.
  • code convention and linters (eslint)
  • code coverage (fail if < x %)

Optional:

  • security analysis
  • or any relevant idea

build

Mandatory:

  • A gitlab-ci file to specify how the back and the front are built
  • Launch a build on each commit thanks to gitlab-ci

package

Mandatory:

  • Write two dockerfiles to launch the back and the front as micro-services

deploy

Mandatory:

  • Continuous delivery: on each build success, the docker images are put on the gitlab INSA Docker instance registry
  • Continuous delivery: on each build success, the docker images are deployed on servers

Challenges:

Some tools: watchtower, https://github.com/pyouroboros/ouroboros, https://docs.docker.com/engine/swarm/, https://www.portainer.io/, https://docs.docker.com/compose/

operate

Mandatory:

  • A/B testing: have several backend instances that use different Spoon versions

Optional:

  • Chaos engineering: how to be resilient to failures?

monitor

Optional:

  • log useful data
  • use data mining techniques to extract information from logs
  • monitor crashes and provide feedback to developers

Some tools: logstash, eliasticsearch, kibana

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