Deployment, monitoring, and performance optimization of a microservices technology stack on Kafka, Kubernetes.

Déploiement, monitoring et optimisation de performances d'une pile technologique de Micro services, sur Kafka, Kubernetes.

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Technologies

• Docker
• Kubernetes (MiniKube)
• Helm
• Kafka
• Ansible
• Prometheus
• Grafana
• Python
• ElasticSearch
• Kibana

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Project structure

• ansible folder which contains the .yaml files to automatically deploy the application and its environment
• kubernetes folder which contains the .yaml files used by the Ansible scripts to deploy all the Kubernetes ressources
• scripts folder which contains the following .sh files:
  • chmodAll.sh: give the execution rights to all the scripts
  • deployEnv.sh: deploy all the environment needed for the application
  • launchExperience.sh: launch the execution of the application, retrieve the data and generate the graphs in the python/output folder
  • mnk-requirements1.sh: install Docker for Minikube
  • mnk-requirements2.sh: install Kubectl, Minikube, Helm, Python packages and Ansible

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Link to Experience

Experience Repository

First configuration with Minikube on a single, clean machine

NB: You must be in the root folder to use the scripts.

Requirements

• 18 CPU cores
• 18 GB of RAM

Steps

• Execute the following command in order to be able to execute all the scripts

chmod +x scripts/chmodAll.sh && scripts/chmodAll.sh

• Install Docker

scripts/mnk-requirements1.sh

• Once the previous script is done, exit the machine and reconnect to it in order to update the Docker users group, thus avoiding using the sudo su command everytime

• Install Kubectl, Minikube, Helm, Python packages and Ansible

scripts/mnk-requirements2.sh

• Deploy all the ressources

scripts/deployEnv.sh

• Launch the experience

scripts/launchExperience.sh

• PS: In order to reset the machine

scripts/resetCluster.sh